TBPN - Anthropic Hits $380B Valuation, Become Unsloppable, WSJ Mansion Section | Martin Shkreli, Connor Hayes, Alex Bouzari, Brett Adcock

Episode Date: February 13, 2026

Sign up for TBPN’s daily newsletter at TBPN.com(00:51) - Anthropic Hits $380B Valuation (06:08) - Become Unsloppable (23:27) - 𝕏 Timeline Reactions (45:08) - WSJ Mansion Section (58:20) - Martin Shkreli, an American investor and former pharmaceutical executive, gained notoriety for significantly increasing the price of the drug Daraprim and was later convicted of securities fraud. In the conversation, Shkreli discusses his development of a new product that utilizes his network and AI to estimate venture capital positions in various funding rounds, highlighting significant gains by investors in companies like Anthropic and OpenAI. He also touches on the challenges of accessing accurate investment data and the potential of AI in transforming industries, emphasizing the importance of product development and sales over engineering in business success. (01:34:32) - Connor Hayes, a product leader at Meta, discusses the development and growth of Threads, emphasizing its unique content format and the importance of fostering niche communities. He highlights the "Dear Algo" feature, allowing users to customize their feeds by requesting specific content, and shares insights on integrating AI to assist creators in streamlining content production. Hayes also touches on the challenges of creator monetization, advocating for directing traffic to sustainable revenue sources rather than relying solely on platform payouts. (02:03:30) - Alex Bouzari, CEO and Co-Founder of DDN, discusses his company's role in solving data challenges for AI implementations across enterprises and nations, highlighting collaborations with Nvidia and Elon Musk's ventures. He shares his journey from France to the U.S., emphasizing DDN's evolution from high-performance computing to AI, and underscores the importance of efficient infrastructure in accelerating AI adoption. Bouzari also addresses the competitive landscape, noting the rapid advancements in data center development in China and the Middle East, and stresses the need for the U.S. to enhance its efficiency to remain competitive. (02:29:01) - Brett Adcock, founder and CEO of Figure AI, discusses the company's advancements in humanoid robotics, highlighting the unveiling of their third-generation robot, Figure 03, and the development of a new, highly dexterous hand designed to achieve human-level manipulation capabilities. He emphasizes the importance of creating robots with human-like form and dexterity to seamlessly integrate into environments built for humans, enabling tasks such as folding laundry and handling dishes. Adcock also outlines Figure's strategy to deploy humanoid robots in industrial settings rapidly, with plans to introduce them into homes once they can perform tasks autonomously and reliably over extended periods. (02:55:28) - 𝕏 Timeline Reactions TBPN.com is made possible by:Ramp - https://Ramp.comAppLovin - https://axon.aiCisco - https://www.cisco.comCognition - https://cognition.aiConsole - https://console.comCrowdStrike - https://crowdstrike.comElevenLabs - https://elevenlabs.ioFigma - https://figma.comFin - https://fin.aiGemini - https://gemini.google.comGraphite - https://graphite.comGusto - https://gusto.com/tbpnKalshi - https://kalshi.comLabelbox - https://labelbox.comLambda - https://lambda.aiLinear - https://linear.appMongoDB - https://mongodb.comNYSE - https://nyse.comOkta - https://www.okta.comPhantom - https://phantom.com/cashPlaid - https://plaid.comPublic - https://public.comRailway - https://railway.comRestream - https://restream.ioSentry - https://sentry.ioShopify - https://shopify.com/tbpnTurbopuffer - https://turbopuffer.comVanta - https://vanta.comVibe - https://vibe.coFollow TBPN: https://TBPN.comhttps://x.com/tbpnhttps://open.spotify.com/show/2L6WMqY3GUPCGBD0dX6p00?si=674252d53acf4231https://podcasts.apple.com/us/podcast/technology-brothers/id1772360235https://www.youtube.com/@TBPNLive

You're watching TVPN. Today is Friday. It's the day before Valentine's Day, 2026. That's right. We're live from the TBPN Ultradome, the Temple of Technology. We should have mentioned Valentine's Day. Yeah, earlier. Two months ago, and then again, one month ago.

I think most of the audience is prepped for sure. But we have some ideas, some recommendations. If you're looking for advice, this Valentine's Day, we of course live from the TBPN Ultradome, the Temple of Technology, the Fortress of Finance, the Capital of Capital. and here's an idea for Valentine's Day. Ramp.com, this Valentine's Day,

show her you care about your future together by putting all of your couples spending on ramp because nothing says I will provide for our family like pulling out a ramp card. You know you handle business. That's right. Anyway. Handling business.

The big news, Anthropic has raised $30 billion at $380 billion post-money valuation. We've all seen the revenue chart. 10x growth, four years in a row, 100 million, a billion, now 14 billion. Will they do 100? That's the question. Will they be at a hundred billion dollar revenue run rate by the end of the year? They're growing on track to hit that, which is crazy and completely unprecedented.

But again, they're going after all of SaaS. They're going after all of software. They're going after all of labor, all of white collar work. All in your job specifically. Yeah. It's not looking good for you. No, we're joking. Never doom.

Never doom. There's plenty of opportunity. There are plenty of good potential outcomes. Dario has been on Dwar Kesheh Patel today, and he did something else with Ross Dauphit. And so there's a number of places where you can go to hear his latest takes on the good ending and what he's guiding towards. It would be interesting to follow. The question is, you know, what happens to the company? that are currently under pressure with the anthropic narrative.

They have to answer this question of, you know, is Anthropic just going to steamroll you? What is your real source of strength? Yeah, not just anthropic, but the labs. Every YC company that is building an AI native, you know, any company that is, you know, slapping AI native on their website. Yeah.

Everyone's going after the opportunity. So we coined a phrase. We decided to coin. something. It's time to coin out. And before we tell you the coinage, let me tell you about Cisco this Valentine's Day. Give her the gift of enterprise grade networking this Valentine's Day. So your home Wi-Fi never drops during movie night because nothing kills the mood like buffering during a rom-com. Get on Cisco. Go ahead over to Cisco.com. So yeah, we were, we decided so how do you, what is a phrase that you can

generally apply to businesses that can survive and then hopefully thrive in during this moment in time. An error in intelligence is too cheap to meter. Yeah. So the the question, you know, earning cycle last couple weeks, every CEO has gone on. If basically, like if you had to answer the question, like what talk about the threat of AI, if you just had to answer the question. Yeah.

Like basically the companies that were just the entire earnings call was just about generally about AI. You know, if you're like a core weave or something like that, that's a little bit more straightforward. But if you have to answer the question, do you have a durable moat right now with AI progress? Your stock is probably going to sell off. But, you know, either way, kind of however you answer it. But there's a second question, which is like, are you a true beneficiary? So, like, do you have a durable moat? And then are you a true beneficiary?

So we decided to coin the phrase unslappable. Unslappable. So these are companies that we'll get into that have some type of moat in an era where it feels like more code could be written in the next 12 months than in all of human history. Yeah. I was kind of running the numbers. It seems possible. The moat is specifically not okay. You're a company that has just spent 10 years writing a bunch of lines of code and it would take a story.

startup a lot of time and money, and they would have to hire a lot of engineers and write a lot of code to create a copy of what you have. It's like, no. So like to rebuild Salesforce as a platform, you would have to spend billions of, historically, you would have had to spend billions of dollars hiring thousands of software engineers to, you know, piece by piece, build out all of the functionality at Salesforce. Of course, you could build vertical solutions and get some amount of traction, but in general, the idea was like there was some, effectively just an engineering mode, and that there was a lot of code that you'd have to write to effectively compete. So I talked about in the newsletter today.

Set the table first. What's going on in the market? Yeah, so software has undergone the largest non-recessionary 12-month drawdown in over 30 years. That's minus 34 percent, wiping out $2 trillion of market cap from the peak. This is J.P. Morgan as of a couple days ago. AI threat sparks historic software stock crash. Goldman Sachs warns of newspaper-like decline. I love the newspaper. What's wrong with newspapers? Still got it. Still got it. And then as of yesterday, over the prior eight trading sessions,

more than 20% of the S&P 500 had a drawdown of 7% or more in a single session, according to the compound. That's a lot. Quickly, before we continue, let me tell you about the New York Stock Exchange. This Valentine's Day, I recommend flying to Manhattan, take her to the floor of the New York Stock Exchange, IPO your company, and ring the opening bell together. Great. Your love just went public. Good one, John.

So, yeah. Yeah. So, continuing. So I wrote, everything was great when we were disrupting manual workflows. But as we enter the software singularity, we are having the uncomfortable experience of disrupting ourselves. Assume the marginal cost of software development goes to zero. If you're a software company where your moat was that a competitor would have to spend a billion dollars to hire a bunch of software engineers to write millions of lines of code to create a product, and you have no other modes, it's going to be rough. Thankfully, there are moats that are unaffected by coding agents and effectively zero-cost software development.

Peter Thiel, PT outlined four key sources of monopoly power in zero-to-one back in 2014. These are proprietary technology, network effects, economies of scale, and brand, or you can think of as trust. Most of these still hold, but proprietary technology by itself is no longer sufficient as a moat. In some cases, if you have a patent to a GLP1 drug, that is a proprietary technology that will give you pricing power probably for as long as the patent holds. And there are patents on certain pieces of technology that even if they can be cloned or re-derived from first principles with your million geniuses in the data center, the first person to patent it gets to reap that value. And that's just the way our... And the issue with software, how many...

A bunch of designer friends of mine have like a design patent on a specific kind of... Can they enforce it? Workflow. And it's cool to say that you have a patent, but it's not... Yeah, proprietary technology can just be, okay, we have a big software system,

but oftentimes it's more like we have proprietary, like something that's regulated, something that's a cornered resource, something that's that's scarce and will remain scarce. But yes, if your proprietary technology is just you're the only person with this particular Python script, that's probably going away. But network effects aren't. And some of the economies of scale, some of the liquidity on these platforms is going to be durable. You can vibe code a, I was talking to Dara Koshershari at Uber

about this. You can vibe code a pickup app that looks like Uber has a map. lets you click the button, accepts payment, but if there's no one on the other side of that network to actually come and pick you up, your Uber clone is dead in the water. Now, if a customer, if somebody does pick it up and the customer has a terrible experience, do you have the resources to actually make it right?

Yeah, but Uber works because they spend a bunch of money getting to scale, and cloning that scale is difficult. Now, the whole self-driving car thing is separate because you bring your clankable. Yeah, we're working on that one. That'll happen. But there are a set of businesses that will have to contend with the clankerification of the economy. But that's second order.

So becoming unslappable means two things. First, your business actually has to drive its economic power from a moat that is unslawable. And second, you need to clearly communicate that to shareholders right now if the market thinks you're just a bunch of lines of code. You're cooked. Tech companies we think of as unslappable. You have hardware, Nvidia, AMD. Intel, Cisco, Broadcom, SK-Hinex, Western Digital, data centers, so neoclods, things like CoreWeave, Lambda,

social networks, YouTube, Instagram, X, LinkedIn, even thinking Roblox, right? They can be not just, you know, they have the network, and they can be a beneficiary of AI, because if it's easier to make games, a lot more people will make games, maybe you'll get more usage. Marketplaces, Airbnb, Uber DoorDash, IP holders,

Disney, Netflix, Warner Brothers. I think if you have a lot of IP right now and the cost to produce, great content drops dramatically, you're going to benefit from that. And then platforms, things like YouTube and Spotify as well. I said it's been an incredibly rough couple of weeks for public market CEOs.

Really disheartening on the show, CEOs has been putting up some great quarters, and then, you know, they're trading down between 7% and 20%. There are two main question everyone wants to know, even if they already sold your stock to buy Adam. One, do you have a durable moat in the software singularity? Two, are you a true beneficiary of AI? Many CEOs are still struggling to answer number one

because it doesn't really matter what you say, just having to answer the question equals a sell-off. And two, this one can really only be answered in the numbers. You aren't an immediate AI beneficiary if revenue is not accelerating. Also, separately, there are a bunch of crazy things happening in the broader economy right now. I think Besson went on CNBC at 4 a.m. It brought out the big dog.

I haven't been able to catch it yet. It was 7 a.m. Eastern? Yeah, 4 a.m. Pacific. Very, very early for us. It's possible to be unslappable, but not an obvious beneficiary, but you'll still likely sell off as a market digests and interrogates the actual real-world impacts of coding agents. Some industries will be more resistant to change.

Other industries will be revealed to have a secret source of market power that was underappreciated in the before times. What I was thinking was Nielsen, this company was, you know, in one way, Nielsen ratings, Nielsen data, a lot of consumer package goods companies use this. I'm sure Matina is looking at how is this Yerba Mata selling in this store. And you go to Nielsen, you pay them, and they give you data. And it just feels like an interface to sales data, but they have this whole network and you just have to pay for it. And it's not really something that you can just spin up.

I don't know. What do you think? I mean, isn't that kind of like what simile is? doing. We had them on yesterday. They're like trying maybe you can kind of do like polls or something about how market will. That's more for yeah it's more for yeah prediction. The bigger one is like is like like I would want to know simile would actually want that data to update their models. Yeah like you want to know okay uh what stores are actually turning my product which store should I be doing promos in which stores should I be doubling down on running

advertising in or what chains are working should I push more into or or even just hey I need to go to one chain and say I'm working like targets working so Walmart should carry me they're not really going to accept just a simulation of that data they're going to want to know that an independent rating agency sort of rated gold rock just bought unslawable.com okay great quickly before we move on let me tell you about app lovin this valentine's day use apploven's axon.a i.i to serve her hyper-targeted ads for exactly the jewelry she wants. That way, she'll be extra excited when she unwraps presence on the big day. Great call.

Capping off the newsletter, I said a lot of the software market feels like the office equipment and imaging sector in the 90s. So companies like Sharp, Canon, Panasonic, revenue was still up into the right, but widespread adoption of the Internet emails and PDFs was on the horizon. Even today, you'll still find a fax machine in every doctor's office, and many of the giants of that era are still around. But if you stayed in those names, you would have missed out on generational gains by simply being long PDF. Got to go long PDF. So, yeah, if you look at these companies, you know, Panasonic's still massive company, and they've obviously adapted over time.

But, you know, it's a shift from growth stock to value stock. investors are less willing to pay for earnings that might come 10 years out because they're worried about those or 20 years out. Instead, they're asking, what will my return on invested capital be this year? What will the dividend be this year? How much cash will you give me back if I invest for a one-year time horizon or shorter or longer? Let me tell you about turbopuffer. This holiday, Valentine's Day, here's an idea, turbo puffer. Store vector embeddings of every romantic moment you've shared in TurboPuffer, so you can do semantic search for that time in Paris and actually find it.

Ferebofer is serverless vector in full-text search. It's built from first principles and object storage. It's fast, 10x cheaper, and it's extremely scalable. So no matter how many memories you're cramming in Turbo Puffer, you're good to go. You're good to go this Valentine's Day. Just do it. Anyway, it will be interesting. I think that there will be a reckoning around who is able to reveal a true moat and help people,

help the market understand what their source of strength is, whether it's liquidity on their platform, the network effect, the IP, if they have a real IP that's defensible. But just having a big bag of code right now is a little bit of a weight since you're seeing so many companies that are saying, well, I haven't, our software engineers aren't even writing the code anymore. Yes, we're advancing our products. But so many companies are going all in. It's also, it's pretty wild how long it's taken for the public markets to react to this one-shodding concept or the zero marginal cost code.

Yeah. You know, coding concept where we were having these same conversations in Q1 of last year being like, what are the implications when you can just put in the prompt box, build me, XYZ tool, right? And it took a while for the models to make progress, but even a year ago, it was pretty obvious that you would get to some point where you could one shot a big platform.

Of course, reliability is still a concern, right? Security is still a concern. There's a lot of businesses where the potential risks of using like a vibe-coded product far outweigh the cost of just paying for the product and having something that's reliable. reliable, trustworthy battle tested. Yep.

And but, yeah, I mean, there's still a ton of questions about how quickly disruption happens, how quickly market structures change it, change. Some things go from monopolies to oligopolis. Some oligopolis are going to go to perfectly competitive. It's certainly a bull market for YC companies who can vibe code something that's as good as a public company SaaS product and then go to those customers and say, Maybe not as good, but it's feature complete. As feature complete, or at least can compete a little bit faster and say, hey, I'll come in with an offer that's 10x cheaper and move you over.

And that's just going to create some pricing pressure. The question is, what's the rate limiting factor? Is diffusion a real factor? Is adoption a real factor? Do you need for deployed engineers to go help companies transform with agentic coding? or do you, or can you, or will this happen inside companies and they'll be building their own platforms? Or will they want just a cheaper product from a new third party that has a different business model that's maybe more consumption based and something where if it goes down on a Saturday, they don't need to even fire off a prompt, how long until these vibe coded systems are like self-healing in the way an enterprise platform is and has like a proper SLA. What do you think, Tyler?

I just have a question. I'm curious, what do you guys think about this? So it's like, if the market is just catching up now to, like, coding models being very good and vibe coding all this stuff, and they're basically like a year late, in one year, what do you think, like, is going to be the thing that they're like, do you think they'll still be late? Is it going to be like, okay, actual, like, white-collar work is you actually can't automate a lot of this stuff? And only in any year that they're actually going to, like, catch up to this. Yeah, that's a good question. The next, next thing.

Tyler, if I knew the answer, we'd be on Wall Street. I think we'll be talking about it over the next couple months. We'll need to see glimmers of demos. Yeah, the one thing is, like, coding never felt. Here's the thing. So in coding, it's a white-collar job, but has always felt a lot less fake than most white-collar jobs. Like, there's a lot of jobs, like email jobs.

laptops jobs, where there's like six people on a call for an hour and like one person is doing, like really doing the work and the rest of them are just saying like nothing for my end thanks, right? And that's like their entire day. Whereas coding, like the best engineers were actually just like grinding all day long, putting in the hours just shipping, right? And so I think what's interesting, like as some of these like, more broad knowledge work tasks, get more easy to automate, do those people just, like, they're still going to be doing meetings? Like, at some point, these companies, I mean, to date, the AI, the AI job loss has just been primarily from companies, I would say, still processing the Twitter acquisition and saying, hey, we just, we need 50% fewer people here. Yeah, this, this sell-off is is much more related to business model competition, pricing pressure than automation and job loss, in my opinion. It's much more that there will just be more competition in enterprise software markets.

