SaaSpocalypse Revisited, Singer x Louis Vuitton, Aman vs Ryan Walker | Igor Babuschkin, Brannin McBee, Garret Langley, Sonya Huang, Sean Cole

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We got to take a victory lap. You want to You want to start taking a lap, Jordi? You want to take a lap while I tell everyone about our SaaSpocalypse victory lap? We got—

Yeah, so I was just appreciating some various software as a service companies—

There's some real winners.

—charts yesterday.

Crazy winners.

A bunch of companies up like crazy. And I was thinking— I texted John. I was like, when did we cancel the SaaSpocalypse?

Yep.

And you pulled up our original Substack that we sent back in February. We just decided at that time, we're done.

It's not happening.

It's not happening. We canceled it.

And there was a lot of fear.

Maybe too early to take a victory lap, but in hindsight—

But there were some good arguments. There were some interesting arguments. And there was a lot of fear. But there were a lot of companies that were getting thrown in the SaaS bucket as just, like, a pure pile of code. You could vibe code it. And while that thesis might play out over a few years, it was a little bit too soon, it seemed seemed a little bit too aggressive. And so we wanted to revisit the SaaSpocalypse and the cancellation of the SaaSpocalypse, see where things are now. So just to set the stage, the SaaSpocalypse was a rough, rough go. $2 trillion of market cap lost across the SaaSpocalypse, the major sell-off of technology software companies broadly. $2 trillion wiped out, gone. Moment of silence. But a lot of it's come back. The iShares ETF that tracks tech and software is up 30% just over the last 6 months.

Did we want to do a moment of silence? Yes. Brought to you by CrowdStrike. Absolute tear.

Let me tell you about CrowdStrike.

This moment of silence is brought to you by CrowdStrike.

Your business is AI. Their business is securing it. CrowdStrike secures AI and stops breaches. No, CrowdStrike's been on a tear. So, yeah, it appeared only logical at the time that every company would be vibe coding their own CRM. CRM, and this would happen imminently, and that any company built on a big pile of code would go to zero. Of course, the core thesis still holds over the long term, but it's a lot messier in reality. So yes, having a huge monolithic piece of software is less of a moat today than it was a decade ago. That's for sure. Competition is increasing, especially for point solutions. But many of those SaaS companies that were so beaten up in the SaaSpocalypse were revealed to have sources of strength that didn't fit neatly into the lots of lines of code written bucket. So babies were thrown out.

1,000 business development representatives.

Yeah.

Source of strength.

That's big. Also, just another thing that's very valuable is what percent of revenue are you claiming from your customers? So if you are going to a customer and you're saying, I'm taking 30% cut, you're probably at more risk than someone who's saying, I'm an IT solution and you're going to spend 1/10 of 1% of your revenue.

Yeah, or Shopify is the best example, right? Yeah, I talked to Lucy about this. Yeah, a lot of e-commerce entrepreneurs, ask them like, what's your biggest expense? None of them will say Shopify.

Yeah.

Even a brand that is like a day old.

Shopify Plus for a business that I know very intimately, I think is around $1,000 a month in cost, and the business is doing almost $100 million a year.

And so even with 1%, even with how good models are today, you would need multiple people basically vibe coding around the clock.

Yeah.

To have a product that was comparable.

Yeah.

And that's not even to mention a lot of the applications that already tie into the product.

Yeah. And you could just put those tokens towards something else that moves the needle and increases revenue by 5% or 10%. There's so many other ways to move the needle. So a lot of babies were thrown out with the bathwater. The most ridiculous one was, I think, DoorDash. But there were lots of people coming for Spotify and a whole bunch of different platforms that should be very enduring because their source of strength is a network effect or something like that. So 6 months ago, we identified 6 companies that we wanted to use as case studies for the SaaSpocalypse. It was Google. Meta, your favorite company, Spotify, Shopify, Roblox, and Salesforce as evidence that large-scale software companies—

Do you have a minute to talk about Meta? I mean, I'm kidding. I'm kidding. I'm kidding.

And it always should have been.

Don't get me started. Never should have been beat up. Don't get me started.

It never should have been beat up. Same with Google. And then Spotify and Shopify were the interesting ones. Spotify, of course, there is a world where you're listening to AI music, but there's also a world where you're listening to AI music on Spotify. If you looked at Phoenix Flexin's Rubbers, the song of the summer in many ways, probably AI-generated, I think it's almost confirmed at this point that it's an AI-generated song. It has hundreds of thousands of downloads on Spotify specifically because that's where he chose to distribute it. Because if he had just left it on the internet somewhere, he's not going to get any royalties from it, and he's not going to get any distribution. So that's where the audience is, and having being an aggregator is extremely valuable. Ben Thompson was writing about this a bunch at the time. Same thing for Roblox. Yes, you'll be able to vibe code a game, but having all the Roblox network infrastructure distribution, that should be valuable in the future. So there were a few different things that might make you resistant to the coming age of agentic coding tools: marketplace dynamics, network effects, strong go-to-market organizations. Jordi put it really cleanly after Shopify's last earnings and when Shopify stock popped 20%, he said, Shopify isn't a victim of AI. AI is a victim of Shopify. And that really— it really made me think.

Yeah, there was certainly some money flowing out of semis.

Oh, that's actually true.

I didn't put it that way.

Into Shopify.

I guess you're right. I guess you're right.

It's got to come from somewhere.

I don't know if victim is right. But yes, clearly, you know, now you have a long list of unsloppable AI, unsloppable SaaS companies. Companies that can't just be immediately spun up and replaced by an AI app. There are AI winners now, and it's a lot of who you'd expect. Cybersecurity is more important than ever. You mentioned CrowdStrike, but Palo Alto Networks is also on a tear. Palo Alto Networks over the past year is up 121%. It's a $320 billion company. CrowdStrike's a $230 billion company, up 107% this year. Over the past 12 months, pretty remarkable. Nikesh Arora taking a little victory lap as well. So 5 months, Palo Alto CEO bought the dip. 5 months later, he must have been reading us because a month after we canceled the SaaSpocalypse, he was like, I think I like this Palo Alto Networks stock. Of course, he's the CEO of Palo Alto Networks. So but he put $10 million of his own money into the company. It's now worth $26 million. Nikesh Arora invested as investors questioned whether AI could disrupt cybersecurity. Palo Alto has reached an all-time high.

Got to give him— got to give him some trouble next time we see him. Why only 10? Oh, man. 10 should have— does that really move the needle?

Yeah, he should have been 10x levered. Yeah. If you really believed it. Come on. But, you know, he has $16 million of basically play money now. I mean, it's boy math. You know, you make— you make $16 million trading your own stock when you're the CEO. You gotta spend that on something fun. And as we know, Nikesh Arora was recently pictured on the golf course. So I was wondering, what does $16 million get you?

Probably buy a golf course.

You might be able to buy a golf course, but what does $16 million get you if you're a golfer in the Bay Area? You can join— you can pay for the initiation fees of 10 elite clubs. You can become members of SFGC, Cal Club, Olympic, Sharon Heights, Menlo, Burlingame, Pinedo Club, Lake Merced, Palo Alto Hills, and 1 or 2 Southeast Bay clubs for when you get out there. For $6 to $9 million, you can pay 30 years of dues at those clubs. And then guest fees, caddies, carts, food, tournaments, that's gonna run you $1 to $2 million. And so the 30-year lifetime total puts you around $9 to $12. Depends on what your tax rate is. I don't know the residency status. But for $16 million, you could plausibly fund a lifetime of belonging to essentially every major Bay Area private club that would admit you. With plenty left for golf expenses.

Fantastic. I think I do it. Nikesh, do it.

Nikesh, I want to see it every single day anyway. I mean, there are, there are SaaSpocalypse victims that have not come back, are probably not coming back, need to completely reinvent the business because they have been made obsolete by just base level LLM capabilities.

The classic— says with £16 million you could buy 640,000 pounds of ribeye.

That's another good usage of it. I think that might be up there. Skip the golf course and start bulking season. Chegg is the canonical example of SaaSpocalypse victim that has not made a comeback. The stock is down 99% over the past 5 years. It was hot during COVID And of course, when it comes to looking up answers to homework, the basic free edition of ChatGPT gets you there, Gemini, whatever you want to use. is going to answer those questions and hold your hand alongside your homework while you're doing it.

Yeah. So they had $376 million of revenue in 2025, but that was a 39% decrease year over year from $617 million in 2024. Yeah, it's now roughly an $80 or $90 million market cap.

Yeah. So it's a very shrinking business, very difficult. You have to continue cutting. Every year to make any money, pull any profit out of that business will be very difficult. The more— the newer company that is more in the headlines these days is The Information is reporting that Canva is slipping into a similar situation because a lot of Canva designs can be one-shot by image models like ChatGPT Images and Banana Pro, Grok Imagine. I saw the new Grok Image examples, and a few of them were infographics. They clearly figured out over there how to do high-fidelity text that doesn't have misspellings or anything like that. So you wind up with a product that if you're designing a birthday card invite, that's something that you would probably go to Canva before. Now you can just go directly to the models. And so there are SaaS companies that have to grapple with their product being more in the direct path of the models. But there are so many other SaaS companies that are buoying the index because they are either in the token path, like if you're a database or an analytics company or an infrastructure product that the labs are consuming and every AI company is using because they're like, well, we're generating a lot more data. We need a lot more Datadog or any other data company. Then those companies are doing really well on the back of that. And then there's also tools companies like Twilio is doing incredibly well. I don't know if you've been tracking this. It's up 150% over the past year. Another story where huge boom during COVID Wow. Sell-off.

$38 billion company.

Yep.

I— if you asked me what Twilio was worth before I just checked this, I would have said, I don't know, $5 billion.

Yeah. No, I mean, like that. And that's where it was a couple of years ago. But it's done really, really well. And I think a lot of that is that it is difficult to go and vibe code all of the interactions that you need to actually send text messages across the network.

It's agentic infrastructure, John. If you historically were a SaaS company, pivot to just be calling yourself agentic infrastructure.

It's more like— yeah, I mean, that's funny. It's more like it's infrastructure that will be Pulled off the shelf by the agent. And so, I mean, we use Twilio for our app where we want to be able to interface with an application via text message, and we use Twilio for that even though we could go and VibeCode that. All of a sudden, you're dealing with the different mobile carriers and the cell networks, and are they going to flag you as spam? And Twilio has all these huge decades of relationships built out.

Right.

And a real network there that even though it's just a tool, and it's just consumption software at the end of the day, it has this moat. And so it's been doing really, really well.

Sebastian in the YouTube chat says, not a fan of these earphone wires. What earphone wires?

Mine?

Mine's— yeah.

They're going crazy. They're going crazy. Thanks for the call-out. We have to talk about— Jiahu Yu. Oh yeah, traded. He is— this took us back in time as well. Let's try to pull up the original traded card that kicked it all off August of last year. I sent it to Jiahu Yu, went from OpenAI to MSL, was one of the first high-profile exits in that whole saga. And one year later, he just announced this morning, he said, I'm leaving Meta to start a new company building the TBD Lab alongside Mark. And Alex has been deeply inspiring and fulfilling. I'm proud of what our multimodal team accomplished across Muse Spark, Voice Mode, Muse Image, and Muse Video, and even prouder of the team that made it possible. Over time, I felt increasingly drawn.

He's calling out his laurels, but he's not resting on them. Over time, I felt increasingly drawn to a problem that will matter deeply to humanity's future, yet remains largely underexplored. It now has my full attention.

More to share as the work takes place, uh, takes shape. Uh, so anyways, I, uh, wanted to take a quick, quick little victory lap because I believe it was Monday or Tuesday.

The victory lap.

Um, yeah, Monday. Um, yeah, anyways, uh, Monday.

Are you— are you— given the situation that you're in right now, are you more of a victory lap guy or a pat on the back guy?

I like victory laps.

You don't like patting yourself on the back?

No, I've always found it awkward.

Yeah, it is sort of awkward to pat yourself on the back. A victory lap gets the blood flowing. It's healthy.

More ergonomic.

It's More ergonomic.

More ergonomic.

So, take your victory lap.

I forget what day it was. Maybe it was Monday or Tuesday when I was feeling a little spicy, but I was just saying that MSL is basically operating up against a clock, which is that they did this massive talent raid across all these companies about a year ago.

Yeah.

A lot of people went to other companies.

And when you're paying these people 9 figures, 10 figures, many of those people are gonna basically spend a year and hit a point where they're like, OK, I have $100 million in the bank, and I'm kind of good now.