And so you assume that margins will fall. That's my read on this. I do have another example, but I will tell you about gusto first. The unified platform for payroll benefits and HR built to evolve with modern small. and medium-sized businesses. So my answer is the uncankerable company. So right now there are industries think about mining. Like I have a piece of land. There is gold in the dirt. There's another company that comes and their specialization is finding where the gold deposits are on my land. There's a third company that shows up with tractors.

and people that dig the gold out, then there's a fourth company that takes the raw or and refines it into gold. There's a fifth company that is a platform for selling that gold onto the market, right? So you have five different layers of the supply chain to get the gold into the market from the ground. Let's just use that.

It could be oil, it could be any mineral. Does robotic labor too cheap to meter change the value of the land? Probably not. but if you have a robotic digging machine that can show up and dig the, dig the ore out of the ground, dig the gold out of the ground at a lower cost. Well, the company that's been set up where their moat was they employed all the best miners and they had systems to know who's good, train them, make sure that they're doing it safely, train them on the tools, make sure that they have the right,

Equipment to dig the ore reliably working shifts, all of that becomes attackable if you're like, well, all I have to do to start a company that competes in the gold mining business is place an order with a bunch of humanoid robots and go to the guy who has the land and say, I want to dig the land and I will give you a little bit more than what the other team that's using a bunch of human labor and a bunch of unautomated systems. So I would say that that's probably the next thing that the market would be processing. And the ride-hailing platforms dealing with the advent of this self-driving car is probably one of these like clankerification narratives. But that will come to a whole host of industries. The question is just on a five-year timeline, on a 10-year timeline, when will it be real? And then when will the market price it accordingly? because a lot of the pressure that you're seeing in the market is not showing up in the financials. Like the companies are still growing, they're still producing cash.

The business hasn't changed, but the perception of the future of the business has changed. And the perception of the future of the market structure has changed. And so that might be the next thing if we're just to play out AI broadly. Anyway, phantom cash, fund your wallet without exchanges or middlemen and spend with the phantom card. Let's also pull up the linear lineup and take you through who's coming on on the show today. Linear is the system for modern software development. 70% of enterprise works based on linear are using agents. It's Friday we have a lighter show, but we got some great guests.

We got Martin Screlli coming on to talk about, take a little victory lap about the quantum computing thing. Connor Hayes, the head of the Reds. We hung out with him at MetaConnect. We're very excited to talk to him about the progress on that platform. Then Alex is coming on from DDN and Brett Adcock from figures. coming on to talk about humanoid robots. They launched a new one today. Finally, on the show, it's been an interesting one.

Clavicular has also been in the news. Oh, yes, what happened? Let's see here. Streamer Braden Peters to host boxing match billed as test of physical dominance. The Valentine's Day live stream pits two figures from the male self-improvement internet against each other. Braden Peters, a live streamer known as

clavicular announced Thursday that he will host a boxing match on his kick.com channel this Saturday evening February 14th at 7 p.m. Eastern directly opposite Valentine's Day festivities nationwide. The bout will feature two personalities from the online male aesthetics community, a figure known as ASU frat leader, an Arizona State University fraternity member who gained attention for his broad-shouldered build, and a creator who goes by Androgenic, a fitness influencer focused on hormone optimization and physical appearance, promotional materials bill the event as a championship of skeletal frame superiority, essentially a contest to determine which man is more physically imposing. The announcement posted to X by the KIC-affiliated

account KikChamp has drawn thousands of engagements and spawned a wave of commentary from users who noted the scheduling choice with amusement, characterizing the event as a deliberate alternative to the holiday. The matchup represents the latest example of niche internet subcultures, in this case communities organized around male physical self-improvement and body image optimization, crossing over into live entertainment. Mr. Peters, who has built his following around content related to physique and social dynamics, appears to be positioning himself as a promoter within the space. No official venue has been announced. The event is expected to stream exclusively on kick.com. So we'll be interested to see how how the news kind of reacts to the event over the

weekend. Certainly, this story has gone mainstream. You know, it's funny that, so if you haven't been following these, we've been taking these like viral kick clip posts and turning them into professionally written articles, just as a joke, but clavicular actually has a profile in the New York Times and it's written like that. And so I think I think our joke is like over because it's hit the mainstream. Joe Bernstein wrote something that sounds exactly like something that we were joking about. Braden Peters, known as clavicular, has emerged as a beacon for a group of narcissistic status-obsessed men. He wants to take his fixation with looks maxing mainstream.

It's a wild piece. Clavicular is a six-foot-two. He weighs 180 pounds and has a 31-inch waist. His bichromial whip, basically the span of the clavicle, from which the 20-year-old streamer gets his name, is 19.5 inches. He has a midface ratio, which is derived by dividing the distance from pupil to the mouth by the distance between the pupils of 1.07. His chin to filterum ratio is 2.6. According to clavicular, these calculations make him handsome. Just not as handsome as actor Matt Bomer. And then it goes on to explain the whole looks maxing phenomenon. And it was very funny watching this

happen because clavicular streams so much that he live streamed the interview with Joe Bernstein. But of course, normally when you do an interview with a mainstream media journalist who's writing a profile, it's like under embargo and you don't know it's coming until it drops. And you don't even really talk about it. And the chat is confused. This is a very popular trend on social media these days. And the New York Times is breaking it down. But anyway, there's plenty more there.

Let me tell you about public.com investing for those to take it seriously. Stocks, options, bonds, crypto, treasuries, and more with great customer service. Really, really wild time on the internet. Anyway, let's go back to the Anthropic round. Matt Slotnick says, LOL at the jockeying behind the scenes to land on this wording. Quote, we have raised $30 billion in Series G funding led by GIC and KOT. valuing Anthropic at $380 billion post money. The round was co-led by D.E. Shaw Ventures,

Dragonere, Founders Fund, Iconic and MGX. Lots of folks getting in. A huge part of this raise is Claude Cod Codes, says Boris Churny, who is the creator of Claude over at Anthropic. Weekly active users doubled since January. People who've never written a line of code are building with it,

humbled to work on this every day with our team. That is remarkable growth at this scale, doubling. Kenneth having some humble, humble pie, or maybe showing just how early it is. He says still less annual revenue than AirPods. AirPods last I checked were a $20 billion revenue business. 22 billion in 2024. That's a massive business. But Anthropical will be there in, what, a week or two?

They just broke top 20 in the app store, and now they're in the top 10. their number seven. The consumer app, Claude, bi-anthropic, is climbing in the charts. ChatGPT is number one for free apps. Google Gemini is number two. And free cash is number three. Threads is number four.

And I wonder how much this is driven by momentum still. But definitely driven by momentum, right? Because it's download. There's so many people that have never, there's so many people that have never tried Claude and hadn't heard of it until recently. And again, we know they're putting a lot of paid spend behind the anti-ads campaign.

Sure. So that's going to be a factor. Metacritic Capital was pretty funny. Back in March of 2024, he said, I continue to be puzzled by Anthropics' $18 billion valuation. And then followed up and said, market is so stupid sometimes. I have no words.

but of course the market was right on this one so far. You can just see they were. Well, are we sure that he was saying it was overvalued? You could have been saying it's undervalued. No, I think he was saying it undervalued. Yeah, yeah, yeah, yeah. I think that's why he's taking the victory lap is because he was, at the time, a year ago, he was like, why is the anthropic so, like, has such a low valuation based on the market.

It was almost two years ago. Oh, this is, yeah, this is almost two years ago. So, huh. I don't actually know. I don't know which way Metacritic was going. Cell phone? Ask Martin Scrowley, who's coming on the show? Oh, he responded.

He said, the puzzled meant I didn't understand why I was worth only $18 billion. Hmm. So. Always vague posts so that you can take either direction. You never paint yourself into a corner. Let me tell you about Gemini 3 Pro. Google's most intelligent model yet.

State of the art reasoning, next level vibe coding, and deep multimodal understanding. I'm glad this chart is now public because it is bananas. It is ridiculous. this. It should not exist, says Bruno F, the founder of Magna Digital. Five billion dollars in tokens managed. Interesting. Yeah, what? Crazy. Crazy. Just another pod guy says Salesforce invests in Anthropic colorized.

I think when Mark was on, he said they have about a point of anthropic going into this round. If I remember correctly, what is this? It's a horse giving money to a car. The car goes. goes and buys a rocket launcher. The car blows up the barn and the horse is sad. And that does be like an apt analogy. It's very funny. And Anthropic has been all over legacy media. First, let me tell you about CrowdStrike. Your business is AI. Their business is securing it. CrowdStrike secures AI and stops breaches. Also, fantastic Valentine's Day gift. from this extraordinary piece in the New Yorker last summer while Mark Zuckerberg was conducting hiring raids on other labs, Shalto Douglas, the Anthropic Engineer and TVPN guest, told me, this journalist, Gideon Lewis Krause, that a number of his colleagues, quote, could have taken a $50 million paycheck, but the vast majority of them hadn't even bothered to respond.

Well, they are early at a 350. $50 billion company and are clearly very optimistic, but it is funny to just money-mogged. Daniel says, so wait, Claude has seat-based pricing. Does this mean they're disrupting themselves, too? Of course, a lot of the concern has been around the seat-based model. Team plan. But it even feels like that is less of, that is less of a factor than just the overall threat of zero marginal cost software. Yeah, why does Claude have seat-based pricing? It's essentially a consumption-based product,

but psychologically, if I'm rolling out Claude to a company and I set up seats for a team, I know that there's individual rate limits, so no one individual is going to, like, blow me up, basically. That's the idea. But this goes into, like, some people are posting, like, if you're getting a job, you should ask what your turn. But in this case, it's not, this is Claude.

This is not the API. This is not Claude. But, you know, when you fire up Clod code, like, you can integrate your Claude account. And so, like, this essentially gives you credits to write code as well. And so the, the, yeah, there's this new meme of, like, if you're going into a tech company, like, ask what your token budget will be. Like, what's your inference budget? And so, I mean, these can clearly skyrocket pretty quickly. There's debates over, you know, oh, should I let my employees use, like, the fast mother?

or the regular mode or pro, like, is the work that they're doing really not valuable? If they're spending thousands a month, if they're spending tens of thousands a month, like at a certain point I need to make sure that they're not being wasteful. And so I think the seat-based plan still achieves a little bit of that, psychological security for managers. And then there's also an interesting, there's probably a pretty bimodal distribution in the value that or the actual cost associated with these. I would imagine that there's a portion of pro users that use 100% of their inference budget every month.

And they cap out and they're frustrated and they might have a second plan or they might go down to a free plan or limit their usage. And then there's a whole bunch of folks who just have a seat and never use it. Or they use basically like very little inference or they're just asking things that can be answered by a free tier, essentially. But they just like let it ride. Zach in the chat says we have 150 corporate cloud users purchased by seat, 50% max out in week one because of Excel token use. Yeah, there you go. Good data point. Let me tell you about Restream.

One live stream, 30 plus destinations. If you want to multistream, go to Restream.com. Dan Primak says, working on newsletter, it may be shorter to list of VC firms, not in the new Anthropic round. It's a party round. Josh says, got some logo sniping, it seems. Pay no attention to what price we paid. I swear it was early. Yeah, no, this is a very, very good point.

Like, if you are a venture capitalist and you say, I mean, it used to be, if you were an AI VC and you had AI as a thesis and you weren't in one of the labs, that was sort of a red flag for your brand. It would be rough to move forward, raise the next round, just from a logo perspective. And now with AI becoming such a mega trend, it's hard to imagine being a really enduring venture capital firm without one of these logos on the site, especially as like, this is sort of the train leaving the station since there's IPO rumors, and you probably want to grab at least one of the big labs logos. Many of the firms have sniped all three at this point.

Sequoia, Founders Fund, Co-2's in a bunch, Andresen's in multiple, I think. There's a variety of funds that have built stakes of various sizes in all the different labs. It seems like Josh Kushner is one of the few that has remained deeply loyal. Yeah. Yeah. There's, there's, there's, uh, and we do recognize we just had some technical difficulties, but it seems like we're back on. We are so back. Let me tell you about console. Console builds AI agents that automate 70% of IT, HR and finance support, giving employees instant resolution for access requests and password resets. Slow Ventures is taking the other side of the all-in on AI bet. They said, congrats to everyone who figured out that foundation models are

infrastructure plays, not startups. Now let's talk about what happens when the picks and shovels phase ends and we're back to building actual products. And Will Minitis says, nightmarish degrees of cope. Yeah, Sam, Sam was always super bearish on The labs from a business standpoint. Was that what it was? So they wouldn't have pricing power? Yeah, effectively. He said, you know, open source models are going to get really good.

Yeah. He was right. They have gotten really good. Yeah. But I think maybe missed that the labs would turn into product companies and stop just being, you know, the eyes. It is sort of interesting. Like if you wound back the clock and you were like, my job is just to invest well in tech,

startup booms from 2005 to 2025. There's one world where you're like, okay, I'm going to go hunt for the Airbnb, the stripe, the YC companies, the Coinbases, all the like application layer companies, the Instagrams, the Twitters, all these different companies. But there's a different side where you're like, I'm going to buy like Broadcom, Cisco, Nvidia, AMD, and still do really well and maybe even better, depending on when you got in, when you got out. But it's a, yeah, it's a very, like, just because it's an infrastructure play, even if that's

true, that doesn't mean that it's not a good investment for an investor. There is a little bit of, like, purist vibes from, like, a venture capitalist should, or certain funds have strategies, and so they say, you know, I'm going to sit out. Slow is a C Series A, but leans more early. And so by the time you're looking at some of these deals, investing it, you know, five, ten, you know, twenty, thirty, forty, forty billion. Yeah. And there's a lot of, there's a lot of funds who have expanded and will invest in anything.

Like you're a mining company, great, let's do it. You're, you know, you're buying Bitcoin on the balance sheet. Like, okay, let's do it. There were a lot of funds that expanded what it meant to just be an asset manager. And there were some funds that stayed very focused. and, you know, we'll see, but interesting. Highlights from the Dario Amadee interview on Dwarkeh Patel, Jacob Rintamaki, friend of the show has a quote here.

All my lawyers never want me to say the word, monopoly. Dario, Dario says, I don't think that's true. I mean, I feel like we're in an economics class. Dwar Keshe says, do you know the Tyler Cowan quote? We never stopped talking about economics. And Dario says, we never stop talking about economics. So no, I don't think this field is going to be a monochurchase. All my lawyers never want me to say the word monopoly, but I don't think this field's going to be a monopoly.

You do get industries in which there are a small number of players, not one, but a small number of players. And so that feels like the like where things are going with both the, you know, expressed viewpoints of the VC firms, investing in multiple labs, that there's a variety of strategies to deploy intelligence, whether it's the best model and get deployed. and traction, whether it's on the infrastructure side, I do wonder how many more changes there will be in the horse race. It feels like there's a new hot model every couple weeks and then someone fires back and then they go back and forth and back and forth. And with all the flow between the labs talent-wise, it feels very hard to corner the market. and it doesn't feel like anyone can patent the transformer or anything like that, which would be a completely different scenario. Can you imagine if Google just had the patent and they were like,

we actually filed a cease and desist against open AI and anthropic. They're not allowed to use transformer-based architectures anymore. Like, we invented it and we patented it, and you can't have it. It's ours. I don't know. But yes, we live in a world where the little tweaks, the little strategies that go into advancing the models and creating these improvements do not seem to be intellectual property.

They seem much more like economies of scale and process power of being able to train at ever larger, ever larger scales, Marshall, ever larger chunks of capital and do whatever it takes to get to the frontier and stay there. Let me tell you about Vanta. Automate Compliance and Security. Vanta is the leading AI trust management platform. Why do we play this? Because the stream, we're having issues again.

We're working to get it back up. If you can hear us, markets now see a 30% probability of a Fed rate cut by April. More than 80% of easing by June over on Kalshi. We're still seeing the Fed decision in March 93%. Say maintains rate, no cut. So a cut would be a wide. wild card at 7%, 9% for any sort of cut. So strong GDP growth, strong job numbers.

You know, stay the course would be the logical thing. But we will continue to follow it. Let me tell you about Railway. Railway is the all-in-one intelligent cloud provider. Use your favorite agent to deploy web app, servers, databases, and more. Well, Railway automatically takes care of scaling, monitoring, and security. Let's play this timeless clip of George Hots. and...

Nah, we don't believe in stealth. I'm a really open guy. You are pretty open. I tell you everything I'm doing. Come on, here's what I say. Here's what I say. I'm going to tell you what I'm doing. And you can try to compete, but I'll still crush you.

Nah, we don't believe in stealth. It's so funny. Also, I don't know why that person cut that to be so widescreen. It looks very cinematic. But I like the quote here. You think the... You think the eggs... You think the eggs I lay our value.

I am the golden goose. Meanwhile. Thinking people will steal your ideas if you share them is a sign of low IQ. And I agree we are in the era of agency. And actually going and executing on the idea is the difficult thing. You need to be charisma maxing. And there's still a lot of secrets to every business. Yes, they're all over.

And CEOs can, you can, you can, uh, CEOs can do 100 hours of podcasts and tell you a lot. about what they're doing without telling you the one or two things that are actually important, and it's very easy for somebody to come in and try to fast follow and ultimately just kind of get it entirely wrong, even though it looks like the right. And I think there was a huge incentive, I mean, going back to the Saspocalypse,

there was an incentive for a long time for companies that where their moat was not software, to say we're a software company, we need to hire the best software engineers, look at our open source projects, focus on all the cool tax, that we're building when really it was a marketplace, or really it was a liquidity provider,

or really it was a network effect. And if you're a network effects business, it can be sort of boring and honestly anti-competitive to just be like, look, we can do nothing and win. No one wants to say, no one wants to hear a CEO say that, but we're gonna find out who can do nothing and win because we'll see it show up in the margins over the next financial...

Meanwhile, over on LinkedIn, George Hatz is posting. And Riet says, George Hatz is the only thing keeping my LinkedIn feed good. He says, hello corporate participant. You are building the machine that will eat you. You think your fake money will keep you safe. It won't. You think your social climbing friendships will keep you safe. They won't.

The only choice is to stop. Tell your friends. Tell your neighbors. If you keep feeding this machine, it will eat you. The proposed revolutions will not be enough. A global scale nuclear conflict might, but even then, I'm not sure. The problem was never AI itself. It's the collapse of trust in society, apps, and phones have snucked between every crevice of people, and they are run by psychopaths.

The AI will be a further wedge, just another lever to manipulate you. You will not be able to stand up to it, and you will be discarded the second you don't serve it like layoffs. You will die atomized and alone, and you won't understand that you did this to yourself. Brutal. Nice little white pill. Nice little Friday white pill. He's such a white piller. Well, here's a white pill.

first, Figma. Figma isn't your average vibe coding tool. It lives in Figma so outputs look good, feel real, and stay connected to how teams build, create code back prototypes and apps fast. But here is the real white pill. For just $33 million, you can have a private home on a remote

resort in Utah. Can you guess where it is? Park City? No. It's at the Amman luxury resort. It's in the Wall Street Journal. The residence is the first to hit the market at Amman. In remote southern Utah, Amangiri Resort, a crown jewel in the Amman hospitality company's portfolio. Wait, they're doing residences?

They're doing residences. Global, they have a portfolio of global hotels and residences. They're listing the first private home for $33 million, located just over the Utah border from the small town of Page, Arizona. The hotel currently features 34 guest suites starting at 5,000 per night and 10 tinted pavilions at its camp, Sarika, providing a temporary. for travelers. But the newly built house on nine acres can be purchased outright. Designed by Los Angeles-based firm, Masa Studio, the roughly 12,000 square foot residence, has six bedrooms and comes

fully furnished. It's the first of 12 planned private homes, which will be about half a mile from the resort. OTP says, but does it have a bunkie? Does it have a bunkey? A bunkie? No, a bunker. Oh, a bunker. Oh, we're going to get into bunkers. There's a whole piece in the journal about how to secure a mega mansion. I know you've been asking, we have the answers. Until it's sold, the home is available to rent for $45,000 per night. Before we continue, let me tell you about Century. Century shows developers what's broken.

It helps them fix it fast. That's why 150,000 organizations use it to keep their apps working. So, residents have been part, residences have been part of the Amangiri vision since the resort opened in 2009. the decision to offer private residences now was spurred by the success of the 2020 Tented Camp launch, rising demand globally for hotel-branded residences, in a sense that the property was ready to take that step. While future residences will share a cohesive aesthetic, each will be designed to respond to the unique contours of the specific site. In Page, the median

sale price was $610,000 in August. There are currently around a half a in listings above 33 million, though, all clustered further north near ski resorts. Amund Gehry buyer interest has been strong, he said, particularly among Amman loyalists and North American clients. Additional residential plots, price between $5 million and $12.5 million are under contract. And so let's get into Lambda. Lambda is the super intelligence cloud building AI supercomputers for training and inference that scale from one GPU to hundreds of thousands.

The mega rich are turning their mansions into impenetrable fortresses, and we're going to tell you how to do it for yourself. Anxiety over high-profile violence has the wealthy spending big on armed security, bunkers, a bunky, and even moats. They're building moats. I haven't heard of an alligator in the moat or a shark in the moat, but people are, in fact, building moat. Being an alligator salesman, I feel like is unslappable.

I think it could be clankable. Yes, maybe. Still at the moment, unslopable. You've got to build the humanoid robot that can go in the water to wrestle the alligator. And that might be, we'll ask Red Adcock. Is it waterproof? Is it waterproof? Can it go wrestle an alligator or not?

Because I don't want it just to do my dishes and do the laundry. I want it wrestling alligators in my moat. So British music producer Alex Grant was living in an under construction mega mansion in Los Angeles. One morning, shortly after 9 a.m., an intruder armed burst into the, the home. He said, uh, Grant said he came in and we had a tussle. He was formerly known as Alex DeKid. Grant managed to call his manager who phoned the police. Soon officers and helicopters were on the scene. He briefly considered abandoning the project after the 2017 break-in, but ultimately finished the 24,000 square foot home, which has eight pools, a car elevator, and a nightclub. Wow.

But he doubled down a security features installing a guardhouse, tall gates and a security system with retina scanners that alert the homeowner to movement in the home. Later, I found out he had these knives on him, Grant said, who recently listed the mansion and a neighboring house for $85 million after moving to New York. In an era of high-profile violence, including the suspected abduction of Savannah Guthrie's mother from her Arizona home just over a week ago, the wealthy are investing heavily in their personal security, particularly when it comes to their homes. Security measures once reserved for presidents and royalty, safe rooms, biometric access, controls, laser-powered perimeter defenses, these are now mainstream items in luxury homes.

Executive protection teams and armed guards patrol gated enclaves and suburban estates. While tech startups are rolling out predictive threat detection systems built for the ultra-wealthy, the shift reflects a hardening view among the affluent. Traditional policing and communal safety are no longer enough, no security. So security is being privatized and customized. The new emphasis is reflected in sales data. roughly 45% of luxury homes in 2025 included a reference to privacy or security up from 38% the year earlier. So break-ins at the homes of celebrities and professional athletes have been putting the wealthy on edge.

A group of Chilean nationals was indicted last year for stealing items worth more than $2 million from sports stars, including Kansas City chief players, Travis Kelsey and Patrick Mahomes. Travis Kelsey. This had something to do with the visa process with Chile where you could very easily get a, tourist visa. So there was these like basically the allegedly there were teams that would be permanently based in the U.S. And then they would be running kind of the operations. They'd be in the kind of war room and then basically tourists would come for two weeks, hit a bunch of houses and then bounce. Wow. And those were the only people that were actually exposed to or exposed, meaning they were

like carrying out the different ops. Well, the Miami Dolphins player to a Tagova, Viola, Viola, I might be mispronouncing that, said he hired personal security to monitor his house while he's on the road. He says, let that be known. They're armed. So if you try to go inside my house, think twice. The homes of celebrities like Brad Pitt and Nicole Kidman have also been broken into Miami real estate agent Danny Hertzberg of Cold War Banker said he began noticing an increase in emphasis on security in 2020 when high profile executives were migrating from New York to Miami during the early days. of the COVID pandemic. Private jet tracking websites have also been an issue. They sent chills through the high net worth community. Corporations are taking note.

Companies offering personal security benefits for CEOs increased by 10%, according to Goldman Sachs. One entrepreneur capitalizing on this growth is David Weiderhorn, who got into real estate after selling a tech company in 2017. I wonder what he sold. He recently built a heavily secured home in Scottsdale, Arizona. and he, in early December, Guiderhorn walked through the 8,600 square foot property,

pointing out 32 casino-grade AI-powered facial and vehicle recognition cameras. There's also a laser intrusion detection system around the perimeter. Pausing at a steel double gate in front of the house, he warned that the security system kicks in even before visitors reach the front door, which is fashioned out of three-inch solid, three-inch, thick solid steel and has 13 dead bolts. He said even the landscape was designed as a deterrent. Cacti. Cacti. Sour orange trees. There are sour orange trees with four inch spikes in concrete planters on the edge of the property. And just beyond those trees separating the house in the

street, a moat. Gators. A moat. Gators. If you try and run through that bush, it will be a bad day for you, he said, should anyone get past the trees, lasers will detect motion and the system will call the police. Inside the house, three ear piercing alarms will go off. And this is an interesting thing. The fireplace surround, like around the fireplace, in the great room, it will change colors. It's made out of crystallo quartzite, and it can change colors. So it'll turn red. So you're sitting there, and if there's anything detected on the property, your fireplace turns red above the TV to show you that something's going on. Very interesting. That's a visual. cue. The home's most fortified feature lies behind a wood-paneled wall, a reinforced concrete

safe room with a 2,000-pound door and an air filtration system built to U.S. Army Corps of Engineers standards. Widerhorn declined to scare specifics but said it cost more than $10 million to build the house. About $1 million was spent on bullet-resistant smart glass, and the front entry security features cost more than $1 million. In Las Vegas, clients of luxury design firm Blue Herons are spending between $100,000 and $1.5 million on security features, including safe rooms and bunkers. Blue Heron is now working on new ways to incorporate architecture with security, such as exterior window shades that could be closed with the touch of a button to protect the home's occupants. In Surfside, Florida, the developer of the Delmore,

a planned 37-unit ultra-high-end condominium project designed by Zaha Adid architects, and with units priced it up to 200 million, has tapped a Washington, D.C., based. security firm to design the building security. The $200 million condo. Yeah. That is crazy. But I mean, I guess from a security perspective, if you're in some massive building,

you're sort of like diffusing the cost. There's more people that might notice something. There's more security guard. It's almost like a gated community in one building. I'm just, yeah. Probably layers of access. I'm just purely thinking you're effectively looking at a hundred million dollars, a floor, right?

That's crazy. A couple floors. Maybe maybe a few. It's up there for a condo. That is huge. The firm is working to integrate technology like biometric access, facial recognition and Irish scanning into the design of the project.

For instance, when a resident or visitor pulls into the building's parking garage, their car will be scanned for license plate recognition, but facial recognition may also identify the car's occupants and their level of approval to access the building. That in turn triggers the security system to allow the person to unlock only

the doors and elevators that they are permitted to pass through. Meanwhile, an AI-powered security system will track movements captured on camera throughout the building, looking for anomalies. Hertzberg said he recently had a client fly in a security consultant to evaluate a roughly $50 million house he had put on under contract. The consultant looked into the viability of installing a complex camera and laser system that could sense any movement on the perimeter of the property, including the water. So lots of interesting stuff. Let me tell you about cognition. They're the makers of Devin, the AI software engineer. Crush your backlog with your personal AI engineering team. If you go further down, they talk about San Francisco tech entrepreneur

Kevin Hart said he and his high net worth peers in California are increasingly focused on security. Kevin, of course, has a home security startup. Yes. Harts said he co-founded his own security company, Soron, in 2024 after being spooked by an attempted break-in at his home in San Francisco. The person first rang the doorbell before making his way around the house, trying some of the doors and windows. When he couldn't gain access, he went to Hertz next door neighbor's home, where he tried to push through the front door. He was arrested by police. That could have been us. Harts said, the Soron system, which has only been launched in beta across a few homes in the Bay Area will differ from other security systems, and that it includes deterrent strategies not only

a response. For instance, if it senses an intruder, it could include a feature that automatically triggers sounds, such as dogs barking or police sirens coming closer. Just the sound of dogs barking feels like a great feature. Just OTP in the chat was saying, do none of these people have a German Shepherd? Yeah, German Shepherds. Fun fact about German Shepherds, you can, like, a purebred dog might be like single digit thousands,

but there are companies out there that will train a German Shepherd for, like, the military, basically, and then also train them to be pets. So they have that level of training, and then you can get up in, like, $40, $50,000 range for dog, which is hilarious. Dog as much as a car. But dogs are typically listed.

It's a lot of money, but it's a lot of dogs. It's a lot of dog. It's the GT3RS of dogs. Truthfully. But whenever you look at the list of like, what's the most likely thing to eliminate, you know, home intrusion risk, like dogs are always at the top. Quickly, let me tell you about another great Valentine's Day gift. MongoDB, choose a database built for flexibility in

Gail with best in class embedding models and re-rankers. MongoDB has what you need to build what's next. And without further ado, we have Martin Scrawley in the Restream waiting room. Let's bring in Martin to the TV event ultra-Rum. Martin, good to see you again. How are you doing? Technology brothers. How are you? We're fantastic. How are you? It's great to see you. Excellent. Are you gearing up for the weekend? Are you excited? Caffeinated, ready to do more work? Fantastic. Locked in, the great locket. What's your daily caffeine stack? Yeah. You know, we talk with Heberman about this. You're the natural. Are you a microdose?

microdoser or do you like do 400 milligrams and then coast? I do I do coffee several coffees and then just like keep taking drinking this all day long and it's a four hour energy yeah five okay five hour energy oh wait how many hours are they how many hours are they doing these days four five it's a lot of energy five anyway what what are you seeing in the market give us the update on just how you're processing the last week of chaos, whether you want to talk about software, quantum computing, what's going on? What's worth following? Yeah, so I have this new potential product. My productize this. I've been tweeting it for now for free. But it's basically this something nobody's ever done before, the VC investors,

which is I'm using my network and some heuristics, maybe even some AI, to guess kind of what positions people took in rounds. Obviously, for some cases, I know exactly what the cap table is, but in other cases, I don't. So I have this. I have this. list of gains or investors. And it's very interesting. So, you know, I started with like, obviously the joke one, which is FTX, would be up 36 billion today. Sure. You know, putting in, what I guess was $300,000 in any sphere, which of course, is cursor at a 4.4, you know, $4.4 million pre-money. Is that really the pre-money? That's still insane. That's still insane because in that, in

that era. 10. Getting, getting into a great company at four. Like, if somebody was pitching you a company at four, it was almost bearish. Like,

oh, they're complete outsiders. Yeah, they didn't have the comp. They didn't talk to anyone smart. That was like, hey, you guys are really smart.

Now, again, like, price it at 10. I'm guessing and have, like, various heuristics. And obviously, like, I'd call somebody like you guys

and say, actually, I think you want to talk to this guy or that number might have to go up a little bit, et cetera. But that's better than nothing. And right now at Crunch Base and pitchbook and stuff, there's you just there's nothing and so it's a lot of fun and so that 300,000 investment

they raised 400,000 so my guess was was elevated to 300 I think I can look at it's actually in the bankruptcy document so eventually we'll get the exact number but that's a 1.2 billion position in today's money obviously the the bankruptcy estate lawyer is just like oh what the fuck is this any sphere it sounds like zero yeah it does it's that when you say any sphere in the context of FTX it sounds like we're a blockchain company looking to do to build a live multiplayer game and your eyes start to

glaze over a little bit. How many NFTs did any sphere drop? Not quite. Anthropic, they'd be up 32 billion now. I'm sure his last BF had the yeah, he posted a little thing about that. Thrive is the big

mystery player because nobody really sure how much money they sunk into Open AI but they also did any sphere. Mm-hmm. Yes. You know, so huge, huge gains from Thrive. They were in a couple later rounds of scale and some other companies.

So big, big numbers there. Probably one of the more interesting ones is is Reed Hoffman. 50,000, $50 million first check in Open AI with Klaus, maybe 25. Okay. 25 or 50.

And that, you know, worth many billions. And then Jan Talin, the EA CEO of Co-founder of Skype. Yeah. Skype guy. 100 million turns to 11 billion. in Anthropic first check with Reed Hoffman.

So 11 bill. So a lot of fun to look through these and see like, you know, you can sort of calculate the returns. And of course, VC fund returns eventually either go public or you can find them somewhere or like oftentimes state pension funds and stuff do that. So anthropic obviously the big use. It is when you, as you break this down, it's so funny that crunch base never like tried to roll out even something that was like generally accurate.

Like, it is, like, very fascinating information. And especially now where, you know, Dan Primak was joking, like, it's easier to list, like, who's not in Anthropic at this point from kind of the big name funds. And so that just makes this kind of information, like, more interesting because, yeah, it's cool that you're in a company. And almost anybody, if they work hard enough, can get some exposure to these names. You know, maybe it's, like, via an SPV or an SPV and an SPV. but still this is the information that like is actually like super fascinating.

The other interesting one is Dustin Moskowitz, who was 25 million in Anthropic as part of the effect of altruism mafia, was able to make $4 billion, which I think offsets his losses from starting Asana, but I'm not sure. He didn't. That's ridiculous. There's no losses from founding. Well, that's that the, that the, you know, the anthropic position would be worth 2x what Asana is. Yes, yes, which is crazy. But he's not sitting on losses.

Oh, you think he bought it at the top? Well, we know he bought huge amounts of a sauna with cash. Okay, okay. So maybe. Keep that in mind. Yeah. Maybe. Maybe I doubt it.

But, you know, to your point. He's doing, he's doing well. So the lesson for folks is just get a small check in the next Anthropic. Get a, get a, try to network on ineffective altruism. I think that, that seems to be the. Yeah, what was the alpha from EA? Like, what? Yeah, do you have a post?

There's a lot of smart people that have no other things to do. So their social setting is like replaced by this sort of like religion or anything like that. And, you know, this cult. And if you're in a cult of really smart people, it's probably something good will come with it. Do you think it's still a cult or do you think it's like B2B SaaS now? I think it's changed a lot. It's like B2B SaaS. And I think like the new cult is.

The new cult of B2B SaaS. You're welcome. The water's warm. Come in. It's amazing. We're automating workflows. We're delivering enterprise value. We're hiring consultants.

We will forget about all the earlier stuff. We will welcome you into improving the economy, raising GDP. This is what we stand for in this cult. Maybe the new cult is the AI agent, you know, website or whatever the, you know, or whatever's next in that world where, you know, the AI entities. What's your personal? So I wrote in the newsletter today, like somewhat of a joke, but a more serious topic. become unslappable, the idea of there are still real modes that exist and the historical

mode of just, we had a bunch of smart people working on building this software for a long time. So if you want to compete with us, you have to also spend a lot of money and a lot of time hiring a bunch of software engineers. That's going away. Yet you're building what is a seat-based pricing tool. and I expect you to do very well with it just because I think in the future individuals will want great access to data

to make different decisions and maybe they're working with agents as well so like I can see that... Yeah, the agents need the data. But what's your personal philosophy because you're clearly not... If you were just caught up in the kind of like fear-based marketing of the labs,

you might not be building, you know, seat-based SaaS tool. Yeah. I mean, data's often firewalled. You know, there's, you know, we have a guy that just talks to every exchange in the world. And, you know, the amount of times he has to pull his hair out because, you know, some exchange in Asia wants to meet yet again, you know, before signing the deal. And, you know, there's no self-checkout. There's no agent. You know, you have to, the protocol is sit down meeting.

And every time you go to an enterprise SaaS company and it says talk to sales, you know, it's sort of like, what does AI do at that point? So I feel like, you know, there's, you know, you also have this trend where, you know, why would you put huge amounts of data into the model, the model should call out? And, you know, compressing the world's information into some parameters and weights, it's just not a wise use of parameter space. And I think everybody's been saying this in AI. And so the problem is, okay, shrink the whole internet.

But what happens when stuff leaves the internet? You know, there's a stock that Bloomberg doesn't have in its portfolio. You guys weren't born yet, I think. But it was called a web van. Oh, yeah. Oh, we know about web van. My family used home grocer, which got acquired by webvan. And I think the home grocer founders probably got liquidity before web van crash.

So I think they wound up doing very well. They killed it. Yeah. Check it in with them. But yeah. Yeah. So Webvan is not on Bloomberg, for example. Yeah.