25% of a huge pile of gold is still a huge pile of gold sometimes.

Exactly. And a lot of those people are just gonna basically see the number in their bank account and be like, am I happy doing what I'm doing? Is this fulfilling, or do I wanna go build a company? Maybe they've always wanted to build a company. And so, In the case of Jiahu Yu, whatever package he had, clearly, he's down to go take a risk.

Yeah.

You could argue how risky is it for him to actually really start a company. I'm sure they'll raise a massive round out the gates. I'm sure he could always get acquihired in somewhere else too, even if the company doesn't work. So, it's not like he's taking on, I would say, that much risk by going to start a company right now. But that being said, I don't think this will be the last of the exits that we see out of MSL over the next even 1 or 2 months.

What if he starts a social network? That would be risky. What if he's like, I'm coming for it all?

I mean, he says, I've felt increasingly drawn to a problem that will matter deeply to humanity's future. So maybe he's figured out how to make aligned social media, better reels, social media safety. I like that.

Yeah. Well, we should let Tyler pat himself on the back for this.

Reels that make you go like this.

But first, let me tell you about Console.com. Console builds AI agents that automate 70% of IT, HR, and finance support, giving employees instant resolution for access requests and password resets. Tyler, take a— pat yourself on the back because this card was the first TBN trading card and Tyler whipped it up. by himself and it doesn't even have our brand on it. And it also has a literal baseball field in the background. But this video or this, this image went so viral, the original post got 30,000 likes on X, was—

It did around 100K on Instagram. Yeah. Random account that again wasn't ours.

It was crazy. It actually broke containment.

Thanks, Tyler, for not watermarking it.

And it was the— it was the first— it was the first moment where we had been talking about a story that really broke through to the mainstream because of this trading card.

We wound up covering on French television.

French television. That's where I was going. That's where I was going. So but because of this trading card, we talked about this a whole— this whole story over a course of weeks. It was very interesting and dramatic. There were a whole bunch of scoops that came out around Mark Zuckerberg making people soup and stuff. It was a lot of really entertaining stuff. We were featured in the New York Times Daily podcast, I think once or twice for talking about it. They clipped us and included our coverage in their telling of the story for their broader audience. And then French television sent out a bunch of reporters and cameras to come and interview us, which was very funny because they kept asking us like, exactly how much money did this guy make? And we're like, look, we don't know exactly how much he makes. And even if we did, we probably wouldn't wanna share that. It was a very fair fight.

You did tell them there's no salary caps.

That's true. There are no salary caps. Anyway, let me tell you about Figma. Agents meet the canvas. Your AI agents can now create and modify your Figma files with design system context.

Instagram rebranded. Zach Pogrob says it's over. It's over? Instagram. The head of Instagram. Adam Masseri just posted a new wordmark after 10 years of leaving it unchanged. Adam says the wordmark at the top of the app hasn't changed in 10 years, so it was time for a refresh, cleaner and more modern with references to the original and the simplicity and craft that's always made it Instagram. So yeah, people, people don't like it. I don't, I don't. have necessarily super strong opinions on it personally immediately. I do think the original Instagram wordmark here on the left had started to feel extremely dated.

Mm-hmm.

But it's still iconic. And I felt like— I feel like we're headed back to this sort of maximalism and branding, right? However, I don't know how many years ago it was, like 5 years ago, all the big fashion houses started going from their historical wordmarks to updating them and making them much more simple and just—

Yeah, Balenciaga.

Yeah, yeah. And there's like 10 different examples. And so this move almost feels a little bit lagging in some ways where I actually like that the Instagram logo was— it did feel dated, but it was so distinct. All that being said, uh, people see the Instagram wordmark so much that this is going to be normalized probably within days, and people will just forget about it.

So I sent a different treatment that I thought they should go with. Yeah, it's declined. We can pull this up. It's right, right in front.

I mean, it's not too late. They could— I mean, this is their first time updating it, but I could see them updating it again tomorrow. Yeah, they like your version.

So I think that would Speak to me personally a little bit better. But, you know, their treatment, it's a choice. It's clean. No, I think this is—

Trey says, look, I'm not a fan of change. This is a war on history.

He's just blanket hating change.

I mean, that's actually— that's such a funny Perfect take because that's people's reactions to almost every logo change. It's like, look, I understand that you want a new logo, but personally, I'm just against change. I'm just against change.

That's hilarious. Yeah, this seems like a pretty minor iteration. So congrats to them. I'm sure— I think this will be well received. I wonder if there's going to be more brand Is there more unpacking around this? Is this— is there a message like, will this— will this new logo ultimately be tied to like Mark Zuckerberg's vision for AI? Is there more— is there more discourse that will come from like what the future of Instagram means, what the mission and values of the company are in this era? Is there something deeper here?

Yeah. The interesting thing is like they really just— they just tried to combine Like a new logo and the old logo.

It's very readable. I think it's fine. It has a little bit of articulation, a little bit of special treatment.

Yeah, I disagree on the readability part. Like the S, which they're taking from the historical wordmark, is way less readable in the new version. But I, again, it's such an iconic A lot of people are saying the R looks like a Z.

Oh, interesting. When I see the— when I see the, the S, I see the Tor logo for some reason. I see an onion.

Yeah.

You can pull up an image of this.

Yeah, I do too.

It looks a little bit like an onion sitting there.

Yeah. Onion mode.

What are they trying to message us with? That's subliminal messaging, right?

Instagzam. Says EZE. Yeah, readable. Tone says that R is so, so bad. I'm getting dragged. Instagzam. Anyway. Instaguam, says Michelle. It's got layers for sure.

You know what company has a great logo? Let me tell you about Cisco. Critical infrastructure for the AI era. Unlock seamless real-time experiences and new value with Cisco.

Cisco has a good logo. Matthew says, LOL, Jordi just never learned cursive. The original logo is cursive. I'm saying that that is, to me, more readable than this Frankenstein. But it will be fine.

Did Louis Vuitton ever do the clean rebrand? It looks like they might have. Is this the actual Louis Vuitton Vuitton logo. I mean, they still have the classic LV, but I think they did—

but the wordmark is—

I think they were a participant in the new wordmark in like the clean sans-serif font. I think it's time to move away from that. And I think, you know, they're taking risks here. I'll defend it and I think it will grow on me. It's also not the— like Instagram's been through a number of rebrandings and iterations.

So we'll see.

But speaking of Louis Vuitton, Louis Vuitton collaborated with Singer and created this insane Singer x Louis Vuitton collaboration for a 911 that looks like a handbag.

They actually made 2 of these. They're calling it the most tacky car ever.

I didn't know where you were gonna go. I knew I saw this all over the feed. I knew we were gonna be talking about it, but I didn't know where you'd set.

Yeah, so why is it tacky? It looks pretty— yeah, let's, let's play this video.

This isn't that tacky. I like the color. You don't like the color? The blue wheels are tacky. That— this part, that's nice.

Well, okay, the bag— the interior is just brutal.

The stick is pretty cool.

The hood with the straps, it's screaming tacky.

This part's sort of crazy. Yeah, this part's Helmets?

I don't hate the helmet. There's multiple cars.

Yeah. There's another version that doesn't have blue wheels. It's a little more subdued, but—

It is. So to me, part of the reason why it looks like, you know, a monstrosity is that it feels like they just— it feels like AI slop IRL.

Oh, interesting. I was—

And to me, it's not actually—

You wouldn't surf with that surfboard, Jordi?

But the problem is, like, I think that if Porsche had collabed with LV, maybe there would have been— like, it would have been toned down, like, a lot and probably be—

They did, right? Didn't Porsche do a collab recently? And we asked— We talked about this.

You're talking about the Toy Story collab.

Oh, that one was really good. I like that one. But I'm going back further.

But I'm just saying, like, this is not sanctioned by— this is, like, to me, like, a tacky unauthorized collab. And I know exactly the kind of person that would buy this.

They think—

I'm happy for them. We're sorry this happened.

This— when I saw this car, I was thinking that it feels less like something that you would drive and more like an art piece that you would put in a, in a house that has glass that you look through.

Vladimir says that the Singer looks like BDSM plus Hampton's Inheritance minus taste.

Oh, because of all the leather straps. Wow. That is wild.

Maybe they just don't believe that taste is the new moat. And they're just fading that whole take.

This is the one I was thinking of.

It says, buckles on the hood, LOL, perfect for a pilgrim.

It was the Amy Leon Dore, ALD Porsche 993. Turbo that we discussed, and I think you were skeptical about as well. Not big on these collabs.

Yeah. I think the main thing is they just went like 300% too hard.

They did. Yeah. It is very aggressive.

It's not subtle.

It is very aggressive. How do I add this?

Avery says the Shift boot is Pretty bad, not going to lie.

Let me see. Yeah, the ALD was much more subdued now that I'm looking at it. We can pull up these images. Look at this one.

Yeah, people are saying, next level gluttony.

Aspirated slop.

People do not like it. Well, it's not for everyone. It feels more like an art piece that you put in a luxury apartment that has glass. Between a seating area like a poker room and a garage.

Like in Dubai? Yes, probably.

Oh, it's Dubai. That's what you're referring to. Yes. This is Dubai.

Yes.

Okay, I understand now. But yeah, pull up the pictures of the ALD Porsche that was on the official Porsche YouTube channel.

So, must be real. Someone else says, that's the ugliest display of good craftsmanship I've seen in years. Yeah, what they've accomplished clearly was incredibly difficult, and they executed their plan seemingly very well. It's just that the plan was way too much.

Okay, pull up the ALD Porsche 993 Turbo collab video because I want you to see— I want you to review. You got to pick one. You're either driving Louis Vuitton or ALD, which one you going with, Jordi?

I mean, this was an actual collab between ALD and Porsche, and it was much, much, much more subtle. It was more subtle. And very well done, and the creative is well done.

Yeah.

I thought this was— I don't own anything from ALD to my knowledge. I've never been a part of, been a part of that brand. But, I liked this collab a lot.

Okay. Within this video, so you're going ALD over Louis Vuitton, over LV, correct? You're going ALD over LV if you had to pick between those 2?

100%.

Within this video, are you going ALD 911 or are you going Flock of Sheep? Which one would you take if they're— if you're offered, you can either have the Flock of Sheep Or the Porsche?

How many sheep?

Look at how many sheep there are. There's at least 20. Look at those.

I think you gotta go— I think you gotta go with the sheep.

You gotta go with the sheep.

Okay. I don't know. I don't know how much—

Honestly, I'm hoping that— I'm hoping that the flock is quite a bit bigger. But if you threw in the sheepdogs and with the sheep, I think you gotta go with the sheep.

Okay.

Michelle says, sheeps are useless. Trey says, those are nice sheep. I agree. They look like fantastic sheep.

Okay. We're going to find out how much a flock of sheep costs.

Ben says, that was a very wolf answer.

Okay. About 50 ordinary sheep in California, you're going to spend about $20,000. That's for 40— 48 breeding sheep.

So you're saying I should take— okay, so you're just saying I should take the ALD 911, put it on Bring a Trailer, and then you can buy 500 sheep. A billion sheep.

Not a billion sheep.

No, but I would lever up. I would lever up on the flock.

You're leveraging up. Okay, let me tell you about Codex. Codex is a powerful workspace for getting work done with AI agents, whether you're writing code, analyzing data, creating content, or— sorry. Or automating business workflows.

Code experts who move work forward. Satyrus Robotics, which is the company that makes the— what do we call it? The Centaur is in the YouTube chat. They say I pay around $300 a sheep. Icelandic. Saint Sheep cross, so they don't need shearing. Okay, good to know. We got sheep alpha in the chat.

We got some other—

yeah, they're, they're saying the sheep don't depreciate at the same rate. Well, but honestly, that could reproduce.

So with your 500 sheep, if you have the right— if you have the right mix of ewes and ewes and rams, uh, male and female sheep, you could potentially grow your flock into the billions, correct? Yes. Become a full-time sheep farmer.

Sheep billionaire.

Scale it up. Yeah. The new, like, shrimp farming hustle is sheep farming for sure. The last one in here is, I guess, the supreme 9/11, which that seems not authorized.

Nick in the team chat says, I'm a sheep the same way Odysseus is a sheep.

What does that mean? Is he a sheep?

People think he's a sheep, but he's really an absolute dog.

Oh, okay, okay. Okay, he's a wolf in sheep's clothing.

What in the slop is this?

I can't even tell.

Get that out of here.