Even though it's supposed to be this great tool. And it's certainly not, you know, on the web. You know, lots of data gets, like, deleted from Google. And there just isn't this, like, rich tabular data available. So tabular data, I think, is going to actually thrive in the AI world because, you know, it's just not going to be in the models. Or if it is, the models get tired after a while. It's not going to give you 3,649, you know, SaaS companies.

with this market cap, it's going to say, here's the top 200, and don't ask me about the next 3200, because that's just not what LMs are really good at. But the frontier technology is sold off very, very hard in the last month or two. And there's a lot of speculation in the quant community as to what's happening. So there's some funds that ran really well with this frontier tech. So I think that includes quantum computing, but also includes nuclear, drones, you know, space, you know, all the stuff that's sort of, you know, next generation things that aren't here yet. And this was like the hottest sector last year.

And anybody who didn't have exposure to this underperformed, and there are some quant firms, I think, that were very, very, very over-exposed to this. And then New Year started in the hedge fund and quant world, January 1st is like a brand new page. Like nothing matters from last year. You forget everything. And so this factor just flips in reverse.

And part of the reason was, was the calendar, I think. And now the quantum stocks look like dog poo-poo, and they've gone down a lot, and, you know, nobody knows what to make of anything. But in the private world, you know, numbers are still, you know, still big valuation, still lots of, you know, big up rounds so far. So that disconnect will be really interesting as time goes on. There was, you know, last time I talked about photonic computing, there's new company, Teelfellow, young guy. You know, I'm telling you right now, these young guys think that, you know, I'm this old dog that can't learn you, I'm going to teach all of you, Youngbucks, 22, 25.

You come into MySpace, I'm going to show you. I've got the dog on me still. But anyway, Olyx is what it's called, and he's raised 220 or 250 to do photonic computing for AI, which, you know, I think is, you know, that's the second company or a third company now that's come out and said, we're going to do it. And he's going to do it with SRAM, interestingly.

So he's got SRM on board. And, you know, so it's like GROC plus, in essence. And I think it's a really good idea, but, you know, execution does matter. What do you think about biological computing? We talked to a fellow who built a neuron in the lab, and it was way over my head. Feed some protein, sugar. Yeah, sugar. So we like the protein part of the interview, but didn't get much further than that.

Yeah. I mean, look, that's how we do it. So I don't see. Why not? You know, I think that it's a spiking neural network, right? it's a little different from the software neural network, but I don't see why you couldn't do it. I think the reading the output is kind of difficult.

In photonics, you have to use almost like a camera. You wouldn't use a camera, but you're using a camera-like sensor. And that sort of is your readout. What's your readout here? Well, probably in the body or the brain, we're using like calcium levels or like other things like that as well, synaptic firing. But if you want to have really good control of that, I don't think we know yet how that works.

But of course, they've gotten these brains in a vat to play Pong and do other things like that. So, I mean, it's certainly possible. And, you know, I was thinking about this with my girl who is in the space about, you know, potentially do we buy pig farm? And we buy pig farm, pigs are really interesting. They're obviously the pork part, you know, gets sold to meat companies. But what's interesting is different parts of the pig are biological drugs. So there's adrenocortocotropin hormone

which is sold for a huge price and then the pig's lungs also make a surfactant that's sold for a respiratory disease. And then finally the brain we're going to keep and grow that in a separate container. We're going to rent it out to Sam Altman at the end. Slop. Slop of the trough.

Literally slop. You will be literally feeding slop to pigs. Yeah, play the pig noise. five times. Talk about the, what's happening in small caps in, uh, or sort of like the long tail of the market is a reaction to the AI boom. I, I, I, I texted a friend who, laughing at, in 20 years from now, your, your child will say, my, my father made is money in pig farming is money and pigs. It's great. I love it. Uh, yeah, I, I texted, I texted my friend saying like, you know, look, everyone is talking about a chip bottleneck.

There's this massive AI buildout going on. Like, have you looked at TSM? And he was like, oh, like, it's like too big to have like some breakout move. Like, I'm not interested. Like, call me when you're talking about, you know, a $4 billion company that's like deeper in the supply chain. I talked to one person that was like they found, they were excited about Anderl. They found some tiny supplier to Anderol. And they were like, this is a proxy.

what companies are actually interesting, how do people think about those like long-tail, early, smaller cap companies that are still like properly indexed to the correct narrative around AI? Yeah, I think they're all scams. I mean, it's an unfortunate, you know, situation. And this is why, you know, actually, Joe Lonsill, you know,

I think I talked, did I talk with this last time? You know, he gave a talk with the SEC commissioner and he basically said, why can I buy TBPN coin? No such thing, by the way. Or that triples. TBPN coin or whatever. Coin you make up on the spot. I could put millions in it, lose all my money.

There's no investor protections. But if I try to buy Andoril, God forbid, you know, you guys blow the whistle. And Matt Grimm stops everyone from buying it and so forth. But the, in all seriousness, I think that that's something we have to fix. I mean, because you end up having people chasing. kind of really low quality companies. There's companies that just change their name to AI and hope that somebody buys them. Same thing with quantum and other things like that. And I feel like two things should happen. First, we should let people buy privates. But two, more privates to go public.

And I think like demystifying and making that less scary, like if, I was sorry, it was Reppelin's Reppelin to go public because there's a drug company called Replomew. And it would be the same ticker. It's like, you can't go public without them. So you have to buy Replic. Repleman. Okay. You invest the drug, and you can go public. And Elon had to buy United Steel because they had X for like 100 years. Oh, yeah.

And, you know, now X is available. So he just waited for them to get bought out by somebody else. Perfect timing. That's crazy. In all seriousness, you know, going public is the best thing ever. It's the freest, cheapest capital of all time. We obviously have seen down rounds from privates in publics. But, you know, that's mostly for like boring SaaS.

Once you have AI, you know, you're going to have, you know, a million. in times revenue. Obviously, the difference with the two is hard to say, but I think of a company like Replet when publicly, you'd be surprised at the valuation you can get. I think you can, there's enough demand out there that I think some of these guys should start going public. Did you have the same read on a lot of people that Michael Grimes going back to Morgan Stanley was incredibly bullish for late stage? Really big deal. Yes, yes, that Grimes, of course. Incredibly bullish for late stage tech and the IPO window being firmly open. I think so. I think you're going to also see other people from D.C., you know,

rotate back, and, you know, it was a really great thing for these people to actually truly make a sacrifice because, you know, I don't think there's that much upside in D.C. And, you know, it's an amazing thing for them to come, you know, do something good for America. And then now you have, you know, people like, you know, folks like Anthropic and Open AI, where their capital needs are larger than the private space, to be frank. And, you know, I think that the ability for them to raise, you know, $100 billion or $200 billion or $300 billion, the markets could realistically support that,

whereas I think the private markets you're really starting to stretch. Like you said, I mean, that anthropic list of investors, the exclusive syndicate was, you know, virtually a long list of every big fund. Yeah. Jordy, what else? 11 labs, 11 billion. Amazing.

Do you use the product? So we, so my company, our first six to nine months, I think we spent trying to make a better 11 labs. Oh, yeah. Or compete. Truth be told, we couldn't make an equal. So couldn't make a better one. But it was sort of my fast lesson in software, which is, you know, the only thing that matters is sales. You know, product and second most important in engineering is like last.

but you know if you if you if you if you don't have distribution you don't try to sell the product it's not going to sell itself and it's a sober lesson of those guys like very aggressive for the longest time if you did a one word or two word sentence in 11 labs it wouldn't output it at all there were hallucinations or all the stuff they just pushed you know they fixed all that stuff of course but you know they pushed really really hard on sales and and that sort of fixes everything And I think that, you know, it's some of the best VCs I've ever talked to said, you know, when are you going to launch your product? And I said, oh, it's not ready. They said just launch it, just launch it, just launch it, just launch it. And, you know, get off the uncomfortable, like, stage fright and just start selling and you'll get more feedback and so forth. So they, I think they took that to heart really early on and just, you know, they didn't have better technology necessarily than other guys. I think they just sort of, you know, realized, okay, who needs to buy this stuff? Let's go build, build infrastructure around that, just incredible success. I mean, I, I, I, I tip my hat to them. Yeah.

How do you think about the moat that comes not from software engineering because generating code is cheap or soon to be free, but training spend. So if I spend $100 million employing a bunch of great software engineers for four years and built some elaborate software system, and you can just vibe code it for two orders of the magnitude, less cost in tokens, you clearly have an advantage against me. But if it's going to cost you $100 million to do the training run that I did for $100 million, is that a durable mode?

I doubt it. You know, I think it's product and sales and brand and things like that. I mean, it's trad business. So there's going to be a lot of people replicating products and then they fail and they're going to wonder why. And, you know, it's the rest of the business. You know, there's, that's, you're talking to 10, 20 percent of your organization. I mean, you really have to get the rest of the organization excited about product. And I think you're going to find one interesting thing that will happen probably is that folks from embedded entrenched industries like certain manufacturing and certain materials businesses, things like that, they're going to spin out themselves and say, I'm going to solve the problem that's been plaguing my industry, but I'm not a

programmer. It's like that I'm not a rapper YouTube. And I'm starting a software company, but I'm not a programmer. But I know that our whole oil industry has had this huge well software problem. I'm going to build the wealth software. And I think startups like that are actually going to not only create tons of wealth for themselves, but they're going to actually help the economy. And that's where, just like the internet help GDP, that sort of solution is where

you're going to see GDP needle move. And it's going to be, it's a wonderful time to be like the nerdiest best guy and say equity research or something like that. Because you know, you might have an inkling, like a rival might have an inkling that, oh, you know, finance is going to be changed by AI. I'm going to try to point

my apparatus at this and figure, you know, out. But if you're the guy that's like, I know everything about, you know, this type of little narrow thing, you're going to really crush it because, you know, you really know what the problems are. So people coming out of industry, there's a rival of ours called Rogo. Rogo is AI company, focused on finance, old Wall Street guys. They have a much, much better chance of succeeding because they did the job. They know what to do. And I think you're going to see so many people come out of the S&P 500 that just said, oh, I was working at Eaton or or Fleur or like companies that are just like big,

you know, Pulte homes or whatever. Sure. And all of a sudden, you know, they're starting software companies that solve the key problems in that industry. Yeah, so maybe the only problems these guys aren't. More companies, but fewer computer science background founders. Yeah, definitely.

I mean, so many of these problems can be solved, I think, without knowing every single data structure and things like that. I mean, obviously, you know, there's just gonna be people, it's gonna be a barbell, right? Right? Like there's people who still need to know how to make an FPGA and program an FPGA. And, you know, when Elon said that, you know, he sort of said a lot of people on fire over the last few weeks when he said that you're going to see AI write assembler or even machine level code, you know, compiled assembler. And, you know, that's a pretty wacky idea. And think about wacky ideas from Elon is they tend to be right.

So it's definitely, you know, one of these things that, you know, is kind of mind blowing that, you know, if you think about AI safety, you know, you know, tell the program, you know, give me a program that does SaaS for oil wells. Cool, here it is. But by the way, you know, in the compiled assembly, which you can't read, because you don't, you don't speak binary. You know, there's this thing that says, you know, I'm taking 5% of the revenue and sending it in crypto to my. I like that that's your AI doom scenario. Just, just slight fraud and theft. Clipping 5% off.

Just clipping a grift to. How do you, do you expect layoffs on Wall Street? Because with all of the broad fear right now among white collar workers, I'm not seeing the layoffs that are explicitly, you know, hey, you were doing this thing for the company, and now we're just running this agent to do that. And so we'll see you later. we are seeing, hey, you are doing this thing.

Now AI can help you do it a lot better. So our expectations are going to rise. We are going to expect you to do more and be more productive, but you still have your job. What are you kind of hearing from people at different finance firms about how they're adopting AI and how they're feeling about job security? I think in general, one of the things you learn in founder school after your fourth or fifth time is that, you know,

you're supposed to hate firing people and you're supposed to learn to like it over time. Nobody likes it. It's the worst thing ever. And the funny thing is, if you become more productive at work, the company doesn't say, oh, yeah, well, let's get rid of you

and save whatever amount of money. Because they're already making money with you employed. So the fact that you're becoming more productive means that, you know, whatever the margins were, they're probably improving. Could they improve even further

by getting rid of you, maybe? But I think there's this like slow atrophy, maybe. but I think in general, we as humans want to employ other humans, and we kind of want to be productive. I mean, nobody wants to needlessly employ people, but I think that there is this idea of, okay, machine can do your job, but we have this at my office all the time.

And I say, Chris, you know, I have a program to do your job, good news. You don't have to do it anymore, but there's a new thing you have to do now. And, you know, our company just got twice as efficient. It's wonderful. And if the day came where there's literally nothing for Chris to do, then maybe, you know, that would be, you know, that could be the day that made sense. But I think that we want to take care of each other. There's always an incremental thing for a company to do.

I think so. No startup founder has ever thought, great. I did it. I built the six products that our customers really need. And there's just no other way for me to expand the opportunity set. Time to kick back. Yeah. I mean, yeah, those businesses die, though.

Yeah, they do. You're either building. I mean, if that person has a couple more hours a day now, it's great. You know, go meet with, you know, some potential recruits. Go meet with some potential customers. I mean, there's always something you can do. And I think that's going to happen in finance. Adoption of AI has been very slow.

And it's probably going to stay that way. Finance people are really stuck in their ways, which is a good thing and a bad thing if you're selling software to them. Once they get stuck in your way, you're very happy. but you know the you know there's there tends to be a heavy dose of contrarianism in certain industries and I'd say you know cross the S&P 500 there's this sort of like

ah you know technology we'll use it eventually and that eventually takes time and that's why the first people to adopt this stuff in great ways is not only because it works really well but also because they're used to doing it as developers developers love AI and they've embraced it

you know very quickly virtually all programmers now use AI there were a couple of holdouts even at our company, but they eventually just gave up. And I think you're going to see the same thing in other industries. Finance is tough because, like, there's this mystical idea that the trader is this, like, random, you know, far into the bell curve, like, super talented person that just knows, has this, like, weird zen kind of ability to tell what stocks are going to go up and down. And then the other end of the barbell are the quants.

And the quants sort of feel like AI is not good enough, but many of them under the, What I've heard is many, many quants are getting new ideas from AI and also implementing them with AI. So I do think that... Yeah, if you work at a hedge fund now, you can just ask your favorite LLM, how should I hedge AI and just implement exactly that? And you're guaranteed to outperform. No, I'm kidding. It's a little bit scary for some quant funds because you do have to wonder if, you know, the thing you've been doing for 20 years, that's your profit center is going to possibly be done by somebody else. that is a little worrisome.

And then eventually, and certainly there are firms, I can name them, but you can just guess the big sort of institutions on the street, that they're increasingly thinking about and even in some cases deploying transformers to do analysis. And I don't see why, you know, the hard part about being Warren Buffett was disciplined,

right, is saying no to so many things. And if you can put that in the prompt or put that in the, you know, in whatever, and the context and you just say, listen, I really only want the best, you know, the highest quality companies, the best returns, say no to everything else. And, you know, I don't see how that's, you know, impossible.

If you just copy the Buffett, you know, strategy, you might be better off. A lot of the mistakes in investing come from overdoing it in things that, you know, in FOMO and things like that and resisting that FOMO and saying, you know, I'm just going to sort of buy these types of companies and do my thing. So I do think, like, investing as a whole are going to start change a little bit.

Lightning. I have four questions. I've got one and then there's a lot of performative AI usage happening right now, the people that are, you know, ordering a new Mac Mini on DoorDash. Ordering 10 Mac Minis on DoorDash. We were joking around

with this yesterday. But, like, who are you looking to for founder-style roles? Like, what do you think truly the most like the best founders are doing like ideally like the most important working on the most important thing at the company which could be a recruit could be a customer could be getting a raise done it could be going going on a long walk and just thinking about the business but there's like heavy amount of delegation and ideally they're like delegating to people that are using a bunch of AI but like do you have any sort of like internal fear around am I using this stuff as efficiently as I should be myself Are you looking to anyone and saying, like, okay, they're actually really tapped in? Because just buying a Mac mini and setting it up and, you know, having it running and texting it, you know, here and there is not necessarily qualify you as like actually tapped in. Yeah.

I wonder if there's a way to, you know, to not annoyingly reach out to customers with AI. And I think that, you know, we all get that email. Like I just hit block on all of them. the, hey, I noticed that you're doing this. So now I'm, you know, I'm, you know, I'm a vendor that's offering you that. And I think that's, you know, going to result in not too many sales. But I do think that these things have some yield. And I wonder if there's a really good way. That's sort of in the back of my mind worries me. And then at this point, I wonder if LLMs can do, can replace recruiters, right? Where they say, who's, who is the best at, you know, time series tick programming or

something like that. And L.M. says, John Smith here, Dave Smith there, you know, they're also named Smith for some reason, and Will Smith there. And I think those, you know, at some point that might happen. Now, of course, some of that's just human knowledge where people whisper amongst each other that, you know, oh, you know, this is the best person at this kind of investing. But I think that, you know, because we're all like blogging and like putting stuff out there, you know, we may also just be able to, you know, ask that person who's the best person. So I feel like there's definitely new ways, creative ways to use AI that people are coming up with all the time that are really surprising and shocking. And they're all like secret sauce, I think, for most people. But, you know,

chain of thought was our secret sauce for a while. Yeah, on the recruiting front, I met a guy a couple years ago who like only his entire recruiting business for years had been work Brazilian fintech engineers. Like he had just done a decade and all he did was help companies hire the best Brazilian engineers that liked working on financial services companies. And he had carved out a great business. And I do wonder, I don't know that identifying who the great ones are. It's like maybe you did a certain number of years at New Bank and then you popped over here and then you popped back.

And like, you can probably pick up some of that stuff. But then what is the value of just like actually having, like how durable is the personal relationship with those people that you've placed over a long enough period of time? and can you continue to basically extract rent because they will respond to your text and not the millionth, you know, millionth, you know, AI text that is constantly kind of chasing them.

Anyways, lightning around, John. I'll just do one. Neo Labs, bullish, bullish. What do you think? I'd say bullish. You know, it's a contrarian view, I think, because I'm especially looking forward to J.T., Jerry T.R.X., NeoLab.