Okay, anyway, let's do some other stories. New bombshell reporting from the Wall Street Journal reveals that North Korea has built a secret workforce inside American companies using stolen identities AI and accomplices in the United States to cheat its way into remote jobs and funnel hundreds of millions of dollars back to Kim Jong-un's regime. It's a fascinating story. The Wall Street Journal article is posted. It's a 30-minute documentary. They spent over a year investigating this. The FBI says that there are thousands of North Korean IT workers applying for jobs, applying for jobs across America. After a year-long investigation, the Journal obtained a trove of leaked browser histories, emails, calendars, and screen recordings from one cell of workers, providing a remarkable look at how the operation actually works. The North Koreans apply for jobs at enormous scale. One cell tracked by the Journal applied to more than 1,000 companies over just 3 months, using AI at nearly every step. And in the documentary, they show a product That is basically Cluely. They will leave a voice agent running while they're being interviewed in a technical interview, give the answer when asked about a particular technology. If they are proficient, they will simply have AI look up the answer, give the answer to the interviewer, get the job. And in some cases, they're using real Americans as frontmen. Basically, they will do the interview and then they will ship a remote laptop to say, hey, you're our new remote worker. You are qualified to work on our software engineering team at this small company. We'll send you a laptop and then you just collect a check, send half of it to the North Koreans, and you don't have to do any work. So, it's like passive income, free money for you, the American.

So, you said they're real Americans, but they're not patriots.

Yeah. That's what I'm hearing. Well, the documentary is pretty gut-wrenching. Like, the individual who they talked to who was Participating in this obviously is probably going to see some legal consequences for this, but it did seem like he had a very, very tough go and got into a very rough situation to be in that situation.

It was certainly not his first choice. Ryan in the chat has a hot take. Kim Jong-un is such a lovable rascal. It's hard to stay mad at him. Boo-hoo-hoo-hoo.

Boo-hoo-hoo. The operation also relies on help from inside the United States. North Korean IT workers pay American facilitators— they're called facilitators— to host company laptops in the United States, allowing the actual workers overseas to remotely connect to them while appearing to be employees working domestically. Also, the North Korean workers, they go to non-extradition countries, so they'll go to China and Russia and a few other countries, and then And from there, they will be remoting into an American laptop so it just looks like, oh, okay, they're like the web traffic is coming from— it's not coming from North Korea but it's coming from a country where if the FBI says, hey, can you send us this person? They're a criminal. That country says, no way. We're not sending them to you. So, for one job paying $75,000 a year, he said he and the North Koreans split the salary 50-50. The workers— How do you know that? They also use stolen American identities to pass employment screenings, often juggling multiple identities simultaneously and holding down several jobs under each name. This all boomed during COVID and the remote work boom. And the scale of the operation is enormous. Some North Korean IT workers earn as much as $300,000 a year. The Treasury Department says North Korean— says the North Korean government can seize as much as 90% of the wages earned by its overseas IT workers and recently estimated that these operations generated nearly $800 million in 2024 alone. Pretty, pretty big. So, the Journal's 30-minute documentary titled Infiltrated: North Korea's Secret US Workforce follows the operation in detail. It's a fascinating watch and I highly recommend that you check it out. So, go take a look.

I feel like it's important to ask, like, are they doing a good job? Like, because Presumably they're not just like hacking. Wow, really?

You're going to steelman this? Okay, I see where your loyalties lie.

No, it's like there's like the skit where it's like, oh, we're going to rob the bank and we're going to get a job there.

Yeah, yeah, yeah.

And over 30 years, they're going to deposit the money straight into our bank account every 2 weeks.

And what happens at the end? Yeah, we walk out the front door.

Yeah, it's like, oh, they're like hacking and they're stealing American dollars by working at the companies.

Yes. So there are sanctions. And because of those sanctions, America is not allowed to do business with North Korea in any capacity, including this one. So, this is sanctioned.

But, like, seemingly, it could be much worse, right? They could just be, like, hacking the company.

That's true. That's true. But they could also be doing both because once you let a North Korean IT worker in your systems, they could be planting all sorts of spyware, a very dangerous situation to be in. But, yeah, a wild, wild, wild story. So, everyone, if you're running a small business with some Remote headcount. Make sure to ask everyone to post something negative about about Kim Jong Un every day to prove their loyalty, I guess, or something. But there is a it opens with a very very funny clip of someone doing a remote Zoom interview and asking someone to say something negative about Kim Jong Un, and the guy's like, "Oh, I can't hear you. I can't I can't hear you. I can't possibly say that." Anyway, let me tell you about the New York Stock Exchange. Want to change the world? Raise capital at the New York Stock Exchange. Just do it. A new luxury hotel canceled a YouTuber's $4,663 stay. Then came the viral feud, reports the Wall Street Journal. A dispute between Aman, which we've talked about a lot on the show, and content creator Ryan Walker illustrates the growing tension between commercial enterprises and influencers. It's a fascinating story and Somebody's got to stand up for the Iman. Somebody has to. I'm ready.

No, honestly, honestly, I don't think the Iman actually needs that much standing up for.

No, the Wall Street Journal broke it down in great detail. This guy— it's bad for this guy. Anyway, let's go through it.

So should we pull up a little of Ryan's video? Yeah, yeah, for sure, for sure.

The social media video is titled—

he probably should have deleted it by now because it is extremely misleading.

It is crazy. It's still up.

It's in the title. And overly dramatic and not representative of what a normal guest experience would be like. Yeah, it is.

It is odd. Let me drop it a few different places, see if we can get this in here. Boom. So, the Wall Street Journal reports that it was supposed to be the hottest hotel opening of the year. Let's play a little bit of his video.

I am a luxury hotel reviewer. viewer here on YouTube. I specialize in very honest reviews of the world's best properties. I'm not going to give away too much as to what happened. I want you to watch the video.

And this is a cool thesis. Like, he pays for the hotels himself. He doesn't get paid by the hotel for the review. The hotel doesn't pay for his stay. And consequently, he can be more independent. This was the Doug DeMuro strategy. For years, Doug DeMuro said, I'm not taking press cars. I'm not going to your press event. I'm going to borrow the car from just someone who owns it, and I'm going to be able to drive it how I want to drive it, review it how I want to review it. And if you're Lamborghini or Ferrari or any other company, you're not going to be able to have any thumb on the scale of my review. Very good in concept, but the execution goes a little bit off the rails in this particular video. So you can see him pulling up to a guardhouse that looks woefully unfinished. It looks very, very rough.

Your name is Brian Walker? Yes. Yes, I know you.

Allow me to verify your information, okay?

Okay, thank you. What's going on?

Drama. This is such a strange area.

It's kind of like— They say cannot enter? Apparently, our driver is saying in Spanish that they are saying he cannot enter or pass. Excuse me, Mr. Walker.

Yeah. We don't have your reservation.

Do you need the number?

No, we don't have your reservation.

All right, we can pause. Let's let's get into let's get into the journals piece. Okay. Long story short, that video sparked a bunch of yeah. There's there's there's thousands of comments on there, people trashing. The property is basically fully taking his side.

Yeah.

But he—

And his side is basically that he showed up, he had a reservation, they didn't let him in, the place didn't seem together, he had a bad experience and he shares that with his YouTube audience, gets a lot of views for it. But the Journal dug in and provided a whole bunch more interesting perspectives. So let's go through it. The travel world was abuzz over the upcoming August 1st launch of Amanvari, the first Mexican resort from Aman, the multibillion-dollar ultra-luxury hospitality group whose mythos is built on seamless service, total tranquility, and fierce guest confidentiality. The new location is set within Baja California Sur's private Costa Palmas community, and the resort promised 18 Beachfront Casitas. So only 18 keys, a very small hotel, but very luxurious. So less than a week after its debut, the hotel was the center of a viral controversy in that YouTube video. He said he tried to check in for a one-night stay and he was turned away. So an Aman spokesperson told the Wall Street Journal, they went on record and they really clarified a lot. They said the deceptively edited video created by someone unauthorized to be on our property does not reflect the circumstances of the, of the incident accurately. Their dueling accounts reflect a new reality where cameras are always rolling, virality can outpace truth, and public perception is shaped less by what happened than who posts first. So on July 7th, Walker booked a stay at Amanvari. The YouTuber with more than 150,000 followers, pretty solid giant channel, has built a brand around paying full price for hotel rooms to guarantee honest reviews standing out amid influencers accepting free trips in exchange for positive content. He says, I'm honest and transparent. I'll tell you exactly what to expect and why. He had previously paid $26,000 for a Four Seasons yacht trip that he panned in May.

And sorry for the spoiler, he's not honest or transparent.

The same month, Walker posted a positive review of Aman Tokyo. Then he traveled to Amanvari on August 3rd. To hear Walker tell it in the video he showed the next day, he was a victim of a hospitality nightmare.

And one thing that's, I think, very funny right away is so, so you're going to review this hotel by a one-night stay, which, which means like, you know, maybe you check in. Yeah, it doesn't look like he wasn't going to get an early check-in either way. Let's say you check in at 4. You got to be out of your room by 11.

Yeah, that's not—

you got a 5-hour window where you don't even know. You— how could you— how could you accurately review the property when you're missing that incredible window from 11 to 4, right? Yeah, yeah, no, you just— it's a good point. You just don't have any context. Yeah, how can I trust your review? So I'm already— my guard is up.

So, uh, his video, which rapidly surged to more than 750,000 views, shows his vehicle approaching an unfinished wooden guard hut with stud walls still visible on the outside. In the interactions that follow, which appear to take place between 2 different gates, staff recognize him, inform him that he has no reservation, and according to Walker, eventually call the police to escort him away. Sounds terrible. As Walker drives off, he finds an email he says he missed sent the day before. It apologizes for canceling his stay due to scaled-back capacity during opening week. Not looking closely at timestamp, he tells viewers the email arrived late the previous night. When later pressed by the Journal, Walker revised his timeline, saying it arrived the previous morning. Walker did not amend the timeline in his video or in a subsequent livestream. The internet quickly took Walker's side. Viewers of his YouTube channel, including people who identified as Aman loyalists and travel industry professionals, expressed disbelief. We'll never book another Aman property again, read one of the more more than 5,000 comments, many of which expressed similar sentiments. Amon spokesperson said the company does not comment on bookings. Inspect the footage closely, though, and questions surface, notably around an absence of the police invoked in the video's title. Amon said it didn't call police and showed the Journal an incident report that made no mention of law enforcement. In the video, at one point in the encounter, a staff member says, I need to call the police now. Walker sees her on the phone, says off camera, yep, she's calling the police right now, but that might not have been related to him whatsoever. So that's like a very confusing situation. Later, he told the Journal he did not see police arrive on site. When the Journal told Walker that Iman said it had not called the police, he said he hoped that was true and that the information would make him reconsider how the resort had handled the situation. There is also the arrival gate that does not look like a typical five-star welcome, and we can pull up a picture of the actual welcome gate because it does look pretty ramshackle. The Amman spokesperson said Walker bypassed the main entrance, and he was looking for trouble access.

My theory is he knows exactly what he was doing. And the other thing is, it also came out that. They had reached out, they had called him, they had WhatsApped him, they had made numerous efforts to make contact, and I just think he wanted, he wanted the drama.

Probably.

Wyatt in the chat says, I want to have my hotels call the police on YouTubers.

So, um, the Aman spokesperson said Walker bypassed the main entrance, ending up at staff access points instead. Instead, ambient audio in Walker's footage captures someone saying, quote, this is the employee entrance. Walker told the Journal he had never heard the remark and that his driver followed GPS directions to the first entrance showed in the video. You can see it there. So internal documents provided by Walker show the resort emailed him 5 days before his visit telling him it was unable to allow stays involving content coverage until a month-long media blackout. and suggested he postpone his travel. Walker replied that the staff should consider him a standard guest. The property replied that it was prepared to welcome him, noting that he could post content after the media exclusivity window. So I'm sure they're doing a whole bunch of different press—

So he comes during the first week, books one night, knows that he shouldn't be filming, still decides to film.

Yeah.

And is effectively looking for trouble the entire time. And the crowd over on the Wall Street Journal loves it. The top-rated comment: I'm on, here I come. Any hotel that bans influencers is doing regular guests a great service.

Yeah, yeah. I mean, that's a big thing is that people go to certain places to not have cameras all over the place, and it's getting rarer and rarer.

And if it's so, it's so actually fascinating to look at the difference. YouTube comments are like, wow. I'm never gonna go to the Amman. And then Wall Street Journal is like, looking now. Walker is a complete tool, says Ray. Edward says, Edward says, seems Mr. Walker struggles with the truth. Oh wow. Second most highly rated comment.