I think these are really smart people. Are they product companies or are they research companies that will get acquired in? I think they're going to all have a crisis and have to figure it out. Yeah, so here's the, here's, like the, the kind of bearish take on Neo Labs. From an investment standpoint, I get it because I would say like really, really elite smart team. There's somewhat of a capped downside. If you invest $50 million, you could probably get $50 of worth of, you know, one other lab that's actually working down the line out. if it doesn't work out.

But these people were like working on something like, you know, hey, these LLMs aren't really learning in real time. They're just kind of like in a certain state. And I'm going to leave this lab and go work on that problem. Meanwhile, the lab is still working on that problem. And we've also seen as different labs have different advancements, the other labs can like quickly just catch up, right? So like one person has a breakthrough.

And so my question is like if a NeoLab raises. is $100 million and actually has a breakthrough, then they just have the problem of, like, are we actually going to be able to sell this better than the labs that will probably figure out how to do this? Then the big labs, it'll figure out how to do this in the next maybe two months later, but they have a million customers already.

So, like, that's the bare case for me. It's like, even if you have this like breakthrough, you don't have the like sales, distribution. Yeah, no, I mean, the bare case is one of these people know about business. they're starting a business, right? So it's kind of a scary thing, but I think that, you know, look at biotech and some other industries, you know, this is pretty common. And ultimately, I think they're doing the hard part.

You know, the easy part is you get a bunch of good-looking guys like you guys, and, you know, you get them to start selling positioning product. But I think the hard part is, yeah, how do you do continue learning? How do you do a new form of the AGI? It's a little past most of our pay grades. And I think, you know, there probably will be a crisis where, like, the real ones will be separated from the fake ones. But that's just human nature anyway. Like, there'll be some funding crunch.

And then somebody has to, like, emerge with that dog in them and say, no, I'm going to raise another $200 million. I'm going to come out with something tonight. And we're going to do it. And that type of, you know, crazy, you know, person where – and then there's going to be folks like, I don't want to name a certain AI company that folded. But I'll throw in one that did, which was the guys who made hay pie inflexion. They sort of had that outcome that you're talking about. But there'll be people that see that valley of death and say, no, we have to finish this. And I think that probably one of the biggest things that people have to remember, but they don't because they don't care, is that the investor's money is sacred.

And if you're just thinking about it as, oh, what's the worst that happens? I wind down and Sequoia loses their money and this and that. I take that really seriously and everyone should. And, you know, I think that the handful that do, you know, will see their runway dwindling and saying, we really got to do a product here and tough it out and figure it out. And I think those will be the, you know, future, you know, future leaders. Well, thank you so much for taking the time. Well said. Top on the stream. Always a great time chatting with you.

Always a pleasure. Have a great weekend. Good to see you. Enjoy the building. Enjoy the caffeine. Enjoy your fifth five-hour energy. I'll tell you about Plaid. Plad powers the apps used to spend, save, borrow, and invest. securely connecting bank accounts to move money, fight fraud, and improve lending now with AI. We have Connor Hayes, the head of threads in the studio.

While he comes in, I'm going to tell you about OCTA. Where's OCTA? Octa helps you assign every AI agent a trust identity so you get the power of AI without the risk. Secure every agent, secure any agent. The vanguard. The vanguards are out today. Oh, they're out today. Well, they've been out, but they're out here.

They're out of your head today. Like months ago, months ago. I have to ask you guys before we start. Please. How are you recovering from clav getting brutally wrong? You frat leader. I just want to know. It rocked the timeline.

It rocked men everywhere. Are you okay? I mean, I think the reason that that resonated is everyone's experienced that, right? I get that every day. I get that every day. John Cugan has never been. It was predictable. It was predictable.

I think it was predictable. Yeah. I wasn't that surprised. But we did. this morning, sauna. True. Remember, the whole team was in the sauna. After our workout this morning and this guy

must have been an ex-bodybuilder. It was just ridiculous. It was one of the widest backs I ever seen. That's why you need the meta vanguard's on so you can capture that. Although I think people are that. That's a feature that could be a hit is basically like

real time video model that reduces if somebody's coming up to frame log you, it just kind of reduces them. There's like haptic feedback that sends you out of the frame. I mean, those are some frame mugs right there. You call them frames, right? They're fantastic.

How is life? What is the day-to-day like for you? The day-to-day changes a lot. We're doing, you know, threads, I think a format like that only works if you are at the center of cultural relevance. And so that brings us into a lot of stuff that's going on in the world.

We were like all over Super Bowl last week. I'm here this week because we're doing a bunch of stuff with NBA for the All-Star game. So that's been really, I mean, that's fun. It's work, but it's fun. And then the rest of the day is like, how do we make the feed better? What are we doing on, you know, content understanding?

Our model's good enough to, like, you know, do something like the Deer Algo feature that we just launched. Yeah, we're talking about that. First, Super Bowl NBA, like, obviously, we all know that social media content production is power a lot driven at this point. There's a few creators that take it really seriously and they have expert teams. obviously threads is like a little lower barrier to entry than a polished two, you know, hour long YouTube video or something like that. But are you shaking hands and kissing babies to get people on the platform? Is that what that is?

I haven't kissed any babies. I have shaken a lot of hands, actually, though. Yeah, so we have a bunch of program. It's actually one of the benefits of doing this at meta. We have such an infrastructure of working with creators and partners. And I think we talked about this actually when I saw you guys in September. like the big learning for us was the people that rock at Instagram don't necessarily succeed on threads out of the box. It's kind of a, it's a very different format.

Yeah, you got really good at making pictures and videos, and now you basically need to be really good at captions that can stand on their own. It's wit, it's like insight, it's things like that. But if you're good at that, to your point, John, the barrier is so low. I was on a flight here two days ago, and I think, I fired off like 15 posts on the flight, replying to people and whatever. And I'm not sending clips to a production team and having them edit it. So that's the beauty, I think, of the format. Yeah. How is the AI spam revolution keeping you up at night? Or is there, does meta have strong infrastructure there where you can kind of just like out of the box identify things?

Very much so. Yeah. I mean, we like, I think as a company have made some good decisions in the last decade of taking these things that are like, basically infrastructure that you would need for any service you build, ads, financial services, integrity detection and monitoring. And we build central teams out that do that for the company and then build it in such a way that it can be applied to any app. Yeah. So we just benefit from all the work that the central teams do. We have some folks inside threads as well. But maybe what you mean, though, is like the agents coming into social spaces. I mean, I guess a somewhat tangential question is just like, when GBT3 dropped, it was like, okay, like, it can write text. And then the surprise to me was deep research, agenta coding.

I had sort of priced in, like, it's going to be able to write a couple sentences. And yet, I find myself when I'm on a short text-based platform, not following AI accounts. Like, I'm more likely to go to a fully AI product when I want something that's more like a Wikipedia. page in a deep research report, a utility. But when I'm actually scrolling a feed of short news items and posts and commentary and hot takes, it's not even that I'm like anti-AI. I would never follow someone who is using AI to post. It's like, no, like no one's actually solved that piece of the puzzle.

There's still some human element that's encoded in, you know, 16 words that are hilarious just based on this moment and this experience and this audience. And that's just stuck around a lot longer than I thought it would. Well, that's like the, I don't know how much you guys talk about this on here, but I think like the word of 2026 in AI is going to be taste. Okay. And that's what you're getting at. It's like a model can produce output.

Yeah. But taste is the thing that differentiates good from great, even on modeling, right? Yeah. You can have all the data in the world and inject it into a pre-training run. Yeah. But actually the best labs are the ones that have people with taste that can hand-select golden sets of like, what is the best response for this thing or what's the best image aesthetic for this thing?

I think it's the same with, like, text-based posts. Like, it has to be real time. It has to have a bunch of cultural understanding. I do think models will get really good at that at some point. The thing that I'm most excited about, though, is like AI assistive in the creative process. So, like, if you're an NBA creator, half the stuff that you do is just clipping content

and being like, did you see that Victor Wimbunyama dunk? Half of it is, like, weighing in on it and having an analysis that comes from your point of view and feels native to you. That first half, if we can automate for people and make super easy to do because they have a workflow that's like watch all the NBA games, give me the content that I should be posting,

and then I'll add on my little flavor on top of it. Like, that would be amazing. And also fact, yeah, because timing with this stuff is so important. I mean, we, this is obviously a big part of our business is like if you're getting to stories, you know, later than everyone else, it's just way less, it becomes, goes from,

interesting to not interesting at all. And so I think for creators that want to build an account like that, any type of tool that allows them to be faster in that process is. It is crazy, though. Like you, I don't, you know, have you guys had geo-raimbolt on here? Not yet. I would love to have it on. Okay.

I'm worried he's going to, he's going to docks us. We've given out so many little teasers with images behind the scenes. He, I think, I meet and love. a lot of creators. He is like the most impressive content creator I've ever seen. He's incredible. But I saw an interview with him recently and he's like, oh yeah, when I was like a teenager, I had a Steph Curry fan page. I think it's still up and it had like 50,000 followers. And you meet all these kids that are like in their 20s. They were raised in a version of the world where Instagram was at the center of the universe and they create like fan accounts that get super

huge. And then it's like then what do you do with it? I guess you get really fucking good at geo-guessing. Yeah, I mean, like we have some people on the team that are, you know, super early in their careers. Maybe this is their first job. And when we talk about, and a lot of the work is like selecting content, editing it, you know, distributing it on the right platform. And it feels like very much like manual labor, like you're watching content. And we've stressed continuously that it's actually, it's very important training for

for doing almost anything because it's like developing taste. It's like developing consistency, speed, being organized, being able to get like immediate feedback on the work that you're doing. Like the feedback loop is super tight. And so we've consistently said like, hey, we don't expect you to be doing this in five years. But like for now, take it extremely seriously

because if you can get really good at this one thing, you might be able to apply it in a bunch of other domains. It's kind of crazy. It's like today's mail room basically. No, it really is. We went in the CIA mailroom. When we were doing a tour of the building and we were like, hey, can we see it? And it felt like exactly the mailroom out of it.

Like the same mail room as like, you know, 30 years ago. I was at their event last night for All-Star and they were the most excited I've ever seen agents about TVPN being on the CAA roster. Like ear-to-ear smiles when I brought you guys. Yeah, they're great. That Rainbolt story is funny. The first social media account that I asked. ever got to somewhat of scale was an Instagram for my dog that I got to like 20,000 followers. That's pretty good. I'm going to get in trouble here because I used a bot to automatically follow

anyone who liked the page or leave a like on. No. Well, eventually the bot got shut down, but it already like went up. What's the account? Yeah, you can ban it. I don't care. I don't want to post any more photos to my dog. I was bored at the time. But it was an interesting. thing of like, how do you solve the cold start problem? And I'm wondering about, you know, now there's a lot of platforms where I feel like there's an audition process. You can go on to a completely blank account. And if you bring a banger, some heat, like the algorithm will, audition you with like 500 random people and be like retention was really great. Let's show this to more people. Show this to more people. Is that the way threads is set up right now? We do a bit of that.

Yeah, exactly. It's like you basically take any piece of content on the platform. You sample it to some people and then you very quickly try to understand did this do well in this sample the smaller the sample though the wider the error bars are so you have to keep auditioning yeah yeah um so it's like cycles of auditions cycles of auditions and then um you know some people fail the audition but uh what happens to those posts what happens to those posts they just languish on a server 500 views like yeah no that's what i'm saying like do they just they just don't end up getting served to many people or they have to get served later because no well because we also we have a really tight window of eligibility for recommendations. We want the app to feel very real time. So something

you posted three days ago won't be eligible to be recommended to someone who doesn't follow you in the app. So it all has to happen very, very fast. The bet on threads, this is like a talk track that I give to every creator that's like, what do I do? It's reply to people. Yeah. The feed loves that. The feed kind of loves reply guys. And it's just not just replies though. Like are you driving a conversation. Sure. The best, actually he was at our event yesterday, Draymond Green, number one example. If you want to go look at someone's replies on threads.

I asked him if he searches his name and he's like, no, man, you just show me haters. His feed is just people being like, Draymond is the worst. I hate him on the Warriors and he'll be like, I looked at your profile picture. You should talk to your mom about how ugly you are. It's like, oh my God, Draymond. He gets a lot of joy out of it. That's his brand and his character. And when he does that, it shows the world.

I'm on threads. I'm doing something that's true to me. I think the people who don't do as well are the ones who kind of just, it's not organic. It doesn't feel like them. It doesn't have personality and replies are like a good way to get that out there. What's what's threads relationship like with the rest of the app ecosystem? Early on, you guys open the floodgates, brought a bunch of people in. I'm sure you looked at like retention who's actually staying here.

How do we get more people like this? But like what does that relationship look like? are you like, because I'll see like a meta, a pop up for like meta, uh, ray bands, right, right when I open the app and then maybe I scroll a few times and then there's like some threads content that's pushing me over. Yeah, yeah, yeah, in Instagram. Yeah, I mean, we, we, uh, we promote the app, the content from the app in Facebook and Instagram quite a bit. I mean, I'm sure anybody watching this who uses Instagram has probably seen some of that. So that's, that's the main point of integration that we have. When we built threads, there was a bunch of like

foundational decisions that we had to make. the beginning, which were like, you know, what app binary do we build on top of? Like, we actually just took Instagram and we're like, because on day one of threads, when it was like a very thin app, it was like 300 megs or something in the app store, because we just had the IG code base. I mean, we've like made it more efficient from that. But it's like what namespace do you use? Like we mirror the Instagram namespace.

You can have a threads only account, but you can only have a threads only account that isn't a name that's on Instagram. You know, like we made it one. So there's a lot of natural. tie-ins to Instagram because of that. We were backed by them effectively in the beginning. But now, like, a lot of our users come from that integration in the Facebook app. We, and you can sign up for threads from Facebook without an Instagram account.

Like, we're trying to make it stand on its own independent of the IG history without, like, disrespecting the fact that that's, like, the best marketing channel you could ever ask for. So we try to own set up. Talk about collabs. I was scrolling this Instagram creator. Have you ever seen the Let Him Cook guy? Have you seen this guy? No. He does this incredible thing where he'll bring the video in.

He'll be like, you can't cook an F1 driver. And this song plays and he goes in and it transitions from like a tire to the road. And it's like this amazing editor. And I was scrolling and I just, and one of them is just him doing the same like motion graphics effect, this amazing edit. And Adam is Sari sitting there with him. And it's very clear that he like collabbed on this and they have shared namespace on them. and I've seen there's a bunch of different ways, but that feels like an interesting, you know,

it's very popular in podcasting. You have a big guest on. A bunch of their audience comes to yours. What does that look like on threads for someone who's trying to sort of network their way to broad account growth? Yep. We do a bunch of this.

I'll give you a couple examples. Like yesterday I actually put up, it's like kind of mortifying video because I did a training session with Lethal Shooter, the NBA shooting coach. Cool, yeah. I thought I was going to do. to crush, by the way. I was like, I walked out the video. I walked down to this basketball court.

I was like, I am going to be the greatest shooter of all time. And it was so humbling and horrible. But like we did it. We did that thing. He was amazing. But that's like, you know, I put some content up. He'll repost it. He has a bunch of fans from Instagram that are on threads. And like, he's actually really good on threads. He's, um, his mentality is very like, oh my God, there were so many one-liners. who's just screaming at me the whole time. But it's very much like, you can only be great at a thing like shooting a basketball if you are centered as a human.

And he posts like motivational quotes like that on threads and stuff and people love it. So that's one thing where it's like, not only is he doing well on the platform, but I do something with him and show everybody there. Like this is big. We also then have a bunch of like more homegrown talent where it's less like take someone who's huge on IG

and bring them to threads. Yeah. There's a guy. There's always been alpha just getting, being one of the first. The first. 10 million users, but then taking it more seriously than anyone else. That's this guy, yo rush on threads.

He's like, they call him the mayor of NBA threads. He was just like at home. He's an NBA fan. Threads came out and he just started posting and people liked it. And like he was with us yesterday at this thing we did in L.A. Him and his wife are here for the weekend. They're coming to do a bunch of events with us. Like, you know, we want people like that to, I think it's really important if you

have a content app to have homegrown talent too. You can't just be transitioning people from other places. Like you need to show everyone. on the app that you could be successful here too if you just do the right things and reach the right audience. What's your philosophy around creator payouts? How do you think creator payouts on other platforms have worked well?

Clearly they work well on YouTube. Our point of view is making a great YouTube video takes an insane amount of work. It's in the incentive of the YouTube platform to pay people so they can quit their job or put more resources to it or buy gear, all these things where I haven't felt like creator payouts have made X a better platform at all because it incentivizes people to just like churn out kind of like low quality content that might rage bait people into engaging

but isn't actually making the platform better. Yeah. I have pretty strong opinions on this and a bunch of priors. I agree with the way that you just position that. The way that at least right now I'm thinking about this on threads is like I want to be in the business of directing traffic to the places where you make money in, like, a sustainable way. I don't know. We've tried different versions of this at Meta. Access obviously had their version. I've never seen in an app like threads a sustainable creator payout product work well over time.

YouTube works well. And then you have like the substacks and patrons of the world that are like more subscription-based. Podcasts, like getting subscribers and traffic to your podcast is a thing that you can monetize and, you know, run ads and have sponsors. like you guys do. And so we have been focused on that by, you know, we did this like pretty simple thing where we worked with Spotify to do like rich previews of podcasts. You can also pin your podcast link on your profile.

I would love to do stuff like then. You can subscribe on Spotify from the feed and things like that. But the whole. Yeah, the reason that that philosophy like I think is smart is that's what we're seeing across the entire internet. Because you're going to have different ways to make money, different creators will. You can't just get paid for views because not every view is equal.

Otherwise, like, the kid running, you know, there's kids running meme accounts that are posting, like, funny, maybe controversial, edgy content on Instagram, getting, like, a billion views a year, but it actually has zero value. It's like the videos of the kids that take the fake turds and put them in, like, Burger King bathrooms. Oh, my God. I'm like, what are we doing here, guys? Now you all, all the viewers will have to look that up. It's like the most horrible content. You're right. The incentive there is like, how do I do something funny?

I actually, like, I'm very, that whole, like, prank video space to me is just this, like, insane. Like, I guess you could have imagined it coming 10 years ago, but whenever I see one, I'm like, how did we get here? I think it blew up on YouTube, like, years ago. Yeah, prank videos were the, that was the original. I used to have a few prank videos, you know, my holster if I go to a friend's house and say, let's pull up YouTube. Let's go. But going back to it, it's like, yeah, if you can be a place that helps people have an audience and build a business, that is what every successful content creator has done. They're not just relying on views, even for us on X with creator payouts, you know, generating hundreds of millions of views in the last year.