Walker says he didn't.

And then someone else says, it takes a special sort of Jack star star star to make me side with the ultra luxury resort with holistic Wellness temples.

Yep, but that's the case we're in. A spokesperson for Aman said the resort also sent him a message on WhatsApp. The Aman spokesperson said the resort refunded Walker's booking in full, pledged to cover additional travel and cancellation costs, and help him rebook his stay. Walker said he received the refund but didn't take Aman up on the other reimbursements. He just showed up anyway. The dispute highlights growing tension between commercial enterprises and content creators looking to record on property. Jack Azon, CEO of luxury travel advisory Embark Beyond, noted that hotels maintain the right to cancel reservations or deny access. He added that properties immediately after opening should be approached cautiously. You don't need to be the guinea pig. Give it 6 to 8 months to grow minimum. In this case, nearly every claim has a competing account. Did Amanvari overreact to a content creator's opening week visit? To prevent an honest review, or did Walker turn a misunderstanding at the gate into a viral story? The luxury world may still value discretion; the internet values whoever sees it.

Ian the X Chat says, "Imagine staying on a 20-room property and having a YouTuber there. I would be seeking." So true. I wouldn't be surprised if they update their policies. We got to talk about McDonald's before our first guest joins.

In Wired.

Yeah.

Reese Rogers says, McDonald's built a 515-page dossier on me. It says I'll never stop eating there. He requested a copy of my data from the McDonald's loyalty program and received an extensive personalized report that algorithmically predicts my next purchase. This is amazing. Pulling up the—

The actual article.

The actual article.

McDonald's secret sauce is really commercial surveillance, says Jeff Chester, executive director at the Center for Digital Democracy, a group that advocates for consumer protections. Privacy experts I spoke with said this level of detail may feel invasive, but it's fairly standard for how large companies in the U.S. run their loyalty programs. The report contains specific pieces of personal information about you that were identified by searching McDonald's systems, which contain information about our customers. Tyler, you had the conclusion. What does McDonald's actually know about you? What does McDonald's know about an individual? That they like hamburgers. That's basically the takeaway, right? Like, the takeaway is, like, The number one most likely product is a large Diet Coke, then the spicy Snack Rack, then the Grinch McShaker Fry large.

We should figure out other companies that, that have these types of, uh, that have this type of data and, and request, uh, full reports. Yeah, we need our own reports. You want— I would love to read—

You want your 10,000-page report on what you like from Aril?

Yeah.

You're really going to go there?

Because I couldn't possibly know by looking at previous orders.

Glass bottled water. McDonald's.

Anthropic is apparently in talks to buy Descartes for $6 billion.

Getting into image generation.

We've had a bunch of awesome conversations with Dean over at Descartes. He's always— he's very, very early, he was willing to do live demos of their product, like interviews completely on, you know, we didn't even test with him before the show. He was just ripping them live. So always had a ton of confidence in the product and they've been just cooking.

They were valued at $4 billion a quarter ago. Himanshu has some extra context here, says Descartes could be one of the first AI labs focused on world video models to be a acquired by a Frontier AI lab. I think this also could mark an initial phase where Frontier Labs start treating world models as a major strategic capability alongside inference optimization as a major offering from Descartes. Yeah, interesting to imagine how this actually links to the core thesis of, you know, B2B and enterprise and and coding, but certainly an amazing technology that feels like on the verge of a breakout. The demos are amazing, but we haven't had the, like, Ghibli moment for world models yet. Like, it's very much prototype, demo video, go and see what it looks like. But we've talked to a lot of people, Oliver Cameron and Fei-Fei Li, about world models. There's a lot of optimism about— how this all plugs into the AGI pursuits of the Frontier Labs. Well, we have our next guest already in the waiting room, so let's bring in Igor Pavlushkin. But first, let me tell you about Railway. Railway is the all-in-one intelligent cloud provider. Use your favorite agents to deploy web apps, servers, databases, and more while Railway automatically takes care of scaling, monitoring, and security.

Thank you, Jordi.

And we'll bring in our next guest.

Here he is.

How you doing?

Hey guys, thanks for having me.

Thanks for hopping on the show. Welcome. Congratulations on the fundraise. But maybe let's go back in time. Tell us a little bit about your history and journey to starting River AI. And Jordi already has the gong ready, so just tell us the fundraising announcement, I guess.

Yeah, we just managed to raise $1.1 billion.

He broke the goblet. He broke the goblet. He broke the goblet.

He broke the goblet. The chosen one. You are the chosen one.

Okay. So see if it works out. So thank you guys. I started my career as a physicist. I was really interested in understanding the universe, but then realized that there was something really big happening, which which is AI, started to happen. And I think AlphaGo was really the moment when I started to feel like, wow, I got to switch and learn how to do AI. So I managed to join DeepMind. It was almost 10 years ago.

Wow.

I worked there on WaveNet. We trained a StarCraft agent that was really strong. So got into reinforcement learning there and then switched to OpenAI at one point. Was really interested in reasoning coding with LLMs, which now turns out to be something that works, which is pretty crazy to see. And then ended up co-founding xAI together with Elon. So I thought it was time for another frontier lab. I'm always in favor of more diversity in AI, more companies doing different kinds of things. So I was happy to support him building up xAI. And now with River AI, we're kind of taking that to the extreme. So I feel like the way we've been building AI is maybe not the way of the future. A few large corporations building these super powerful models. Everybody has to pay them by the token. We want to figure out how we can distribute AI to everybody in a way where you own it, you're able to shape your own AI systems. Maybe you have the inference running in your home or in your office. That would be the best achievement if we can figure out how to do that efficiently. And we're running a few different bets on how to help people build up their own AI. So we're helping companies build AI with the River API. That product's already out. So if you go on river.ai, You can log in and you can start training models based on open weights. So we support all kinds of very powerful open weight models. And then we're also using that platform to build out personal AI agents that are increasingly personalized to you. So as you're using them, they understand you better and better and it should really feel like you're building the AI, you're creating it.

Can we go back to your time at DeepMind working on video games? games. I'm so interested as— in video games as a benchmark. I saw someone using Codex to play Slay the Spire, and I've played a lot of Slay the Spire. It's pretty difficult. Now, it's a— it's not a fast twitch game, but I'm wondering if you— like, how would you think about the value of video games as a benchmark? There was another story about the FAA hiring Yes. ...traffic— flight traffic controllers who had previously played video games. So there's some sort of transfer where if you're good at video games and maybe SimCity, you might be good as a flight traffic controller. And you could imagine a situation where AI gets really good at playing video games and then becomes more useful in a whole bunch of different, you know, work-related tasks. But it feels like the gaming benchmarks are still toys, they're fun, they're people just doing them off on the side. But how do you think about the role of solving video games or testing models on video games in the modern era?

I think it's a great idea, but I might be biased. I used to play a lot of video games growing up. I still do some gaming from time to time. I think it's awesome. And I think the idea here is you want to test your AI on system— on problems that it hasn't necessarily been trained on directly.

Yeah.

So you want to have some level of generalization. And games are amazing because they have all kinds of complex things you might have to do, all kinds of problem solving you might have to develop on the fly. And that's kind of measurable how much progress you're making. So if you're getting to the end of the game, you're doing well. If you're making progress from one level to the next, that's measurable. So they have many, many properties that make them pretty ideal for measuring AI capabilities. And the craziest thing today is we have these powerful agents that have been trained mostly on coding tasks.

Yeah.

Like you give them some code base and you ask them to fix a bug or develop a new feature and they go out and they do all this tool calling to figure out how to do it and rewrite your files. But then you can also hook them up to a game and give them an API like here's how you control the units in the game or here's how you manage your resources or here's how you move around in Pokémon and other games like that. And I think it's It's crazy that these models are so capable at playing games and just shows you how much we've— how far we've come in terms of generality.

And yeah, where are the shortcomings though? Because, you know, I can think of one, which is like with a game, like you can basically run an agent, have the agent play a game infinite, effectively infinite amount of times. It can fail a lot. It can learn things like that. One of the challenges is in the real world, like let's say someone was making a sales agent Like an agent that wants to help you get customers. You can't necessarily just let the sales agent run wild in the real world, as a business at least, because it's going to mess up a lot. A bunch of customers are going to have a bad experience. And you could make— maybe the agent gets slightly better from that experience, but you could have lost a bunch of potential customers or pissed a bunch of people off or things like that. And so how do you think about making the jump from agents that are very effective at playing these games in a generalized way to agents that can be effective at long-running tasks in the real world that involve effectively complex groups that are third parties?

Yeah, that's a good question because most of the training today is done with synthetic environments. So it's— you're building up these RL environments inside of your AI team. And you're training the models with reinforcement learning. And so they kind of go for a simulation, you could say, and they're not really interacting with the real world when you're training them. And I think one of the big frontiers right now, one of the big developments you might see is actually the training moving into an online setting where the models are directly interacting with the users, with the companies that are using them. And as they're solving tasks, as they're figuring out what to do, we update the weights of the model. They get better and better. And it's a big research problem. Right now. So nobody knows how to pull this off in general. And the best agents, they've all been trained in simulation so far. But it's one of the things that we're working on at River AI. So if any of the viewers are interested in doing some research on this, reach out.

Yeah, it feels like we're not that far, at least in the gaming sense, to, in the training step, just create an environment that's just like, here's a Steam account and a credit card, go buy. every game and try and, you know, get the platinum trophy or, like, complete the game and feed that in. But the gaming thing is sort of a pure benchmark at this point because it feels like the labs haven't identified it as something that really they want to focus on. Can you talk about the tradeoff between, like, bench hacking for good and bench hacking for bad? Because there's the game that the labs are playing, but then there's also, like— product and, and it does the task and it classifies all of my taxes. I don't care if you bench hacked on that as long as it gets the job done. Right. And so there's this push and pull between those. How are you thinking about communicating that with your customers, your— the companies you work with who might be fine with a model that's only good at their specific task?

Yeah, exactly. I think that's a big opportunity for any company out there today because you own your own data that you've collected from your customers or from the work that you're doing. And if you eval the systems on that data, this is like the perfect eval for you. If you're able to improve your models based on that, you might end up owning the best model in the world for your particular task. So I think that's actually huge for companies. They should be building these specialized evals and they should be trying to build their own models. And the River API makes it easy to fine-tune your own model given your eval, given your own training. But in general, when it comes to AGI and improving the intelligence of these models, I think we want to hit them with some surprising benchmarks. If you want to measure generality, then throwing in a game that it hasn't been trained on, that it's never seen before, I think that's a very, very interesting measure to see how far out of distribution can they go? Can they do interesting things we haven't trained them for?

Huge, huge fundraising round. We've talked to Ajay a bunch, and he has a very interesting thesis around actually going much deeper in the stack, acquiring compute. How are you thinking about the uses of those funds? Because I could see coming to you as a company and knowing that you have the capital to go and really optimize all the way down to the stack and become a NeoCloud, build a data center for me, or help me with the more expensive stuff. expensive CapEx piece of the puzzle. At the same time, like, I don't really have a rule, like a solid frame of if I come to you and I say I want to fine-tune a near-frontier open-source model, is that actually that expensive? And wouldn't you just ask me to pay for that upfront? So that doesn't seem like a huge capital cost to you, but what is the shape of the cost that you are planning on incurring over the next couple of years?

Yes. So we're charging the customers really by the token. So if you have a fine-tuning run you want to do, if you have an RL run you want to do, you only pay for what you actually do.

Oh, interesting.

Choose some kind of model training run size that's perfect for your task. Some customers, they end up training a really small, really fast, efficient model because they've got the best data for that task and end up beating the largest and most expensive models out there. Other customers want something more general, or they want to utilize these larger open weight models like KimeK3 and others that are coming out. So that's a more expensive training run. But yeah, we obviously need a lot of access to GPUs to make that happen. The funding helps with that. But even if you have the funding today, you still need to get access to GPUs, and GPU prices are increasing steadily.

Yeah.

So I think what we're going to see is more and more investors collaborating with their portfolio companies. companies around compute, bringing up GPU capacity, distributing it among the portfolio companies. You know, some, maybe some of them need a little bit more in one month than others and so on and so forth. And it's a new kind of strategy that we're seeing, I think, to deal with the fact that compute prices are going up. There's so much scarcity.

Yeah. Would you say that's like one of the biggest sort of challenges for for River at this point is just compute planning. I mean, we've seen it. We've seen the full spectrum now. We've seen Sam last year, you know, getting really, really, really aggressive. And then we saw, you know, earlier this year Anthropic just sort of being caught off guard by the growth. And it feels like that is as, as a CEO, you know, you're, you know, it's a completely new skill set for— Yeah, it's like a new—

it's never a moment where Marc Benioff was like, I don't have Enough servers for Salesforce, I imagine. Like, they were way different problem set. But now it's, uh, yeah, demand planning is like a key, key, key skill set for a CEO.

Exactly. It's a totally new skill set that's super important. And it's so difficult because as a startup, by definition, you have this variance for the future. You don't know if you're going to grow by 10x or if you're going to grow by 3x over the next 12 months, right? So you have to play this really, really difficult poker game to figure out what is the right allocation for me, or maybe create some deals that are more flexible so you can actually scale up dynamically as the demand is growing. So I think we're going to see more and more of that happening. And yeah, so we're bringing up quite a bit of GPU capacity, and it's really important both for research and also to power the API. So as more people are starting to tune their own models, it's becoming very popular now. A lot of companies are reaching out about wanting to build their own custom models that they own and train on their own data using their own evals. So demand is going to keep going up, we expect.

How do you think about custom silicon over the next few years? YouTube, I believe, has a custom silicon chip for encoding video very efficiently because you upload one video, they need it in 360p, 480p, 720, 4K HD. And then we saw Talos bake the weights of LLaMA, I believe, into their chip and prove that that was, you know, exciting enough that AMD acquired the company. And I'm wondering if you imagine a future where a company comes to you like, you know, you can imagine like the Visa network is like, we want to run a transformer-based model on every transaction and it's going to be like trillions of prompts effectively or more. And so custom silicon might actually make sense, but then the models jump forward and you can do batches and there's, there's so many different tradeoffs. How do you think custom silicon will play in the diffusion story of AI?

Yeah, I think we'll see more and more custom silicon. Obviously, companies like Nvidia and AMD are also going to do extremely well, especially on the training side. Yeah, it's really unmatched what they're able to do.

Yeah.

On the inference side, there is some room for optimization because we believe that with personal AI agents coming up, so this is kind of the next evolution of agents after coding agents, which have been super successful. We expect that the demand for tokens will go up even further. So to the point where we don't even know how we're going to serve all these tokens for everyone given limited data center capacity. given all the bottlenecks in the data center supply chain. So I think we got to be smart and start to develop some custom silicon specifically for inference of these personal AI agents. I could imagine being much more power efficient with these kinds of chips. Can we maybe bake some of the transformer architecture into the chip to kind of exploit the fact that we know what kinds of models we're going to run? So that will make it more specialized. You might not be able to run any kind of model So Talos takes that to the extreme. So you can actually bake in the model weights. But today, you're not able to fit weights of very large models on a single chip that way. So that's the big bottleneck. So you're only able to do maybe 8 billion parameters or something like that, whereas the best models have trillions of params. So hopefully we're going to see some chips that are able to run those top-of-the-line models very, very efficiently.

Do we need more NeoLabs? Or basically, is there enough idea space that more people should be spinning up entirely new labs? I imagine a lot of the people that would be candidates to spin up labs themselves, you're probably trying to recruit.

Recruit, yeah.

But are we past peak NeoLab or are we just getting started?

Hopefully we're just getting started because this idea of building powerful coding agents, having APIs and so on, we all had this a few years ago at OpenAI and other places that that would be the future. But now that it's actually arrived, I think a lot of us are feeling like this can't be the end of the line. There has to be a different way to own and build AI systems. And so that means there's opportunities for research, there are opportunities for new kinds of business models. Totally new talent can move in. Somebody who doesn't have a big name in AI can do something really amazing today because they have to kind of have to think out of the box, come up with something that the AI expert that's been doing it for 10 years, they might not come up with it because it's such a wild idea.

Right.

So I think we're going to see a phase of innovation, totally new approaches to how AI systems are built, how you make use of them. And some really cool AI products as well for consumers. So that's what I'm looking forward to the most.

Yeah, what an exciting time. Well, congratulations and thank you so much for taking the time to come chat with us.

Yeah, excited for the next one.

Yeah, we'll talk to you soon.

Thank you guys. Cheers.

Have a good rest of your day. Goodbye. Let me tell you about MongoDB. What's the only thing faster than the AI market? Your business on MongoDB. Don't just build AI, own the data platform that powers it. Our next guest is the founder of CoreWeave. We have Brandon McBee coming back on the show after an insane Q2. Congratulations. Give us the headline numbers. How'd you do in Q2?

Q2 was phenomenal beat for us, right? That, that couldn't have come in better. We're extremely excited with the performance of the business and balance of the year is just going to keep on improving from here.

What's the biggest bottleneck now for you? Is anything changing based on all the data that you've collected over the first half of the year?

No, like bottleneck remains supply chain, right? Like that is the hardest part of this business. And it's also what we're best at, right? We have 51 data centers in operation today. We know how to navigate this supply chain. We know how to get this stuff online, delivered to clients, do so on time. It's immensely challenging, right? This is the most important commodity on the planet right now. And CoreWeave is singular in its ability to deliver the best performing infrastructure out there.

Mm-hmm.

You guys are spending a lot of time doing demand planning. Demand is obviously off the charts. What are you— we just had Igor on from, from River. We were talking with him about this sort of like new skill set that, that technology founders need to have around demand planning, right? You have a— let's say you have a neo lab, you're developing products. It's very hard to gauge how much demand you're going to have for them. The right strategy over the last couple of years was just to assume that demand was, was near infinite and sort of plan against that. But for smaller companies that, you know, have smaller balance sheets, it really feels like that is going to make or break a lot of these companies, especially, you know, neo labs that Yeah, that, you know, their margin profiles and all these other factors are going to come down to how well they can predict their own, their own demand for their products.

Yeah, I completely align with that sentiment, but I'd probably take it a step further. Like, what happens after that demand is planned for? How do you finance it? Right. And for us, that's been just an absolutely critical skill set that we've assembled team-wise over the last 6 years. And The latest financing that we did, DDTL 5, was a term loan B offering. I thought was a fantastic example of that ability to work with demand planning and get the right financing in place for that demand. That was the first facility that we've done where the contract duration is actually shorter than the amortization period. Right. In other words, it asks the investors in that facility to take on renewal risk on compute versus all of our prior facilities. Investors were fully covered by the original contract value, right? If it was a $5 billion loan, there was $7 billion worth of revenue sitting behind it. Right now it's opposite, like it flipped. And what that enables us to do is to spend more time in the shorter duration contract. Market because we just proved that it's financeable. And for us, that type of client is predominantly enterprise, right? The AI lab cohort, the hyperscale cloud cohort, they like to sit in the 5 to 6 year range because they know that they need that compute, they need that scale, they need it for that long duration. Enterprise is at the shorter end of that curve. And as you guys know, historically we've been really focused on the longer duration contracts, but Having this proof point in the market now that we can go finance these shorter duration contracts is, is really important to us. So I think that goes hand in hand with the demand planning aspect.

There's a ton of hyperscalers, I mean, that have been building data centers for a long time. There's a ton of neo clouds. How are you positioning differentiation? I imagine that demand is so strong that it's not the, the biggest thorn in your side by any means explaining the value, but it feels like it always has to be in the back of your mind as if demand ever softens. We want to be differentiated. We want to be differentiated even in a market that's tight on demand. So how are you positioning CoreWeave specifically?

Look, I think it's widely recognized by our clients, by third-party analysts, by our suppliers even, that we are the best representation of this technology on the planet. So that demonstration of value will continue to be through our technology product. It'll be through our timeliness in deliveries, our ability to scale across all different types of workloads, whether it's training, fine-tuning, inference. It'll be in delivering the best performance-adjusted FLOPS and token tokens out there.

Jensen was on CNBC recently talking about a $500 billion deal with a lot of big banks. What was your interpretation of what that deal means for the industry overall, where that project is going and how CoreWeave fits into that story?

I think it's wonderful for the space, right? It just continues to show the amount of capital that's willing to underwrite the buildout of intelligence. As you guys know, we've been at the forefront of financing this market for years. I think Having more capital in here is just great for the sector.

How have you been coaching people through? There's some folks that are like, "I'm worried this is like dot com." There's other people that I'm worried about this being like the mortgage, you know, boom. What what pieces are different this time? What pieces are okay? We are actually borrowing from this particular build out. A lot of people go to rail. Roads. There was, you know, a huge amount of value created. There were booms and busts in various times. What— how are you dealing with the various critics of the buildout?

So one of those points I feel like we talked about this last time I was on, I believe, was depreciation or useful life of compute. And, you know, the, the variable that we were able to introduce and highlight in our earnings is the A100 SKU.

Yeah.

Right, this is a 2020 SKU.

Yeah.

And we still have clients coming in asking specifically for that SKU, right? It's not like they're asking for Hopper and like, oh, we only have Ampere, or they're asking for Blackwell and we only have Ampere, right? Like they're saying, no, we want Ampere for workloads because that is the most performant platform for their workload. And we signed a contract in the quarter that goes out through 2029, right? That is now an implicit—

so it'll be a 9-year-old chip by the end.

9-year chip, right? And this is a take-or-pay fixed price contract. And pricing on A100s for us have held solid since early 2025. Yep. Right. It's like, I think one of those big criticisms was, well, this is 2 or 3-year compute and it's useless after that. We've been very consistent that 6-year depreciable life is accurate for this infrastructure. And I think that there is really strong opportunity for it to have material useful life beyond that. And we see it every day. Right. And it's, it's just in the way that AI workloads are being optimized across different SKUs. And it's this concept like there isn't one AI model to rule them all. There isn't one GPU to rule them all. It's just this matrix of different sizes of workloads relative to different sizes of GPUs where it's filling in across.

Yeah, my thesis has been that there are AI workloads that get, that get built out, maybe a recommender system, a basic text transformation system, a translation system, and then those will stay in place for a really long time and those will be used by more intelligent models. But then there is the question of just will the chips burn out? Has any Any thought change there, or is that pretty well understood?

Right, like this stuff is meant to run the data center. It's meant to run for long duration. We're not seeing any acceleration of burnout or like unexpected rates of errors. The infrastructure is doing great.

Yeah, that makes sense.

What is going on on the power side? I imagine there's a lot of people over the last year that have realized how important power is to this whole buildout and are trying to front-run players like yourself and get access to that power in hopes that they can resell it. I imagine the utilities are somewhat sophisticated at this point, and hopefully for a while will just call around and try to go directly to the operators. But What is actually— what can you share about like the current dynamics around that, that hunt for power?

I would say the power market is very competitive, but there is power out there. Right. And the bottleneck is less electrons for us. It's more of powered shell. Right. Or like delivered data center capacity. And that goes all the way down to the components that are in the data center. Right. Like think of the backup battery supply. Transformers, etc. But it's also the people, right? Electricians is a skilled trade that is a significant bottleneck for the industry, has been for some time, will continue to be for some time, because that's a trade that takes years to develop the skill sets necessary to be able to work in a data center site. So I believe that that is going to remain more of the bottleneck than power is right now. You're absolutely correct. I can't cap the number of emails I get a day from people I've never met before trying to offer us powered land all across the US. But I— that is less of the bottleneck and it's more on delivered powered shell capacity.

Are you hiring electricians directly or does this go through subcontractors for specific projects? This predominantly goes through subcontractors.

Subcontractors.

What?

Right. We have a little bit of self-build ourselves where, like, we're going out and sourcing GCs, contractors, etc. But for the most part, we lease capacity. Yeah. And that's been the way that we've scaled the business.

I imagine that there's a lot of folks in the organization that are technologists. They understand the technology and the hardware and the software and how everything pieces together. What are the other areas that you're hiring? What are you looking for in somebody joining? If somebody wants to join the CoreWeave organization that draws from a different pool of human capital or talent?

Going back to the point originally, financing, right? It's deeply important to the business. You know, we've, we've done a fantastic job assembling a team up in New York. We've raised, I think it's north of $40 billion in debt and equity over the last 24 months. Yeah. Wall Street investment banking hedge funds consulting private equity like all of the above yeah I'd say predominantly private equity private credit investment banking guys like deep financial backgrounds yeah yeah but look we're hiring across the business right it's engineering it's physical deployment teams I think we're it is our HR organization is doing a great job let's put it that way yeah busy How domestic is the footprint?

There's a lot of nervousness about the buildout in America. And my default interpretation would be if there's a lot of pushback in America, like people don't mind waiting 500 milliseconds for LLM responses. So yeah, you can put them in space, but you can also put them in, you know, another country. How are you thinking about the international opportunity?