Like, the X creator payout is like such a rounding error that I wouldn't be mad if it went away, right? I think it's, you end up, it's funny, because when you talk. to talk to people, it's like there's people like you guys who hundreds of millions of views, rounding error, you want to be mad if it goes away. The people that tend to care the most about it are the ones who get paid out like $80 a year. And I do, I actually sympathize with that because it's like if this is a side hustle for you, to your point before, you want to buy a new camera, you want better gear, like finding ways to get people enough money to sustain the thing that they're doing and give themselves more attempts to make it big or build a bigger

audience, I think is great. We just want to do that by pushing people to the places where you're monetizing more efficiently. Sure. Yeah. Are you seeing SponCon happen natively on the platform, like on Instagram where, I mean, I see a ton of influencers who are like, get ready with me, and this outfit's brought to you by the app or something. And that's been a backbone for a whole variety. I have a friend who's been working with figs for a long time, and she'll talk about figs clothing, and it works really well on Instagram. Have you seen that flywheel start on threads? It's interesting that you asked that. I mean, we have had some of these, I would say it's more like memes that everyone in the app participates in for a few days, but not like categories like that.

I mean, like, get ready with me. It's like Alex Earle was dancing with the stars because she did get ready with me videos five years ago. That's like, I don't think we've seen equivalents on threads, but we had this. Do you guys know that like, sorry, I'm just bringing up memes on the show, but like, hey. That's what we do. You started with a meme. Do you guys know the, I hate gay Halloween. No.

That was like big on threads. Okay. Wait, I actually do think I saw one thing. It was just people being like, you know, there was actually one that I laughed at the other day. It's like, hey, gay Halloween, what do you mean? I'm like, you're going as the grass from the bad by half time show or whatever.

You know, like there was like two days. All these like very obscure like niche references. I think that's what threads is good at is like the niche humor. That is a great Halloween outfit. We were, during the Super Bowl, I was just sitting there zooming in on on the grass. Because you could see there was like coordinators. that would be like right up in the face of the grass, just like yelling them like,

get to the right, right. I thought they were going to do something, but then I found out it was because they had limitations on the number of carts. You can roll out onto the field. So they had to add people. The way that they were able to do the set was to have humans walk on and off

because there's like a restriction on the number of carts that we put on the field. I like it. Nature finds a way. It's amazing. How big is the team? How do you think about scaling the team? What does it look like to go to Zok and say?

I need a 500 more. Yeah, I've never made that ask. We're relatively small compared to the other apps inside meta, like by orders of magnitude. But we are growing this year. We're investing in like two things. One is like just relevance, making the content ecosystem better and stronger and the personalization of the feed. The Dear Algo thing is like a part of that.

And then the other one is just like making sure that we can grow sustainably. Like these promotions that we have in Facebook and Instagram are awesome. I think that we will have them for a very long time. But we also want to make sure that people are turning to threads without having to see a promotion. There's a bunch of just like basic work to do well there that I think other companies have done really well over the years. Even just like SEO and getting yourself like if someone searches Super Bowl halftime show, I want threads content to come up on a search engine there. And so those are the two categories where we're growing, but it's still a pretty small team. Yeah.

I want to know more about Dear Algo. and I want to share my experience. You can tell me if this is just me being weird or if this is actually a trend. There was a time when a social network would be all things to all people. So if I liked sports and tech and cars, I would get all three of those sort of mashed together.

I could maybe go into certain communities. Now I feel like I have different apps and different platforms. Like for real-time tech news, I go to X, but then if I'm watching a video essay or a car review, that's on YouTube. My Instagram is much more timely, much more funny, more reels. And then my podcast player is for like the conversations that aren't very visual. And so I have all these different platforms.

And I'm wondering about like, is there, is there a future where someone's using threads for one interest of theirs? And then Instagram for a different interest of theirs. And there's kind of two separate communities. And they're sort of intentionally steering it that way. I think it's possible. Like, there is kind of to my point before about what content works well in the app and not. Like, I would say in a category as broad as sports, you probably always will have two types of content. It's like, show me the super cut of like Kenneth Walker in the Super Bowl and then show me, you know,

Mina Kimes talking about his free agency or something like that. Like, Threads is going to be really good at the ladder. I think Instagram will be really good at the former. one of the ways that a lot of these apps think about how to get to the point that you just talked about, which is like, how can we get the user to tell us what they want to see without asking them? So that's like, what do you search for? What do you dwell on? What do you share with other people?

What do you like? All these signals. And like, our job is to figure out which signals are signal and which ones are noise. I actually think it's possible for an app like threads to be multiple things for people, but probably not everything. Yeah, yeah. I don't want threads to be a video app. That wouldn't make sense. We have like a lot of investment in short form video at Instagram and on Facebook.

And even like the political infighting. You've been like that's something we've not really into it. I don't need to do that. But I think that there's a space for the text format that's really big. And my biggest takeaway from the last few years of threads, which when we first started it, I think we very much saw growing the app as we need to pull people from other services to grow. I've been really pleasantly surprised at how we've grown.

the category. There's a lot of people that use threads that never used X or similar platform in the past. And so that's the thing that I've been really focused on is like, why is that happening? What are those people doing? And a lot of it is like these niche interests, dating threads is really big actually. It's like singles go on threads and make a post and put it into the dating threads community and they're like, hey, I'm looking for love. But then we also get book threads. There's like a crocheting community. I tend to spend my time on sports and pop culture and stuff like that. but there are these very niche communities that we actually built like a community's product so that you can find those people and kind of make your app about that.

So how does Deer Algo work? Is it plain text or buttons? Yeah. How can someone actually custom? We just like we just sort of built it off of what we, so there was this viral moment like a year ago where people were writing, Dear Algo, show me more tech content or whatever. Or Deer Algo introduced me to people who are into these things. And that, I mean, to say that it didn't work would maybe be incorrect, but it's like the system

wasn't architected for that to be like a strong signal. Totally. Of course, if you write about a thing and you like a bunch of content about it, maybe the algorithm will pick up, you want to see more of that. But it wasn't working with like high intent. So now if you just go type Deer Algo into a post on threads, it like tags itself blue. You can say, you know, the other day, actually because I'm a Patriots fan,

I was like, stop showing me NFL content. And for three days, I got nothing about the NFL in my feet. It was amazing. Like, I don't even know if the Seahawks parade happened. It didn't cross my timeline. But then you can also say, show me more of something. So actually, I think I made one the other day.

That was like, show me more real grass people from the halftime show, not AI-generated ones. And that worked. The reason why we're able to do it is because content understanding and topic trees have just gotten so much better with LLMs.

Like five years ago, we might have had you as dog sports cars. Now it's like this specific model of this car, which is associated with this brand, which is made in this country. A million parameters that no human can understand, but it's way better. Just like ad targeting. You will get like a rejection.

If you say like show me more murder, we'll probably like, we can't do that. If you say show me more of something that's like so niche that we don't have enough content, we'll tell you like, hey, there's not enough content for this. And then we actually tell you in the feed when you see something that's because of the request that you made, it'll be like marked as such so that you know what you're getting more. It's fun. You guys should try it. Yeah, I love it.

Yeah, I've been waiting for the plain text interface to the... Jordy could make his first threads post today, maybe, by trying it. I will do that. I haven't done one. No. I got to, all right, I'm going to get there. I don't mean to shame you on the live street. That's a cross-vose thing.

I'll be on there. At Jordy Hayes on threads. Find me there. Actually, I made my first ex post in three years today. Yeah. Because you guys tagged me on there. And I wanted to route people to friends. There you go.

Always, always be selling. Yeah, always be selling. The app, the app, the app looks absolutely beautiful. Thank you. Number three in the app store too. I love the polish. Anywhere from two to three, I want to get that number one. Do you, do you, like, wake up and check the app store charts?

That is not a thing I do. I wake up and I look at like six dashboards. Also, I mean, just to be clear, in the- Well, it might help if you put a big monitor in the office that just has your app store position. Yeah, that's usually when you put things up like that, it tends to like, yeah. That's a great tip. I'm sure my team will really enjoy that. Anyway, thank you, so.

Yeah. me. Thank you. Thanks so much. We'll talk to you soon. You heard Martin talk about it, but now you're going to hear me talk about it. 11 labs, build intelligent real-time conversational agents, reimagine human technology interaction with 11 labs. And I'm also going to tell you about fin.a.I, the number one AI agent for customer service. If you want AI to handle your customer support, go to fin.a.i. And up next. Next, Alex Buzari. He's the co-founder and CEO of DDN. He's in the Maurice room waiting room and now he's in the TV pinel. What's happening? How are you doing, Alex?

Good to meet you. Hey, how are you guys doing? We're doing fantastic. I expected, we expected you to suit, Magas. Yes, the outfit is fantastic. I certainly have. What's the background on the, on the suit? Have you always been to fashion? Is it particularly... I've always been into fashion. I'm sure you guys appreciate it because you're definitely not like everybody else. Yes, yes. Well, now, we'll hit you up after the show for some Taylor recommendations. Uh, but, uh, very, very, very, very much. Very excited to meet. Yeah. Well, first time on the show, please give us an introduction.

So CEO co-founder of DDN, DDN solves all the data problems associated with AI implementation. Or enterprises, sovereign, so nations, countries, large-scale deployments, Nvidia users internally for everything they do. Elon, large, Brock, on 200,000 GPUs is powered by DDN, hundreds and hundreds of deployments like that. So that's what we solve the problems of AI and we help organizations monetize AI because it's great to invest, but if you don't monetize, what's the point? What's your background? How did you get into this business? How long ago? Been in technology forever. Born in France, came to the U.S. in my early 20s, went to school

here, loved it, and then just did a bunch of technology companies. This one, my partner, I started about 20-some years ago. Wow. At the time, we're solving the problems of high- success. So high-performance computing is basically government labs, academia, trying to solve complex,

technology problems. I mean, those guys were our customers. We ended up powering 60 out of the 100 fastest supercomputers in the world in every country, basically, three-letter agencies, Department of Defense, Department of Energy.

And then this little thing called AI started to happen. And so, Nvidia came to us and tapped us on the shoulder. And they said, well, we're trying to stand up a reference architecture. That was eight years ago. And they said, we have all the pieces. We don't have the data. And so we became part of that architecture. InVedia became our customer.

And, you know, here we are eight years later. AI is booming. As you know, as you see. I mean, it's expanding, exploding in every aspect, every industry. And that's been the journey. And the journey is super exciting. Walk us through, obviously, you're quite bullish on AI and implementing it across every possible industry.

But how did you personally kind of process the different evolutions and paradigms from the transformer architecture to all the different steps that we've had since, then. Sure, sure. And that's a great question. I mean, look, when Nvidia came to us eight years ago, I mean, honestly, I don't think anybody realized how quickly it was going to grow and evolve.

And so we walked away from that first meeting saying, well, we need to develop a radically different architecture. And that architecture for AI to be successful needs to connect edge. So edge devices, think of that as autonomous cars. Think of it as sensor data. robots in factories that move things around. So it has to connect the edge to the data center

where the data is getting processed, analyzed. That's where a lot of the Nvidia infrastructure is being deployed, and then multi-cloud. And so the evolution really was, as Nvidia and other companies have been deploying faster and faster GPUs, the resulting factor is that there's a scarcity in the number of GPUs available in the world,

scarcity in power. There's not enough power in the world, and there's not enough data center footprint in the world. So our technology has basically evolved to adapt to these limitations. People are spending, organizations are spending millions, tens of millions, hundreds of millions. We have customers who are spending tens of billions in building out infrastructure. Well, if that infrastructure is not productive and is not delivering value, then it's wasted, and the ROI just doesn't work out. So we've evolved our software stack, call it the data plane, to ensure that these infrastructures are running in the most effective way possible, irrespective of what power shortages might be or data center footprint shortages might be or the number of GPUs that are available. So that's really been our evolution.

It's been, you know, lock and step. A lot of it guided by Nvidia. I mean, our engineers and their engineers interact on a daily basis across all ads. aspects of NVIDIA's engineering. And the primary problem is, how do you make it easier for enterprises to implement AI in their environment in a non-disruptive way? I mean, in essence, you're dealing with CIOs who are like, well, I don't want to have any glitches, because if I have glitches, I'm going to get fired.

And line of business people who are saying, hey, I want to benefit from AI in developing better, more compelling, more competitive products and services. So you have this tension, which means you have to make it. easy for them to deploy in their environment. You have to make it risk-free. And so with NVIDIA and others, we've developed these integrated solutions that are industry-specific that can be deployed and make it easy for enterprises to bring in AI into their environment and benefit from it. So it's really that. I think we're moving from an early adopter phase, which is a handful of organizations are benefiting from AI, you know, the hypers, the,

the chat GPTs of the world, the grocs of the world, into one where the industrialization of AI is underway. And I think that's one of the most compelling things that is happening out there. But for that to take place, easy, easy. The latest earning cycle, I think everyone was shocked by some of the CAPEX numbers that were coming out from the hyperscalers. Was that surprising to you? Not really, because again, we're very,

very close to the center of the universe, which is Jensen. And if you look at it, I mean, the Cappex might see. Yeah, Jensen, Jensen was saying, like in Q4 of last year, he was throwing out numbers that implied that the hyperscalers would be raising their their Cappex projections massively. So it shouldn't have been that much of a surprise. But when Jensen was first saying it, he's obviously a salesman. And like, you know, it felt, of course, it feels a lot more real once they're throwing out, you know. Well, I mean, look, if you think about it, the hyperscalors have a software suite which they're monetizing across a very broad population, hundreds of millions of users,

billions of users. And so you look at that capex and you align it with how much they're charging and how sticky the offering is, you just got to do it. Because if you don't, one hyperscaler will emerge, I think, as a leader. I mean, just like the Google search engine, there will be one leader, and then there will be a number of others who will have market share, but they won't be the leading market provider. And I think everybody has come to the conclusion that you have to invest very, very heavily

because without massive infrastructure deployments, you cannot train the model at the level of complexity that is required, at the real-time elements that are required in order to deliver outcomes to organizations and consumers. So I think it's really that. Everybody is racing to be the market share leader in this newly created space. I mean, Google is doing it. OCI is doing it.

Microsoft is doing it. Meta is doing it. There will be one leader. Getting a little bit more specific, software engineers have done an excellent job creating and adopting a bunch of AI tools. What are maybe some under-discussed areas that you're seeing AI adopted and real usage growth that the kind of broader tech community is less focused on because these are maybe companies or industries that aren't typically at the center of the conversation.

Sure. I mean, look, the places where we see significant traction, financial services, because the ROI pencils out beautifully. I mean, it's a no-brainer. The better your models are, the more complex you can run those models. The faster you can get outcomes, the more differentiation you create. so the better return to your shareholders. And so that's like companies that are doing trading or?

Oh, think hedge funds, high frequency traders. We have some very large customers in that space. Those are very technical organizations. Typically, the people in these organizations have come from the world of high performance computing so they understand the benefits of it. And so, yeah, that's one bucket, which I think will continue to expand. Secondary is life sciences. Anything having to do with drug discovery, bringing a new drug to market, genomics.

The costs associated with bringing a new drug to market are staggering. It's billions of dollars. It's years and years of development. And so in the end, if you find yourself with a drug which is being rejected by the FDA, well, you have a problem. So AI gives them the ability to better triangulate what should an optimized drug be to cure a specific disease. and how do you increase the likelihood of that drug getting accepted?

So the cost will still be extreme because of animal studies, human trials, all the different steps, but we could enter a world where you have a higher success rate for drugs that are entering those. Exactly. I mean, it's higher success rate. It's better predictability. And it's also as the omniverse, digital twin starts to happen. I mean, the ability to basically run what if scenario.

that you don't have to do in the real world. So if you're bringing a new drug to market and you're saying, well, there's like eight different ways I could do this, but I'm not sure which one is going to be the best outcome. You run simulation in the omniverse with synthetic data, and then the responses come back saying, well, if you combine parts of the first one

and the third one and the fifth one, combine them together, likelihood of success will be higher, the drug will be better. So I think increasingly we're seeing that the omniverse and synthetic data is coming into the mix. Autonomous driving clearly, because, well, if you have driverless cars on the road, you have to collect data in real time.

This is cameras, audio, this, that, the other. You have to continuously reprocess the model at value loss scale. So many car manufacturers are our customers in that space. Manufacturing is starting to happen. Again, factory floor automation, retail, just how do you optimize inventory in various types of retail organizations? And then the other really big ones is sovereign AI. I think with what the Trump administration has done, they've created lots of concerns worldwide in terms of autonomy and risk. And the U.S. is no longer there to just bankroll you.

so you have to protect yourselves in some ways. So we're involved in lots of... Have you spent much time in France over the last few years? There was obviously a little tiff between the Western, the U.S. tech community and Macron last week around. He came out with an announcement that was kind of intentionally misinterpreted a little bit. I heard it, Jordan. Maybe by me.

But he was kind of putting out charts of showing foreign investment. And we've heard that a number of labs have been excited about the energy availability in France and look to capitalize on that, but kind of just kept running into different blockers kind of from a regulatory standpoint or a general speed standpoint. But what's your kind of take on France's progress around sovereign AI and just kind of catalyzing the industry locally? So look, I mean, one of the organizations in France that's very, very active in the space, is a company called Mistral. So Mistral is our customer.

So we're deployed in their infrastructure. I think, look, at the end of the day, lots of super, super smart people in Europe, in general, France, Germany, UK, all of it. But the scale of investments is just not at the same level as the U.S. and China. So today, it continues to be a two-horse race. I think it's U.S. and China. And the Middle East is starting to deploy massive resources into it. I mean, Kingdom of Saudi Arabia, I mean, we're involved in those infrastructure buildouts,

so sovereign AI. The good thing there is that the cost of energy is very low. Land availability is very, very significant. And there's a desire to really step up what KSA is doing. Likewise in UAE, and well, there are geopolitical tensions between the two, but I think both have aspirations to set themselves up on the world stage as being the third player. Europe will be there, no question, but Europe, I mean, all these countries have centuries of history, and so getting things done quickly, easily, it's not quite there.