I think that's right. But I would qualify more on like on the county level. Right. Like we're getting pushback. The whole industry is getting pushback at the county level in some places. But that ultimately doesn't change the fact that the demand is there. Right. Getting county-level pushback, state-level pushback, it just means that it's going to be built elsewhere because the demand for AI is the strongest it has ever been. The ROI on AI is the strongest that it ever has been as well. I mean, inference is, is absolutely profitable for our client base, which means that they're going to keep coming back to core products. We're in Canada, we're in Europe. We recently announced an expansion into APAC as well. I expect for us to keep, keep moving globally, but keep a focus on domestic deployments.

How strong is the correlation between social media pushback and and county-level pushback at like a city council meeting? Because I feel like there's sometimes a big disconnect where something can go viral, maybe it has some misinformation, gets 100,000 likes, but then the actual county and the residents are fine with what's going on. And it's sort of this like getting mad on behalf of someone. But do you see a correlation between a story or a news article that happens in this particular area and then there is actual movement on the ground at the local politics level?

Look, I'd say it's very specific to the sites. Sure. Right. Like we, we are engaged in conversations wherever the local communities would like to understand the value that we're bringing to that region.

Yeah, that makes sense. Jordi, anything else? Not for now. Congratulations and thank you so much for taking the time. Big one. Thanks, guys. Great to see you. Goodbye. Let me tell you about Shopify. Shopify is the commerce platform that grows with you. your business that lets you sell in seconds online, in-store, on mobile, on social, on marketplaces, and now with AI agents.

It's very interesting. It feels like one of CoreWeave's and some of the other NeoClouds' advantages is to just be able to be completely out of the politics and like the drama of AI, right? Like, oh yeah, all of the labs and hyperscalers and all these companies, like they have financial relationships, they have personal relationships, some of them Some of them hate each other and want each other dead. CoreWeave can kind of sit there like Switzerland and be like, anyone need tokens?

Yeah, that's true.

When a niche hit tweet fails to bang, James Heel shares a quote from Peter Jay. When a sub-editor complained that his— the Times columns were too Too complex. Peter Jay famously replied, I only write this for 3 people: the editor of the Times, the Chancellor of the Exchequer, and the Governor of the Bank of England. True. Not quite audience of one, but audience of 3 mentality. I think it's a good way to stay sane if you're posting online. You probably don't want to be too sucked into the algorithm, although this one may go viral. I don't know. Anyway, we have our next guest, Garrett Langley from Flock Safety. He's the founder and CEO. He's been on the show before, and we're very excited to talk to him about the latest news. Garrett, how are you doing?

He's back. Good. How are you guys?

We're good. Welcome back to the show. Thank you so much for joining.

Um, anything been happening since the last time you came on the show? I saw the news. Pretty chill. Pretty chill.

Um, imagine. Uh, well, let's kick it off with With the report in the Journal, Flock adds privacy guardrails after surveillance backlash. What happened? What are you actually implementing? What is the story?

Yeah, I mean, there's 2 big buckets, right? You've kind of got privacy and then accountability. And I can start with accountability because I think that's the bigger topic, or I think it's the bigger topic, which is, lo and behold, law enforcement abuses their power at times. And that's horrible, right? I mean, it's, it's really bad. And we built a tool about 4 months ago as a, as a test to kind of scan the audit logs that we've always had to look for abnormal behavior. You know, we solved a million crimes last year. We know what good investigations look like. We built this tool and the headlines over the last few weeks show you that we're pretty good at finding abuse. And I thought this was maybe just isolated to us. But what I found out is like when law enforcement searches DMV, they search criminal records. There's no audit logs there. There's no accountability. So we launched that. And I think you're going to see over the coming weeks, you know, more headlines of officers being arrested for abusing their position of power. So that's it. That's the— that's—

Yeah. Where does that actual— where's the oversight board live? Is this a separate product that's sold to like a district attorney effectively? Because if the person's like, yeah, I checked the audit logs, I was behaving poorly, that doesn't really do anything to stop the process, right?

No, no. Yeah. So it's a free product that all of our customers are now required to use.

Oh, okay.

Which we're the only company that I'm aware of in this industry that requires their customers to actually hold themselves accountable.

Okay.

For most of our cities we work with, there's a police administrator and then a city manager. that is reviewing the audit log. So, in the hopefully unlikely event that the police chief himself is the one committing a crime, the city manager is still there as the double-check.

Yeah. So, the business has grown a ton, and obviously, Flock products are deployed all over the United States. I'm interested in the backlash that has grown. You see a lot of videos with a lot of social media attention negative towards Flock. Is this actually showing up in your financials at this point? Like, because I imagine you have to replace any camera that is destroyed, but I can't tell if there's just one camera that's destroyed and then a million people view it and like it.

Yeah, no, vandalism is real. It's always been real, though. Just like weather has been a problem. You know, we deploy these products In Florida and there's hurricanes and in California and there's earthquakes. And so we're used to that. I mean, if you looked at the data, you'd be hard pressed to say, when did this TikTok trend blow up?

Sure.

You know, I'd say the sad part to me is you've got these influencers on TikTok and Instagram pushing this and they're convincing these 16, 18, 20-year-old guys to go do it. Yeah. And they're committing felonies. Yeah. It's like I saw this guy that got arrested in New Mexico, and he's gonna face 5 to 9 years in jail.

Wow.

And I'm like, that's horrible. This guy's life is over. He's got a felony on his record. He's going to jail to cut a camera down. It just seems really crazy.

So one thing that I've been identifying is it feels like there is a gap, particularly between liking a post on TikTok or engaging with anti-flock or the deflock campaign and maybe even going out in the world and chopping one down versus at least trying to go to your city council meeting. Because I just have to imagine— I've been to city council meetings. If there's 50 people there that are all taking the podium and saying, look, I am a citizen and I don't want flock in my city, city council will usually respond to that. Is that disconnect real? Like, what is going on there?

Yeah, I mean, look, it's surprising to me too because, you know, city councils are normally pretty boring meetings. And there's really only 2 topics that are being debated right now, which is data centers and Flock.

Interesting.

And you guys probably have better tools than I do. You can look at social media traffic and they're fully correlated.

Okay.

Which makes me wonder, like, Why? Because I've been asked this question, why now? And I'm like, I don't know. We've been in business for almost a decade. We went to thousands of city council meetings every year, I think over like 10,000 last year. We're not hiding anything.

Yeah. But no, it's just— to be honest, I think a large part of it is like, well, everyone's been talked to about AI safety one way or another, right? It might have been a viral clip of Sam Altman talking about AI in 2015 that gets resurfaced in like an Instagram reel today, and people assume that it was said today, and the clip was out of context. And then, but you have to look at like, I think people are like very scared of the technology overall, which I think is fair because they've been told to be scared in a variety of different ways.

Mm-hmm.

And then they're using AI in their life or in their work, and that's cool. But data centers present something that's like, a data center in your backyard doesn't necessarily give you an immediate benefit.

Mm-hmm.

And it could have some real downsides, right? Like noise or potential— there's all these sort of possible negative externalities. And then Flock, it's like when you— when, you know, Dario's talked a lot earlier this year about AI getting so good at looking over sort of like vast quantities of data and maybe the law is not sort of like staying, you know, moving quickly enough to respond to that. And so, like, Flock is like a very— I can see exactly why people are fixated on that because The product is clearly very, very good at fighting crime. But then also, also, if you are a bad actor, it's like the dream, like basically toolset, right? It's literally like in a video game, like God mode, right? And so I think like there's like very real— I can see why there's like a correlation, but I don't know if this is where you're going, but I don't necessarily think it's like some organized nefarious group that is like, we wanna shut down these 2 technologies. And so anyways.

No, I think there's some truth. I think the other thing that I think is true is, as I was asking someone, aren't you afraid of all the data brokers that buy your location data and sell it? And they're like, well, I can't see it. And I can see your camera. I think it's like a valid point, which is you drive by a flock camera and you say, well, I see it and I say I feel a lot safer. And some people might say, oh, I feel like this is Big Brother. And I go, it's like, but Big Brother wouldn't have an audit log and wouldn't have transparency and wouldn't do these things. But I do think a lot of the feedback is fair, which is like, how long should this be stored? And I think the thing we got wrong was expecting local government and state government to follow along fast enough. And I just, I don't think they are. And this accountability measure, like, no states require this. They all should. And like, we dropped our data retention recommendation from 30 days to 7 days, which means the majority of our customers will just simply accept the default.

Sure.

And state regulators have moved to 21 days. But like, we've done the analysis and we think we'll have a, you know, 10% reduction in efficacy. with that reduction, but I think it's a fair trade-off. And look, if the government wants to say, like in New Jersey, it's a mandate, 5 years of data retention, that's up to the state of New Jersey to decide. We'll push for what we think's right, but I might agree with Dario there in that case. Regulation is a good thing for this type of technology, and it needs to move faster, not slower.

Yeah, it seems like the speed of regulation is a huge issue here because the technology moves much faster. And I think folks on the left feel like they could be attacked by people on the right and vice versa. And so, if there's a new technology that rolls out like mid-cycle, all of a sudden you're grappling with it and your worst fears on the— on sort of like the extremes of the political spectrum are that they will be used by the opposing side. Aggressively against you, even if you are innocent. And I think that's where a lot of this is coming from. What do you think?

Yeah, no, I think that's true. I think the other thing, and I don't know who gets credit for saying this, you know, as a technology industry, we still feel like we're this bubble. Yeah, it's like a small part of the economy. And the reality, like, technology is the economy now. And I don't think as founders and CEOs, we've like fully grappled with what that means. And I think about someone like, you know, like Jamie Dimon. I'm like, he, like, has so much influence over our fiscal systems.

Mm-hmm.

And I think he probably understands that responsibility because banking has always had this, like, kind of austere posture of their responsibility in the world. And I think as technologists, we're catching up. And I think I'm in that same boat of, you know, we helped a million crimes last year. Last month we did 1,025 Missing peoples. That's real human life.

Yeah.

There's a real responsibility with that impact, and I'm glad we're catching up. We're not done. Like, we still have a lot of work to do. But I think if I look around the table, my other peers, like in public safety, I think we all have a lot of work to do.

Yeah, I think, yeah, there's been a very real positive impact of the product, and I think like people have every reason to also be concerned because even with these guardrails in place and audits, you have, even if you assume like a very, even a half a percent of police officers in the US are corrupt in some way or not, shouldn't be in these organizations, that's still thousands of bad actors that are in the system. And so, I think one of the challenges that I see is like, I feel like this is like too much of an too big of an issue for just you and the Flock exec team to be, to be in charge of, right? Like, I think you're very smart. I think this company was started for, for all the right reasons. I think it is having a positive impact in many ways, like you said. But at the same time, like, this is a national issue right now. You know, you're not elected. It's not your job to decide, you know, Americans like privacy. And so I think like, my question is like, what is happening at the national level? Obviously, counties and cities and states are trying to figure this out. But I feel like this issue is like beyond— I don't feel like this issue should be decided by you. I think it should be decided by our lawmakers because it comes down to our fundamental rights as American citizens. So I actually, I want this— the issue is just blown up on on social media. But I think it's time to, like, have a much more of a national kind of conversation about this. And then ultimately, probably new laws put into place to make sure something that you can point to and just say, like, look, like, we are abiding by the law in our country and our lawmakers who were elected.

And the correct path to push back on Flock is through the democratic process. Exactly. Call your representative. That does feel like the correct outcome.

But that, that feels very self-obvious. And it is interesting, you know, I was getting— saw someone push on X like you should require a warrant to use your product. And the response I wanted to make was, yes, when it is the law to need a warrant, yeah, we will happily follow the law. Sure. But 40 courts in the last few years have all deemed This isn't, you know, a violation of the Constitution.

Interesting.

And this is tricky though, because every state, every city has like a very different point of view on what safety looks like.

Yeah.

I mean, you look at, you guys, you know, hometown of San Francisco, San Francisco's own version of safety has also changed a lot in the last decade.

Totally.

And I think it's a better version today than it was 5 years ago, but it's still changed and it'll probably change again. And so it is a pretty tricky situation from setting the right laws, because I struggle to see how the federal government could establish a law that matches everyone's goals. And so my hope is, like, states— we had 9 state bills get passed this year. I'd love to see 20 or 30 next year that at least start to move this in the right direction. Because I do worry, like, any federal regulation will just make half the country mad and the other half of the country just as mad. Yeah.

In theory, like, city, even city by city, like, there is a— like, I think people might misunderstand that, like, Flock doesn't put up the cameras. They sell them to police departments. The cameras in those police departments have, you know, heads that are elected in many cases, right? There's like a sheriff that gets elected.

People who get to pick.

Yeah. But at the same time, I'm sympathetic to someone that basically thinks you put them up because it is It's an opaque process. Many Americans cannot tell you the names of everyone on their city council and who the mayor is and all these things or when the election is and how solidified that particular mayor is and whether or not they can actually apply pressure around this issue. It can take years to actually facilitate change in a community. And if you're in the minority, that might never happen for that particular community, but—

Yeah, yeah. I was referencing earlier with like more like friction. Like, we— there's historically been security cameras around in a lot of places. Yeah, private companies. You could get access to the footage, but there was a lot of friction to doing that.

Sure. Oh, yeah.

Which is good and bad, right?

Yeah.

It's good in that a bad actor is going to have a tougher time, like, putting together footage in order to understand someone's movement. But again—

Yeah, yeah. Everyone's comfortable with, like, there was an assassination attempt on the president. We should look at all the CCTV cameras.

You should get that first.

But then all of a sudden when it's like, okay, like now there's going to be an AI agent that's watching you, Jordi. If you speed at any point during your commute, you're gonna get, you know, a point on your license. It just feels like an annoying society that a lot of people don't wanna live in. And then there's a whole continuum there. We're grappling with the potential for way, way, a way higher level of enforcement and way less of a gray area around our rule set and our laws, which is something that the laws might need to change or we might need to adapt to. I don't know.

No, I agree. And I think to your point, like, I have a lot of sympathy for our elected officials at the local level. Because they now need to become experts in AI, public safety, data centers, water. Like, it's, it's like, and these are most of these times, these are part-time unpaid positions.

Yeah.

They're normally lawyers, doctors, real estate agents in their communities. And so, I mean, they sign up for the job, but it is, it's not straightforward. And, you know, we're, we like the way the system works today where every one of our contracts goes to city council for vote. That makes the job harder, but makes it transparent. Like I saw the other day, you know, I was able to find the video from 6 years ago when we did our first ever city council meeting and how nervous we were because we'd never been to city council. Like, what would that be like? And I've never been to city council. And now it's kind of just a part of our regular day.

Yeah. What's next? Because these updates are good, but I don't think they solve I don't think millions of Americans are still going to have— are basically probably not going to read the updates and are still going to have an issue. So what's on the roadmap? What more are you doing to try to find a solution to the concerns and the issues?

Yeah, I mean, I don't think we'll ever be done because I think this balance of privacy and safety is, is a bit of a moving target. Someone asked me the other day, you know, wouldn't it just be better just to turn off all the cameras? And I said, maybe 30 years ago when every single police department was fully staffed, maybe even overstaffed by today's standards. But today, more than 80% of police departments are understaffed. So I don't think, you know, a draconian no more technology is a viable solution. But I do think as a technologist, we have an opportunity to make better products that deliver on that kind of combined goal. And so for us, like, we're excited to get this— these tools out there into the wild. You know, I anxiously await potential headlines of more arrests in the coming days. I think that'll happen and that'll be tough because I think a lot of trust in communities will be broken. I think that trust was broken many years ago and now light's being shined on it. But I think for us, we're going to continue building tools that allow law enforcement to both do their job and build trust with the community at the same time. So we've got a lot of stuff coming up, a few more announcements coming up in the coming months, and we'd love to come back and share those when they're ready.

Yeah, that'd be great. Thank you so much for taking the time to come chat with us.

Yeah, don't envy—

Every possible take is being enumerated. It's a very interesting—

you want to switch jobs?

Yeah, yeah, yeah.

I don't think anyone in technology Envy's, uh, envy's your job right now. Um, but, uh, but the consequence of being consequential is what I tell the team.

So, yep.

Yeah, that's accurate. Well, have a great rest of your day.

Good to see you, Gary.

Thank you so much for the update and explaining everything. We'll talk to you soon.

Cheers.

Have a good one. Uh, we've been keeping Sonia Wong from Sequoia Capital waiting too long. She's a general partner. She's been on the show before.

It'd be great to just talk about— it'd be great to just talk about venture Capital for a little bit.

Well, now we get to back to AI. Back to these guys. How's it going? How's it going?

We haven't seen each other in a while.

Congrats on everything. Congrats on the acquisition. Thank you. Thank you. Great to see you. Yeah. So temperature check. What's going on with this AI thing? Is there anything there?

Temperature check. Oh my gosh. There is absolutely something there. The numbers we're seeing from these companies. Yeah. Never seen anything like it before.

For. But interestingly, it's less of a power— I mean, there's power law companies, Anthropic, OpenAI. There's a lot of companies that are doing really great. But then there's also this diffuse community of like NeoLabs and NeoClouds and so many different application layer stuff where you're seeing just really solid business fundamentals that previously would take a decade to build up. You're seeing it in 2 to 3 years.

Totally. The Anthropic and OpenAI and xAI are growing at a pace that nobody has ever seen before. But even if you remove them, this next cohort of companies—

Still great.

Arvy, Open Evidence, Glean, Factory— they're growing at rates that we've just never seen before. One of the most interesting things that's happening right now is we used to have this separation in our heads of there's the foundation model companies and then there's the application companies. And I would say one of the most interesting things that's happening now is that all the application companies are starting to build their own research capabilities, their own labs. And that's kind of like this concept of democratized intelligence. So I would say it's not only revenue that's not just accruing only at the first— at the top 2 players. It's the production of intelligence itself. Seems like it's very much democratized.

Yeah, we were— I don't know when Dylan was on. Maybe it was last week, but Dylan from Figma. Yeah, we were talking to him. I was like, I want Figma to work on the problem of— Design and code. Basically, slop has been this, like, you know, it's been— slop has been getting better and better. But, you know, it's basically like you have a new breakthrough and then for 2 months it's like, wow, it's so good now. And then you realize that it can only do, like, one style over and over and over. And I feel like there's all these application layer companies that are in such a great position to work on some of these fundamental problems that for better or worse, the labs are not able to focus enough on, right? Maybe it's only a billion-dollar revenue opportunity, right? And so, if you're a lab and you're adding billions of dollars of revenue a month with your core business, why would you work on a problem like that? And so, I think there's so many examples of that from from Figma to some of the other ones you mentioned.

Totally. And I think if you look at it from the perspective of the startups, there's just this huge wave towards companies wanting to own their intelligence. And I think a smaller set of companies has been beating this drum for a long time. Like, I'm on the board of Fireworks. Their tagline is own your intelligence. So they've been advertising this for a long time. Obviously, Cursor went on the journey 2 years ago of starting to train their own models. Um, but what's happening now is like, Both the giants in the ecosystem are starting to speak up and the startups are actually getting extremely good at building their own research. So in terms of the giants, you have people like Alex Karp talking about sovereign intelligence. He has this phrase, own the means of production, which I freaking love. Satya talking about your proprietary data. Jensen championing open weights. So you have all these giants of the ecosystem speaking up of like, hey guys, you should own your intelligence. And then if you look at it from the perspective of the little guys, the startups, who we are in the business of backing, a couple of years ago, they were primarily looking at, you know, moving, moving some of their intelligence towards these open weight models, primarily as a cost rationalization exercise. The thing that's different now is like it is an existential and strategic imperative for them. And so there's this, there's this phrase, you guys probably remember this from the crypto days, not your keys, not your crypto.

Yeah.

This idea of like if somebody else is custodying your weights for you, I don't— custodying your keys for you, it's not yours because something could happen to that brokerage. Something could happen there. And I think like, I think the AI version of this meme is not your weights, not your products. Because fundamentally, if you don't own the weights, if you are just making an API call, you don't have ownership, you don't have steerability, the data doesn't accrue to you. And so like people are kind of waking up to this. And so if your use case is like you want a coding agent, like for that, I'd say close model, close agents. That's fantastic. Yep. If it is like your core product, I think companies are increasingly waking up to like not my way, not my product.

If it's what you sell to your customers, it should be yours.

That makes a lot of sense.

Founder office hours. Coach me through. You're on the board of my hypothetical company, software company. I'm using AI, $500 million ARR, let's say. And I, and I buy this thesis and I come to you.

Pretty confident example there.

$500 million. Not bad.

There we go. We're cooking. We're cooking.

No, no, no. I mean, like, we have, we have fully made it through. We're, you know, an AI winner. We're accelerating, growing. Growth is great. But I come to you and I say, okay, I'm all in. We're going to own our intelligence stack. Is there a moment where we need to have a conversation about what the talent budget will be. I mean, we saw these crazy MSL deals. And for a lot of these companies, they might be unicorns, they might even be decacorns, but they're not going to be able to staff a team of AI researchers and build a full Neo Lab doing like next-generation fundamental research. So what does the team buildout actually look like? Is it enough to take your, your best software engineers and have them them use coding agents to fine-tune models for your team, or are you hiring entirely new disciplines? What is the correct shape of an internal AI lab at a successful scaled unicorn, decacorn software company?

Yeah. So typically, you're not going to be pre-training your own models. There are specific use cases where you actually need to pre-train models. That's a totally different thing. If what you are doing is trying to take off-the-shelf open weight models and then adapt them and make them really, really excellent for your domain. That's a much larger talent pool. And what we've seen is there's actually 2 flavors of talent that are really good at this. One is people that have done post-training before.

Okay.

So the post-training teams at the labs are very, very large at this point.

Sure.

There's plenty of these people floating around. And then the second profile is actually interesting, is just like, engineer, or I guess like just generally smart person, smart person, poker player. This stuff is actually not that hard. And like part of the reason it's even possible for all these companies to have their own labs now is because the actual post-training stack has matured. Sure. So it used to be that only OpenAI and Anthropic had the infrastructure in-house to be able to do things like post-training reinforcement learning especially. But now you have companies like Fireworks that gives you the post-training infrastructure. You have LangChain that gives you the evals. You have Trajectory that helps with the continual learning. You have, you have Merkur that helps you with the, the Data Factory stuff. And so like all these, all these components now exist. And so if you as a generally smart person, um, see the, see the menu of opportunities, you can actually cobble together your own research stack in a way that wasn't possible a couple years ago. And so like to give you a sense, very, very small teams can get very far. The Harvey team has put out, I think, pretty extraordinary research there. They just put out an entire RL environment last week. Their benchmark is state of the art for legal, and their entire research team is 7 people. So you can get very, very far. We're definitely not— you know, you're not competing with Meta or OpenAI for size of talent budget.

What about one click down? I don't want to invest in building the team, owning the stack entirely. There are NeoLabs that will show up and fine-tune a model for me.

Yeah.

Is that the domain of growth-stage startups, or is that product going to be more consumed by enterprises that maybe don't have the DNA to just move a bunch of amazing engineers over to do a post-training job? training stack and spin up and roll their own. But the NeoLab offers— I'm thinking of like a Thinking Machines Tinker, like what happened with Ray Dalio's fund and how they were able to fine-tune a model, get really good results. That feels like its own new market of like post-training as a service, fine-tuning as a service.

Yeah.

But how does that piece in? Is there a world where you don't necessarily necessarily have a relationship with Merck Core, but your third party does.

Yeah. Look, this is a huge ecosystem and a huge market because I think everyone sees the opportunity of, you know, you obviously like the closed model inference market will always be gigantic. Yeah. But I think the open model inference market is becoming very large. And for companies to actually be able to make use of open weight models, there is a maturation process, there is a handholding process. There is an entire, like, you know, come work with us, we will forward deploy people onto your staff to help you go on that journey. And so there's lots of options. Fireworks has a fantastic team for this. Mercore has a fantastic team for this. It kind of depends on the specific problem you have.

Okay.

So the specific problem you have is, hey, I really want to do reinforcement learning on my online data. Fireworks is fantastic for this. If you're like, hey, I can't train on my customer data, I need to get my model really, really good for this specific domain. Can we create a bunch of synthetic data around this opportunity? Merkur is fantastic for it. So it kind of depends on the use case. Generally, I think that it's like really important. It's an and like companies need to have extremely smart people in charge of this in-house. This can't be something you outsource like your lunch menu outsourcing, right? This is so core. And so you need to have smart people in charge deciding on your strategy, deciding on your technical roadmap and then making judgment calls of which parts of the stack you want to outsource to others, which parts of the stack you want to lean on others for. Harvey's actually done a really good job of this. They lean on pretty much all of the 5 or 6 NeoLabs I just mentioned as their partners. But you need to intentionally own it. And over time, just like we saw Cursor go on this journey, I think a lot of application companies will go on the same journey that Cursor did. Over time, you become more and more incompetent. more competent in-house and you bring more of that expertise in-house.