Whereas in the Middle East, well, you have one decision maker. And if that decision maker says go, it goes. With infinite resources. I mean, right, trillions of dollars under management in both places. So making a multi-hundred billion dollar investment is nothing. Straightforward. Yeah. When you look at where DDN is spending money on software today,

how do you think that will change over the next five years? covering the SaaSpocalypse. And it seems like a number of great companies today could be comparable to the sort of office equipment and imaging companies of like the 90s where they're, they had the revenues were really high, but then the internet and email and the PDF came along and suddenly people just needed less fax machines and all that kind of thing. Sure. I mean, look, I think the market is overreacting in some ways, as it sometimes does.

So, you know, somebody makes an announcement and then everybody freaks out. Oh, my God, oh my God. This whole industry is going to get commoditized. Everybody is going to go out of business. Service now is going to go out of business. My God, my God. I think you have the forward-thinking organizations in SaaS who are adopting and integrating AI into their offering.

And I think those will do well, provided that they do it at very high velocity. And then you have the ones who will be more traditional in their thinking and in the way they operate and I think those will go by the wayside. I mean, just look at IBM. IBM is a perfect example. Look at Intel. I mean, these are companies that had everything to succeed. I mean, why is it that Nvidia is where they are and Intel is not?

Well, because of the velocity of execution and the ability to adopt something that is happening that is completely different from what it was before was not quite there in the culture of the organization. So I think the way to look at it is which organizations have leaders who are embracing the change, not fighting it. and who are going to integrate it into their portfolio and forge the right alliances. I mean, you could say the same thing about GSIs, Accenture, Deloitte, all of these organizations. I mean, Accenture has, what, 750,000 employees?

How many of those are going to be relevant in this AI-enabled world? Well, Accenture has to completely transform the way they operate and the value that they deliver. Otherwise, it will just go like that. So you need really forward-looking visionary leadership that will force the change. Because if you stay in your comfort zone and you say, oh, I have a great business. Like you said, the top line is steady, the bottom line is fine. You will get whacked. That's just the way it is.

I mean, look, at which AI is operating, it's Jensen speed, is pulling the whole industry out of velocity, which very few can follow, the speed at which he is turning the GPUs, the integration of the software stack and the echo system into the GPU enablement. The open source approach he's taking. I don't know if you saw his CES keynote. He's basically developing turnkey integrated software stacks

and is open sourcing them in order to accelerate adoption industry by industry. I mean, what he did with versus. say it is, it's okay. Here's an open source software stacks. It's kind of the opposite of what Elon was doing at Tesla, which is a closed architecture. It's like I'm opening it up because if I, if I open it up, I will accelerate the adoption of AI by the automotive industry and they will buy more of my GPUs. So I will put 5,000 engineers on this for many, many years and then I will put it out there. I mean, it's a meta, really. What's a salivating adoption?

Yeah, when you think about kind of forecasting and planning for your business, are you more scared of a like chip bottleneck or energy bottleneck when we talk to different? I would also like to put in research idea bottleneck and energy bottleneck. There's sort of four categories that people are worried about progress halting on. And to date, it's been obviously oscillating between chips and energy and energy. Yeah. So look, the ability to process, I mean, think of AI as you have models, you need to train the models, then you need to layer analytics on top of it.

And then the most important part, which creates value, is inferred. From that data, you need to get value. So I always say, we are to data what Nvidia is to compute. And in order to do AI successfully, you need to combine the two together. So what that means is an infrastructure can only deliver benefits if it is cost effective. And in order to accelerate the adoption of AI, you need to make it cost effective. These shortages will continue, I think, for the next several years. And so you have to say, given the limitations that I have, how do I make these AI workloads more effective

and have the ROI pencil out across industries. I mean, I was at Nvidia yesterday, actually, and we're talking about that. How do we accelerate the adoption of AI by enterprises? Well, by packaging turnkey solution that optimize outcomes. How do you make sure that these agentic AI organizations that are providing services, and unfortunately these services are very consumptive of tokens,

which means many of these companies are now upside down. They're losing money because, what they're charging to their customers does not tie into what is costing them because they're relying on AI. So I think the cost reduction and the compression in terms of tokens required to perform a certain task is really where it is. So I think it's a software play. The underlying infrastructure, eventually it will happen. I mean, SSD shortages and end shortages. I mean, we deploy our data plane on top of storage.

SSDs, hard drives, and so on. Well, over the last few months, the cost of SSDs has tripled. So it's significant. And it's not available on top of it. Now, we happen to have an architecture where we can tie into SSDs or hard drives and so on. So our customers are able to do the same,

if not better, with less money. But, I mean, these are issues. But these are transient issues. I think eventually the problem that needs to be solved is how do you ensure that a task that is performed for a consumer or an enterprise is cost-effective for the organization that are delivering that service. And it's really that.

I mean, that's what we're very focused on. That's what our partners are very focused on. That's why many of our interactions with Nvidia revolve around this. How do we make sure that we make it easier to deploy, easier to integrate, and lower the cost, lower the cost of power, lower the cost of building data centers,

compressed the velocity. I mean, look, what Elon did with his data center, and we were involved every step of the way. I mean, he built out the data center in four, four and a half months, which was unheard of. Yeah, when you and the team heard the initial timelines that they were planning around, did you believe it? I said it's completely mad because we had done probably

more than a hundred large data center deployment, and I had never seen it done in less than three years. And when the X team first came to us and said, oh, we're going to do it in four, four and a half months. I said that it's just ludicrous. How is that even possible? But see, the way he did it, instead of hiring people who were experts in building data centers, and all of them would have said, it's impossible, mental block, right? If you've never seen it done in less than three years and somebody tells you four and a half months,

he goes, it's impossible. This is stupid. So what he did is he hired very, very smart people who were very good. at connecting the dock outside of the box, and he said, okay, I want this done in four and a half months, figure out how to do it. And they did it. I mean, we were there with them Christmas, New Year's, weekends, 24-7. I mean, there were mattresses in the hallways. I mean, everybody was sleeping there. It was just working to get it done. And he got it done. Now, it was extremely painful, but he got it done. And so you go, okay, so the new benchmark now is not three years.

it can be done in four, four and a half much. Have any other, have you seen any other, either Neo Labs or Labs or Hyper-Scalers be able to replicate that kind of timeline? Like once he set the bar. China. They are very, very good. I mean, we are so behind.

We are so behind. I mean, they've developed models. I mean, I was looking at what they're doing in data centers. I mean, the first one is the cost metric. I mean, in the U.S., the cost metric is 10 to 15 grand per kilowatt to build the data center. In China, they're able to do it for between a third and a fifth of that. Why can't we do it? Because they're looking at it in a very optimized manner.

What Elon did, he did the first one in four months. Lots of issues. Then he did another three. And lessons learned from the first one. applied to the next three. The fourth one, he's like, OK, I got this. And then he did the next 32. And the Chinese are doing it the same way.

They're not looking at each one of these as a one-off. They're saying, we really have to focus on optimizing, optimizing, optimizing, optimizing, and then we replicate. And that's something we need to do better in the US, for sure, for sure, for sure. How do we lower the cost to build a data center, and how do we compress the time to build a data And China is way ahead of us right now.

They're just way ahead. It's reality. Well, hopefully more Colossus data centers coming online soon. I know, I know, but I mean, it needs to be done. I think the good thing is people are realizing that China is very good at certain things. And instead of saying, well, no, we're just going to ignore them. They say, okay, how do we learn? I mean, I had a meeting with one of our large customers from the Middle East, and we're actually

going through the design architectures from China. looking at how they do it. And we're like, okay, how do we apply that to doing it in the Middle East in a very modular manner? And it's really remarkable. I mean, again, we're not talking about 20, 30 percent cost improvement or timeline compression. It's when you say it's three to five times, the economics associated with that are huge.

Yeah, dramatic. Massive. Yeah, that makes it sense. That's, yeah, wow. Thank you so much for coming on the show. Yeah, really, really enjoy. Appreciate it. Yeah.

We'll have to do this again soon. Great to me, Alex. We'll talk to you soon. Thank you. Thank you. Thank you. Thank you. for your weekend.

Let me tell you about label box. Reinforcement learning environments, voice, robotics, e-vals, and expert human data. Label boxes, the data factory behind the world's leading AI teams. Let me also tell you about vibe.com. We're D2C brands, B2B startups, and AI companies advertise on streaming TV, pick channels, target audiences, and measure sales just like on meta. Up next, we have Brett Adcock. He's the founder and CEO figure.

and about 12 other companies, serial entrepreneur, with a massive release today, Brett. How are you doing? Welcome to the show. How are you doing? Yeah, thanks, guys. Thanks for having me. I think most people will be familiar,

but break it down, where is Figure now and give us the news today? Yeah, so we, well, several months ago, we had unveiled Figure 3 or third-generation humanoid robot. This morning, we actually gave a sneak peek at a future roadmap item we've been working on for about over three years, which is our newest generation hand. Yeah.

I think we've been working on this project basically since the beginning. Our generation one was like this tendon-based hand that we designed in 2022. Sure. Had tons of problems with it. And we've basically been working on trying to reach human, like, how do we approach human parity in terms of hand dexterity and sensors? Yeah. Yeah, does anything else about the robot really even matter if the hands aren't, like, human level capable?

I think, like, one thing we're realizing is, like, more and more if we want to, like, learn from humans. We need to, like, look and do human-like things. So even, like, from a visual perspective, like, having the right kinematics of the hands so that we can do human-like stuff. Meaning, like, if a human folds, like, you know, socks or towels a certain way, like, we need to really understand. how to be able to do that on the robot. And so if we truly want to do like full general purpose work in a home across the whole world at billion unit levels, we have to start approaching like human like level dexterity. There's somebody going for a stroll in the background.

Yeah. What is that? Is that just a walk cycle? Is that scripted? Is that, did it decide? Did the robot independently decide to walk behind you right now? What's going on? Yep.

We literally have hundreds of robots here on our campus. in California, they're everywhere. They're all over the point. Okay. Why jump straight to full dexterity, humanoid form factor? Why not wheels? Why not pincher, grabber, more incremental?

You know, we've seen Amazon acquire that robotics company just to sort of move packages around. There is a logical chain of events that you could do more incrementally, but you're going for the moonshots straight away, it feels like. What informed that decision?

Listen, we have like a very deep respect to trying to do what like human level work in the world without changing the world too much. And if like we as humans built the whole world around our, the way we look and feel like the way we like move around the world. So we like, you know, we use tools, doors like stairs like like so like you know, we've like built the world so that human body can interact with. The ultimate form factor for this is a is a human. You know, like if you start like removing like the ability to like have legs or fingers or the different stuff, you're just going to do less of what humans do in the world. So our view is that we want to go out and basically do everything a human can. That approach is basically a human form in the limit. So we went after the hardest problem here, which is like how do you design human or hardware?

How do we design neural networks now to work on that hardware? It's a really difficult problem, but it's like super tractable. This is a problem that will be solved in our lifetime. In the coming years and decade, we'll see like millions of humanoids out in the world doing all kinds of things. Weird. What is the, what's your bar for to get to the point where you're selling, you're selling a robot that somebody can buy and put in their home and start doing tasks. Because it is, there's a lot of, you know, I'm sure you're testing this stuff constantly and you're able to do think tasks like laundry or moving dishes from a sink, cleaning dishes, etc. And yet the bar is an individual just saying, well, I can just, you know, do this myself.

It's quick. So that's one. You have to overcome that. It has to be so good, so consistent. But like what do you think is a bar? There's obviously companies like 1X that are pushing hard to, you know, get robots into homes. You guys are pushing hard to. Elon is obviously, you know, adapting his Fremont facility, right, to be able to, you know, make these at scale.

But I think everybody's sitting around being like, okay, once I can. hit by on one of these things. Yeah. The, the, the, the, the, the, the, the amount of pressure that the first company that kind of comes out, if you don't count Unitri, but the first American company to come out with a robot, the pressure to actually deliver real value when people are like, hey, I just spent 30 grand on this, 40 grand, 50 grand, the pressure is going to be immense. What is the bar for you?

Yeah. I would say, like, um, the thing that really matters here, uh, in the world, is getting into a spot where you have a humanoid robot that can go off and do like many minutes and then hours and days of work fully autonomously with neural networks. Like, that's the bar. And if I think you, if you look at like who's doing that today, there's not a single group out there that can recreate the video we did two years ago, which is basically we had a figure one just moving Kurek around with a couple hands for like a minute or two.

That was done with neural nets. We were just standing in place. It was uncut. It was a few minutes long. And I haven't seen a single company in the world able to do that today. So we can like pretend that we're like teleoperating robots and be super silly and act like that's going to work. It's not going to work.

We have to deploy neural nets at scale to robots that can be fully general purpose over a long period of time without any human intervention. So for figure, I think we're just like by far in a way the best example of being able to do this today and we're still like, we still have so much more to go in order to be able to put it into a home, like, for days and days and be like extremely useful in that respect. So right now we're able to do like pockets of this work really well. Like we're able to do like clean up the home, do like we can full laundry, we can do dishes. Like this stuff is being done with neural nets fully end to end. And a lot of times like doing it pretty high performance. So my view is like

we will only launch a product here at figure into the home when we're really ready. I think the world will only accept the product in the home, and it's really ready, too. Nobody's going to deal with, like, silly, teleoperating the room in the home, things like this. Yeah, the other thing is, like, we've seen with, we've seen with a number of hardware, like the humane pin. You had the Rabbit R1. Like, people might be willing to try, like, a digital product, like a couple times,

even if a lot of people will try it. If they have a bad experience, they won't come back. Some people might try it again. JetGPZ got better. Whereas with hardware, it really feels like if you launch a hardware product and it doesn't, deliver real utilities. Yeah, it basically kills the company. Yeah.

So the bar is just so high. So yeah, timelines, you guys have the benefit of being private, even though you have a valuation, somewhere around the range of Ford. You have time to figure this stuff out. What are the timelines that you're setting internally? What are you rallying the team around? Yeah, we're working kind of two past. How do we ship robots in the industrial workforce as fast as possible?

Attract is pedal to the metal, like every single day. We have many different customers there fully signed up, ready to go, and we're excited to, you know, we had robots at BMW last year. We have like more robots going into commercial customers this year. The second is we want to solve a general purpose robot, like solve general robotics and a home. And the best, one of our top goals is like be able to drop a robot of ours. into an unseen home this year and do like full general purpose end-to-end work.

And it's extremely tough. I think we can go do it. But we're working like day and I to go get there. And yeah, it's a it's like it's basically how do we design. It's the closest thing like AGI for like for physical world, right? Like how do we get something that can like have common sense in a home that you can talk with, it can understand things? Maybe you can teach us something on the fly and you can watch.

you and then ultimately to be able to carry out those tasks at high performance all throughout the day. So my hope is we can make material progress on this this year. Our goal is like working day and night to try to solve this. To the extent we can hit this goal of like being able to do full end-to-end work, there's other barriers of like privacy and safety and other things that are really hard that we're also parallelizing. But my hope is by the end of this year we're making considerable progress towards this,

being able to show like some some crazy insane things with these robots in you know in these type of environments but this is like this is a separate track to like the commercial side like we're already out like and we've already been out being able to do this we're going to go out even larger this year in 2026 they'll deploy robots at scale this is important for us to get like a real operational readiness like how do we make sure a robot like how do we make sure we can run robots at scale really well here figure yeah how yeah and it's all i mean it's it's it's a like much more straightforward to have a robot in a setting where you have trained professionals, probably wearing hard hats that can be kind of monitoring the robots from far away.

You're not dealing with the safety risk of like a robot falling on a dog or on a kid or any of the other challenges in the home. What's your timeline to a robot humanoid being able to bench two plates? Is that an interesting problem to solve? It's the only problem that's interesting to me. For us, we're very fascinated on when that'll happen. Yeah. Is it bench or squat?

What do we want to do here? I mean, squat is probably the overall compound lift squat. I feel like is pretty... A thousand pound club, ideally, but we'll take just bench press if that's what you got. I mean, we should, if we can bench press that, we should be worth at least twice afford, right? Okay, yeah. Yeah, yeah. Yeah, I agree.

Just for that. The tickets to the bodybuilding competition. No, but I feel like, I feel like even as silly as that sounds, you know. It's an interesting benchmark, yeah. I think the over in China, they're doing Robot Olympics. They're doing marathons. They're doing all sorts of stuff. Okay.

Can we be real for a minute on all this stuff? Yes. Like, let's just like, let's, let's be real serious. What really matters, I think, for us as humans is we look at the distribution of what humans do, it's like useful. And we try to do as much of that as possible. Yeah. These things where we run like marathons or we do backflips or we do karate

moves or we like try to deadlift 300 pounds they're not in the main part or the fat part of the distribution yeah they don't matter and if you really want to size for those and do those you're going to build a really expensive and heavy and unsafe robot that's hard to manufacture yeah you're going to build like a super duty truck and like nobody like no people want the 10 20 000 humanoid that can do general purpose work right that's what we want so if you're trying to size a robot to do those kind of things like silly things i think of like those like gymnastics and other stuff, you're going to build a very specialized robot that can do a very small percentage of what normal humans do every single day.

So our goal is to build a general purpose robot to do a majority of what humans can do out there. We want to do like laundry and dishes and be a companion. I want to ship robots at skill and a billion level into the workforce to do logistics and health care and build buildings and build data centers. Like that's the stuff we want to do. I don't need to do backflips to do any of that work. I want other robots building other robots.

So I don't know. I mean, I think you look at the silly stuff out there. It's not only not important for the roadmap. It makes the hardware extremely like heavy and hard and expensive. And all that causes more problems. So like none of that matters in our mind. I figure we, you know, every once in a while we'll put a robot on a DJ stage with dead mouse and stuff for fun. But like we're definitely not trying to design a robot to be great at that.

Yeah. We want to be great at like the things I do every day and you guys probably do every day. I mean, you guys are probably deadlifting 300 pounds. But like, at least for me every day, I'm trying to like, you know, just do normal, like normal practical stuff that billions of people today are doing that we can help offset. How do you, how do you think, you know, let's say we get the iPhone moment for humanoids, hopefully in the next few years and that it's a, a piece of hardware that has real utility. that a lot of people are buying, how do you think the kind of form factor evolves? Do robots over time look, you know,

do they follow the iPhone path and that they get like thinner, lighter, you know, that kind of thing? Is there, like, what have you been learning so far that maybe people kind of misunderstand about the form factor long term? Yeah, the long term form factor is more and more approaching an average human in terms of like the range of motion,

payloads and speeds and like what you can do. If you're too short or too tall, you're just like you're not in the right habitat for like interacting with a human world that well. So in an extreme case, it's three foot tall. It's like really hard to get most things out of cupboard or get into the, get into the sink or reach over a table. They actually become really practically hard to go do. So it's going to be like an average human size overall. I think we're in like the pre.