Sure, sure.

How are you processing the current price war? You have sort of the lagging labs starting to compete more on price. You have leading labs trying to make sure that they have competitive models at every part of the curve. But yeah, anyways, what's your take and And where does this go?

Look, I think Jevons paradox, not to be an annoying VC, but Jevons paradox is a freaking wonderful thing. Because what's happening is like, I see the data for all this stuff, right? From— oh, there we go. Bam. Look, our companies, we see the margins going, their gross margins going up. Because at the same time as like AI usage is going way up, but their gross margins are also going up, because they are the beneficiaries of intelligence getting cheaper and cheaper to either. On the other hand, I see this from Fireworks. I see this from the model companies we're in business with. Their cohorts are getting better and better and better. So it's not like they're facing price competition and their businesses are going into the gutter. They have phenomenal businesses where because they're able to provide intelligence at increasingly cheap prices, their businesses actually get better and better. So I actually think this is an everybody wins situation.

Yeah, part of the, part of the challenge with, I feel like, X trying to process the price wars and how open source is fitting into all of this is that when you have Anthropic and OpenAI still as private companies, people just don't have the visibility and they don't realize that even with great open source models and even pricing price cuts across different providers, you're still seeing that just massively accelerating revenue. And it's not like— it's not like the biggest customers aren't aware that open source exists and it's good, and they are using it in a bunch of different ways. So, I think it'll be very—

It's an and.

Yeah, yeah. It's an and. Yeah. And I think it'll be very helpful when more of these players are public just so that everybody has the same access to information.

Yeah.

Totally agree.

Thank you so much for coming on the show.

Let's do it again soon.

Great to see you guys.

Do it again soon. Great to see you.

We'll talk to you soon.

Goodbye.

Let me tell you about Public.com. Investing for those who take it seriously. They got stocks, options, bonds, crypto, treasuries, and more with great customer service. You ready for this next one, Jordi? You're going to love this company. They put a brain in a vat, basically.

Really?

Yeah. We have Sean Cole from Prisma. He's the founder. This is his first time on the show. Sean, how are you doing?

Hi, guys. Thanks for having me.

Welcome to the show. Is brain in the vat appropriate or is that derogatory? Should I stay away from characterizing your company that way? I think it's pretty good. I think it's pretty good. Okay. Take us through it. Introduce the company. Introduce yourself.

So I'm Sean. I'm the founder CEO of Prisma, and we are training brain cells for compute. So previously, I think you guys might have seen, you know, we made brain cells play Doom. Yeah. And we just launched, like literally just launched, and we got these cells to do token prediction. So kind of the basis for language modeling.

That's amazing.

OK, so how many cells do you need? Because many people have said that I have seemingly only a few brain cells. And so how many brain cells do you actually need in order to do next token prediction?

I can predict tokens all day with just a few brain cells. It's no problem. So it seems like an easy job for you.

Not that many. So we're renting some brain cells out. We're using about 200,000 brain cells to do token prediction. It's good enough.

Are these literally like donor brain cells from cadavers or are you growing them yourself?

Your brain cells.

Are these stem cells? Like, where are they coming from? Walk me through the full process. What's your supply chain?

I think you got it exactly. So we're using sort of total stem cells and we're taking these stem cells, differentiating them into different types of human neurons and putting those in a dish that we can stimulate and get responses from basically.

Okay. And then you said you're able to do next token prediction. I imagine that you're not anywhere near the frontier, but how are you actually benchmarking, like, what is capable? Because this is probably all predicated on a very extreme exponential kicking in at some point, but where actually are we in terms of progress?

Yeah, I think So I'm going to give a pretty funny example, which is it's currently at this current stage, the token prediction is basically, is this a hot dog or is this not a hot dog type of token prediction? It's pretty basic.

Well, can you say, say you're alive, and then it says, I'm alive?

Yeah, we could get it to do that. You could. Okay.

I think fundamentally what we've done is we've proved that these types of sequential context-based architectures with electrical stimulation are a viable architecture on these biological substrates. We had a specific example where it was a nonlinear task. So let's say that to refer to context early in the sentence, and if we used a linear decoder, so traditional silicon, it could only maximally get 75% mathematically. But we got above that. So we got 78%. We beat silicon on this very constrained task.

Sure.

Because it was able to model these nonlinear dynamics in context.

How long do the cells actually last before you need to replenish them?

So I think currently they last 6 months. But of course, I think human brain cells last far longer, like 100 years, 80 years. So I think the goal obviously is to extend them for as long as possible.

Yeah. You were kind of getting at this, but But not fully. So why do this? I have some ideas of why you might, but it seems like kind of a hassle. So you've got to have a good reason. Is it like—

What do you have against silicon, OK?

I'm assuming there's like— is it energy efficiency?

Yeah, yeah, yeah. Play it out. If this goes the way you want it to go, is there actually a benefit over just a huge data center or something in space with a solar panel on it? It feels like the current chip stack, the AI stack, is pretty efficient. We've squeezed out a lot of the inefficiencies of being a human, potentially.

Yeah, I think that's where it's really interesting because, you know, regardless of how efficient we make silicon, like silicon we have right now is supremely efficient, but we still haven't solved the efficiency aspect of it in terms of power efficiency. I think human brains are extremely power efficient in comparison to silicon. I think there are things that we can harness there on top of other stuff like sample efficiency. Human brains learn very quickly compared to silicon, much fewer examples. And continual learning is free on biological substrates because they keep learning over time.

Yeah.

But I think continual learning is something that has to be expanded on in the AI space. We're still figuring out what's the optimal approach to use. But yeah, massive, massive energy efficiency.

How do you actually think about that energy efficiency though? Because I've seen— I mean, there was that news of like $5,000 worth of SOL tokens solved a bunch of math problems. When I think about like not even the salary of a mathematician, but I just think about the food that goes into generating the calories that generates the energy that generates the theorems from a mathematician, you're way above $5K.

Yeah.

So it feels like the models are actually pretty Pretty efficient, but what am I getting wrong?

I think if you think about the cells as growth, as humans, we are expensive. We have to feed ourselves and all that. I think with Doom previously, we showed that it's possible for us to inject information, essentially force these cells to learn much faster than a human would learn. So you don't have to learn the basics of language, ABCs. You can tell it to just predict whether this is a hot dog, this is not a hot dog, something like that. far quicker so we can skip that kind of like prior human learning building phase that would be very expensive normally. So that's kind of the stuff that we are approaching it with.

Yeah. Is it possible that golden retriever brain cells could be better at long-running tasks like chasing a ball?

Well, I think that human brain cells for now empirically, they are the best.

However, Shots fired. Well, you know, we've tested it, but yeah. You put the golden retriever in the vat?

We tested rat neurons, right? So there are rat neurons and then there are human brain cells.

Whoa, golden retriever, rat. These are not comparable animals. Let's give the golden retriever some credit. What is the business going to look like over the next decade? I imagine at the end of all of this, there's some sort of business model where you're selling intelligence, but in the short term, there's some venture capital that comes in through Y Combinator. Congratulations, by the way.

Thank you.

But what's the middle step? Is it partnering with biotech companies? Is it NSF grants or government funding or something like that, or partnering with a university? How do you you keep the lights on and keep the flywheel going? I imagine you can raise more money off of scientific breakthroughs, but I imagine that there'll also be an economic, a commercial flywheel here even before you're selling the work.

Yeah, I think something that we're really looking at right now, which is great because we've just started, is with the exponential increase in AI capabilities, we're going to start building our lab from scratch to be automated. We want to automate the stem cell research to differentiate them into neurons, the optimal compositions, the optimal kind of like spacing on the electrodes, let's say. So I think that the automation aspect of our lab can easily be branched out into different things like drug testing. And I think that could be significant revenue in the short term to push this all the way to make sure that we get brain cells to be the fundamental substrate for compute.

Very cool. Well, congratulations. What a fascinating company.

Fascinating company.

Thanks for taking the time and have a great rest of your day.

We got to introduce Sean to the guy that we had on yesterday. What was—

Put them together, you got a whole human. He's getting tissues. He's doing drug testing.

Vivodyne.

Vivodyne.

They are doing some interesting stuff.

Well, have a great rest of your day.

Great to meet you, Sean.

Thank you, guys. Cool. Bye.

Thanks for having me.

See you soon.

Cheers.

Good one.

Uh, do you mind shaving your head for me? Uh, don't tempt me. Do you mind just letting me take a saw to the top of your head? You think I'm gonna put your brain in a vat?

You think I'm gonna put your brain in a vat?

You wanna come up to the roof with me?

I don't wanna go on the roof, John.

You think I'm going to throw you off the roof? I like that it's green now. The green's fun.

We should get buzz cuts sometime. I think next summer, summer buzz for both of us.

Well, it's got to be a bet. It's got to be, oh, you know, SaaSpocalypse is over or something. Some prediction that then we can take a victory lap on or shave our head in sadness. Marques Brownlee might have to shave his head, right? He made a bet, or he said, if the CyberCab ships to Elon's schedule, I'll shave my head, something like that. And people were going back and forth. And the Tesla fanboys were saying, he's going to have to shave his head. And he's like, not yet. Because, of course, all these projects take a long time.

I don't even need much of a reason to shave my head. I actually have gotten a bunch of summer buzz cuts over the years.

So you'll be like, if the stock market moves by more than 1%, If we don't get through the end of the year, I'll shave my head.

Silver Lake is in talks to buy Workday, sources say.

That's a big deal, right? Isn't Workday huge?

Workday is— let's see, I'm sure it's popped.

$50 billion company.

Popped 17%.

Wow. The take profit.

And so now a $50 billion company. It was a $43 billion company, at least when this article was written. We'll see. I'm curious what— that is a bold, bold bet. But I can imagine there's a bunch of AI transformation that they'd feel like they'd be more easily able to do as a private company.

Are you a standard crying face emoji guy, a tilted crying face emoji guy, or a tear streaming down your face emoji guy?

I'm normally— okay, I want to actually pull this up so I can see more closely.

Which one are you? Joe Weisenthal has recently transitioned to a tilted crying face emoji.

I don't dabble in the tilted. I do the tears and the straight on.

Do you do the streaming down the face?

Yeah, yeah, yeah.

You need to mix that one in. It's the most popular emoji of 2025.

Yeah, I went through maybe a decade where I wouldn't, I wouldn't touch any of the crying.

Oh, any of the crying ones. You do a smiley?

But I've been, I've been laughing a lot. Okay. The last couple years, mainly because we've been doing this show. That's great. You gotta throw a laughing emoji.

I like that in iMessage you can do the haha, but then you can also throw the crying emoji. But I gotta experiment with The tears streaming. Do you ever go with the cat versions? No, I never LARP as the cat.

Never go, never go cat.

But expect a cat emoji from me soon, Tyler, in our group message, in our group chat, because it might be underrated. There might be some alpha there. I don't know. Anyway, there was clearly alpha at this auction. A JPMorgan hand-signed mortgage bond from 1886 sold at auction. For just $847, someone got a steal, says Dylan Abruscato. This needs to go in the Museum of Business. There's a bunch of these good ones. I was looking at the—

Yeah. How did— why did Dylan find this after it had already— the auction had already closed?

I don't know. Yeah.

Get it together. Get it together, Dylan.

There's another good one. Can I— how do I drop this in the timeline? Microsoft, in 1995, 1996, published a wine guide. This is from the corporation, the hyperscaler, the Mag 7 company, Microsoft. They released a wine guide, the essential— click to the next image, and then the next one. There we go. OK. The wine guide came on CD. The essential reference from vine to glass. If you wanted to know about wine, this is where you had to go. You had to get the official wine guide from Microsoft, the software company. Fascinating. Know your audience moment. A lot of Microsoft fans, customers, 1996. If you're implementing Microsoft in 1996, probably enjoy a glass of wine every once in a while.

So why not? That's good. Why not? Well, John, I'm going to read a Buco Capital bloke. post that I think applies to this exact moment right now. He says, I think we're very close to the point where caring about AI or talking about it a lot is a bit embarrassing. Move on already. Who cares?

Move on already. I mean, there is a point where, like, we don't talk about the internet anymore. We talk about what's happening on the internet. We talk about particular internet companies. This stuff does diffuse. If it diffuses fully, You stop talking about the underlying technology. But there's a horse race on, Buco. There's a lot of money on the line. The entire global economy, potentially. But that's right. He's just horsing around.

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