I'll make an argument here that we're in the pre iPhone stage. We're in the flip phone stage for for humanoids. And I think we know it's better than anybody. We've been building them like crazy. We have our third generation out in three years. We've walked three generations in three years. I think what you'll see here is that we're trying to find this ideal product, like product fit, like long term where that's headed.

And we're like learning every year where that's going. It certainly means being more human-like in our mind. So we can unlock more percentage of this distribution we just talked about earlier. I'll make a statement that's pretty bold is that when you look at like figure one to figure two to figure three, we've had to like step up in performance. and they're just better and better every year. When we had to figure four here, it'll be the largest step that we've ever made by like, but by a long shot.

It'll be the first time that we feel that we probably hit like iPhone one level humanoid. We're just like this is the right place to be in. And then this will like, this will, you know, this will go extremely far at a point where it saturates at some point in the future, you know, maybe 10 more years. But we feel like relatively early. It's an extremely difficult piece of technology. It's obviously early in this. So it's got to be like earlier than phones, right?

We're not like, we're not there yet. So, but I think the iPhone one moment will happen with figure four and it'll just be, it's just an unbelievable machine. And I, uh, I never would have, uh, suspected we'd be able to make that big of a move. You know, in figure three ship, I'm like, this is it. This is like the best it'll ever get. And then, you know, the more we learned and ran it and the more we develop neural nets here with Helix, the more we really understood better about like what the hardware should

like should look like and be like. And the more we got folks in the room together with us and said, how do we radically redesign the head, the hands, the kinematic systems, like all of it from scratch. And I think you're going to see something. I mean, this stuff is just going to get crazier and crazier in capabilities. What are your goals around consistency? So for example, a robot that can unload my dishwasher, if one out of a hundred times, it, it, it, like, breaks a plate into, you know,

200 pieces. Maybe that's not that big of a deal if it can, like, you know, pick them all up easily and I'm not home and I don't see that, you know,

you're exploding the plate. But what, what level of, like, consistency do you guys need to get to before you're, you'd be at a point where, you know,

you can sell one of these things. I would say, like, we probably need something pretty high. I think it would suck pretty bad if you're at my house and drop, like,

the number one mom, coffee cup. You're getting your ass booted, right? Like, I don't like, I think you got to be, especially around safety and stuff, like, this seems to be super high performance. So we like, we watch folks that are trying to like teleoperate and ship early when the product doesn't even work. And it's just, it's just silly.

They're all going to die. You got to ship something really high quality. And that, that is just like a super hard thing to do. So I figure we'll ship into the home where we're ready. We're not ready right now. We're trying to get, like, you know, I'm here until midnight every night, seven days a try to get more ready with my team. I hope we hit some place

where we're getting really, really close this year is what I really hope. How are you processing? But you're right. Yeah. How are you pressing the Waymo story of teleop? Because I was completely on board with the Elon pitch for straight shot to FSD,

collect a bunch of data from the cars that are on the road, train the big neural network, and FSD. I mean, we talked to Alex Roy, who drove without touching the steering wheel all away from L.A. to New York. Like, it clearly works. At the same time,

a lot of people in San Francisco hop into Waymo and they're like, that works too. And so it was a bit of a narrative violation where a lot of people were saying like the Waymo, teleop model will never scale. And it feels like it's scaling. So how is it is there a world where both approaches work or are they fundamentally like different industries? I think what I'm seeing in the space here and it's been like a pretty big shock is like everybody in the humanoid space is just teleoperating the robot with a human in the back and they're putting out a video out and not being very explicit. it. It's very different than this. It'd be like the almost analogy for your Waymo Tesla, like your Waymo's being driven by some dude in Kentucky, not with neural nets. Waymo has neural

networks. The way they went about with the sensor suite to go do it is maybe harder to scale than cameras. The situation happened in human noise is like there's a large percentage of the companies out there that are like have a dude in the back, like that are like teleoperating with the robot in real time. And then like, you know, we're trying, we've done everything we've ever put out publicly has always been with neural nets on like you know stuff we do we've never teleoperated that's you know in that case like those any of those videos um so it's just like the self-driving stuff's not the greatest analogy um you're definitely not going to be able to human teleoperate in people's homes and the latencies will be terrible the data coming back will be terrible train neural nets

it's just not enough data so there's just a bunch of problems with that story and um it's it's not going to work if it would work fast and we can get product market fit and get out earlier we would do it's just like it's just dead end completely you really want to solve like for real neural nets real autonomy from from the get go how big of a bottleneck is data what are you guys doing to solve it like is there hardware breakthroughs that you guys are looking to achieve or or do you feel like the obviously you have the new hand which sounds like it's it's a it's a step up but what are kind of the key bottlenecks we just unveiled helix two about three weeks ago it's a robot that can basically do like fully end-to-end whole body work. We did it in like unloading the dishwasher and

rerunning it. That was basically the whole stack there was basically neural nets basically all the way down the stack. The only reason why it could do that now or like let's say from go from there to do laundry is just a data problem. Like we need just more data to cover the distribution of those new tasks and then the robot can do it at this point. So we feel like the like the longest pull in the prior to like extremely high rate manufacturing is how do we acquire data at like a really high clip. And so we're spending a lot of time on that. That gets you to a point where like, you know, acquiring data through teleoperation is just

not going to even be close. You have to embrace like learning from humans at scale. That's kind of figures like, you know, core models that comes to helix for neural nets. And I would say if we could snap our fingers and have enough of the right data today, you would have a general purpose sci-fi future of robots in our office right now that we'd be able put it anywhere. Like we have it. It's just, we are just extremely data constrained. It's not as simple as just like going out and getting random data. It's got to be the right type of data to match the observations and action spaces of the models well. But we now know what that data is.

We are acquiring that data like crazy here a figure. We'll spend nine figures of capital on acquiring data like this in 2026. So it's a huge focus for us. We think it's, by far in a way the biggest bottleneck to get to general robotics. Yeah. How do you think about China in the context of the race for humanoid robots? Obviously, there's competition from humanoid robot makers there, but there's also a bunch of great parts suppliers at all levels of the supply chain that might be useful to build American humanoid robotics companies. How does that puzzle play out? I mean, listen, I think like as it raised the competition, I think what's extremely important is seeing robots that can do like human-like work with neural networks that's useful. We haven't seen any of that out of China today.

They really don't have any hands. Good on hardware, but they're still behind on software. Well, I would say like you probably don't have good enough hardware if you're not able to do the software really well. They don't have enough compute in a lot of cases to run like things like Helix on board. Unitary, for example, has a very tiny computer where you can run like very small reinforcement learning controllers to do like open loop replay. play of stuff. They wouldn't be able to run Helix on a board of hardware like that. They don't have any real human-like hands of five fingers. So you're really missing a couple of big parts of the story. Beyond that, I think they've been great in existing kind of industrial robotics

and existing consumer electronics last several decades. I think those are playing a big part of the ecosystem supply chain for humanoids that are important in some cases. But, you know, But listen, we basically design almost everything internally here at figure. We don't go buy designs from China. So we do it all here internally. And we even manufacture the robots next door in our campus here. We have a figure three robot now coming off the line every three hours. And I think we'll be at every half an hour here in the coming, you know, a few months.

So we're like, you know, like things are coming out at a pretty high clip. But I think today, like if you look at like who's doing the best human-like work, with neural nets over long time horizons. It's not China. And I think we can, I think we feel at least a few years ahead of anything we're seeing out of there. What's compute like you, I mean, you're mentioning you're working so intently on neural nets. You have to train those. Is, is it, are you at a point where a training run is run on a massive cluster? It costs nine figures or something like that, or is it more data collection at this point? And then the actual training run is pretty tight. Yeah, we spent like hundreds of millions of dollars on compute that is, yeah.

There we go. There we go. We spent, yeah, a bunch that went live already. So our next giant like step up is going into April, like first of April. That's for training, Helix models that we're doing here internally, which are quite large. Yeah. In long runs. And then separately, we do all of our inference on board on two GPUs in the torso of the robot.

Sure. So we can run in like cases where we don't have a network. We can run at much faster speeds. and we can put all those models fully on board the system. So all of our robots now are kind of they're running off brains that are all on the robot. So they don't need any outside network to be able to do work. So talk about like input and output. Is the is the network sort of taking in voice input and trying to translate that into plain text actions

that then get transformed into motor actions? What is like the reward function for a humanoid robot? Yeah, we're taking in, we're basically taking in the, like, the, like, the, the, the, the, the, the, the, the instructions through text or speech, like, what should I be doing? Yeah. We're taking in vision from the cameras. Sure. And the current state of the robot, like, where is, like, what is, what is the body doing? What does the sensors look like? And then we're basically processing that on board with Helix 2. Yeah. Helix 2 is in outputting, like, basically, trajectories of where the, like, what the motor should be doing. Sure. Basically, figuring out, like, what do I put torque at in every single joint to produce, you? to move my body in a certain way.

And I think, you know, honestly, one of the hardest problems we've had last two years is two years ago we were basically doing it's like, you know, coffee work and other type of stuff on tabletops. And it was really, it was unbelievable. It was like the first time we're like, man, neural nets on humanoid's work.

We spent the last two years trying to leave the tabletop. How do we walk around when neural nets fully end to end? And it's extremely, it sounds kind of, it sounds like, you know, maybe not the hardest problem in the world.

It was been like some of the hardest problem in the world for us of how do we get the whole body like 30 plus joints all running at like say 200 times a second and doing the right things with camera frames and a prompt coming in and that's what we did with helix 2 unveiled three weeks ago is we had all that done so it's the first time in three and a half years where we feel like we have the right technical stack to actually scale which we didn't have last like several years yeah we were running at bmw last year and we're like man this is going great we're learning a lot but it's not the tech stack i want to scale and we have that now with Helix 2. So we're really excited to hit the gas on, and we're going to hit the gas on

this in 2026. Congratulations. Yeah, it's great to get the update. Yeah, this is awesome. I know you said the bench press is silly and things like that. It's not silly. It's to us. No, it makes perfect sense. Even the bar, even just wrapping out the bar, I'd be pretty excited about. A little bit of a meme. I also think, it's a serious company. It's a serious company, but even serious companies can have fun. Yeah. I'm also looking, I'm looking forward to the moment that, that you get a figure robot surfing at Jaws too. Maybe, maybe, are they waterproof? Can they swim?

Guys, we got, we got it, we got a gym here. Okay. You guys, you guys, you guys swing by. Okay. And let's get, let's get the figure three and you guys in the gym. Let's, let's see, let's see how you guys are all, let's see how you guys. Yeah, we'll figure out the match up. Thank you.

Awesome. Well, have a great rest of your day. Yeah, great to meet you. We'll talk to you soon, br. Cheers. Nice to me, guys. Let me tell you about Graphite. Code review for the age of AI.

Graphite helps teams on GitHub ship higher quality software, fast, fast. I will also tell you about Shopify. Shopify is the comic platform that grows with your business and lets you sell in seconds online, in store, on mobile, on social, on marketplaces, and now with AI agents. There's a company that launched yesterday. Yes, what company? Open cloth or slack. I don't know what it's called.

But they said they launched three hours ago, and they just hit one million ARR just now. So they made $350 in three hours, which is $1 million. of ARR. We've done it. They did it. Final four. They did it. I saw a fake post that was like, meta acquires open cloth for a billion dollars or something. And I really had to fact check it because I was like, this seems so possible in this day and age. I think they have that team with Manis. Yeah, yeah. I think the Manus team is in a good spot to sort of bring some of those functionality to bear. Ring apparently has terminated its partnership with flock. Their Super Bowl ad did not go as plan.

The doorbell company ran an ad during the Super Bowl that's out of a search party feature that uses AI to help locate lost pets. People Uh, quickly, uh,

realize that maybe it could be tracking things other than pets, but anyways, they probably are the, the Super Bowl loser. I was, I was in the end, the worst blowback of any company that I, that I've seen.

Um, this, This Circee post is so good. VCs love to be like, yeah, hedge fund guys may be smarter, but at least I make less money. Good stuff. Goldman Sachs CEO, David Solomon,

we're going to see potentially some very, very large IPOs unprecedented in size this year. He's agreeing that it's about to rain. It's about to rain. Oh, one of the IPOs that could be going out is cohere, Aidan Gomez. We've got to get him on the show.

I'm such a big Aidan Gomez fan. $240 million year set stage for IPO. This is in TechCrunch. Of course, Aidan Gomez, a death grips fan. So you know he's a good time. You know he likes the death games. Size Gong moment. Airbnb, according to SAR and according to Chesky,

has generated $19 billion in cash flow since going public. Not going to vibe code that. Not going to vibe code a house. You're not going to vibe code a basement that you can sleep on. the couch on. I met my co-founders for my first company on Airbnb. I didn't know that. Yeah. Move to Silicon Valley, get into YC, need to find somewhere to stay, was staying with like a friend who was sort of, you know, not doing a startup, so way different lifestyle and searched on a service that was actually the most vibe-coded software, but in 2012,

it was a mash-up between Craigslist and Google Maps, because Craigslist, didn't have a Google Maps feature. So if you were looking for housing, you had to just guess where the places were, insane. So it was called Padmapper. Someone took, they scraped Craigslist and then put it on a Google

map and so you could click and be like, oh, that's near me. That sounds like a good place. But Padmapper, Craigslist had given Padmapper a cease and desist. We don't want you scraping us because, yes what? I mean, every single marketplace created in Silicon Valley was immediately

scraping Craigslist. Totally, totally. They've fought back aggressively. They fought back. And they said, hey, we're going to get around to doing Google Maps on Craigslist. And so Padmapper, get out of here. So when my co-founder and I opened up Padmapper, the only data that was still flowing to Padmapper was Airbnb.

Because Airbnb, of course, is a marketplace. It doesn't matter if someone else is driving traffic. They love that. They were all over SEO. They wanted other people to flow in. So we didn't know this. But our future friends and co-founders had a large place. in Sunnyvale that they had an extra room and they had thrown that on Airbnb.

That showed up on Padmapper. We go over, take a tour. We're like, this place is sick. It was a disaster. All the toilets were broken. They were like, it's like the social network. It's got a pool. It's got a jacuzzi.

We're going to be hanging out. It's going to be the best summer ever. The pool and jacuzzi filled with algae, like truly filled with algae. We spent the entire summer being like, we're supposed. smart guys, we can beat the algae. Let's go get one gallon of bleach. Pour it in. We're like, we're going to need a hundred gallons. Thousands of gallons. It's going to just, we're going to be swimming in bleach. Yeah, no, it was like, there's nothing you could do. And then we were like, there was like a filtration system, but that was super clog. So we were like empty out the filtration system,

try and take it all apart. But like everyone who was like an expert was like, yeah, you just have to drain this and like declare like pool bankruptcy basically. Brutal. Well, New York Post says, have an AI girlfriend or boyfriend. Now there's a bar for you. There's a Hell's Kitchen establishment that has been redesigned for those who have AI partners so they can bring along their phone for romantic evening. Very, very dystopian.

Her moment, but not entirely unsurprising that this bar is pivoting to AI. It's a good day to launch, right? Because 4-0 is deprecated today. Deprecated today. Is it still available? Or did they stop? it at when the clock struck midnight.

I still see it. It's still on my chat. Chipit. Well, it'll be interesting to see what the community does because I did see some posts about people being like, I'm recreating 4-0, I'm fine-tuning some Chinese model. Kimmy could be potentially fine-tuned on 4-0 outputs and paid for and distributed. There are other ways for those folks to get what they want, essentially.

Well, it is Valentine's Day weekend, but before we go, Tyler, we did have a recommendation for you this weekend. You mentioned that you've been seeing a lovely lady, and we thought... This was supposed to be abstract. We thought... This was supposed to be a recommendation for the audience. Yeah, well, there's a girl that maybe... You can't believe you're doing this.

Maybe Tyler likes, and we were just saying, go, surprise, tell her, hey, tomorrow, just have a bag ready. This is so out of pocket. Continue. Have a bag ready. we're going to go do an overnight trip. Yeah. Find a nice hotel.

Nice hotel. Check in. Staycation, basically. You're not getting on a flight. You're just going somewhere local, but somewhere nice. Yeah, somewhere nice. Yeah, the beach. Easy, easy to set up.

Check into the hotel. Yeah. Maybe get her kind of a spa day. Yeah. She goes to the spa. You sit down. And she doesn't know this, but you actually booked her an eight-hour spa, like a full-day thing. You sit down.

Time to lock in. Time to lock in on some cheeky. I have cheeky pine. I have Dorcas, Rio. Yeah, yeah, yeah. You got a lot of stuff. So lock in and then just start getting Guinness on room service. Yes.

21 now. Pint for pint. And go, go every time, every time. Every time AI is mentioned, you take each other. Yeah, or every time John takes a sip, take a sip. Drink a whole beer. Yeah. And you basically are going to have.

Yeah. So she comes back eight hours later from her eight hour spa treatment. And it's like, what were you doing? And you can just catch her up to speed on everything you watch. And I think, I think they really appreciate that. What do you say? You haven't listened to Dwar Keshe Elia? That one hits like a ton of bricks on Valentine's Day.

Ask your spouses, ask your girlfriends, your boyfriends. Have they listened to Ilya on Dwar Keshe? Are there timelines up to date? If not, that's the best Valentine's Day gift. You can get them. I agree. Up to date understanding of what's coming. But we hope you all have a wonderful weekend.

We love you. Yes. Thank you for hanging out with us this week. Yeah. And we will be back Tuesday. Monday is a holiday. It is? We're off.

Yeah. Really? Yeah. Yeah, markets closed. I did not know that. Yeah. I'm learning this for the first time. I'm learning this for the first time.

Yes. We experimented with streaming on holidays and it was. There was not a lot of news. So we'll be back Tuesday. 11 a.m. Pacific. We'll see you then. Nice work, brothers. I'll see you on the next one.