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

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Today is Friday. It's the day before Valentine's Day. 2026.

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That's right.

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We're live from the TVPN Ultradome Temple of technology.

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We should have mentioned Valentine's Day.

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Yeah.

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Earlier two months ago and then again one month ago.

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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 TV Pan Ultradome, the temple of technology, the fortress of finance, the capital of capital. And here's an idea for Valentine's ramp.com this Valentine's Day, show her you care about your future together by putting all of your couple's spending on ramp. Because nothing says I will provide for our family like pulling out a ramp card. Knows you handle business.

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That's right.

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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 $100 billion 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.

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Your job specifically.

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Yeah, it's not looking good for you. No, we're joking.

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Never doom.

1:32

Never doom. There's plenty of opportunity. There are plenty of good potential outcomes. Dario has been on Duar Kesh Patel today and he did something else with Ross Douthit. 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. Be interesting to to follow. The question is what happens to the companies that are currently under pressure with the anthropic narrative? They have to answer this question of is anthropic just gonna steamroll you? What is your real source of strength?

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Not just Anthropic, but the labs. Every YC company that is building an AI native, any company that is, you know, slapping AI native on their website, everyone's going after the opportunity. So we coined a phrase, we decided to coin something. Yes, it was time to coin out.

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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.

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Get on Cisco, head over to cisco dot com. So yeah, we decided. So how do you. What is a phrase that you can generally apply to businesses that can survive and then hopefully thrive during this moment in time?

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Intelligence is too cheap to meter.

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Yeah. So 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 unsloppable. Unsloppable. 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. I was kind of running the numbers.

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It seems possible 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 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. No.

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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 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 moat 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.

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On in the market?

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Yeah, so software has undergone the largest non recessionary 12 month drawdown in over 30 years. That's minus 34% wiping out 2 trillion of market cap from the peak. This is JP Morgan as of a couple days ago. AI threat sparks historic SOFTWARE stock crash Goldman Sachs warns of newspaper like decline.

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I love the newspaper. What's wrong with newspapers?

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Still got it.

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Still got.

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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.

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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. Your love just went public.

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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 are a software company where you're moat was that a competitor would have to spend $1 billion to hire a bunch of software engineers to write millions of lines of code to create a product and you have no other moats, 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.

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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 rederived 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 and the.

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Issue with software, how many I a bunch of designer friends of mine have like a design patent on a specific kind of can they enforce it workflow? Yeah and it's cool to say that you have a patent, but it's not.

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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 Khoshari at Uber about this. You can vibe code a pickup app that you, you know, 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.

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Yeah. Or if a customer, if somebody does pick it up and the customer has a terrible experience, do you have the, do you have the resources to actually make it right?

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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 unclanker. 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.

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Yeah. So becoming unsloppable means two things. First, your business actually has to derive its economic power from a moat that is unsloppable. 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 and you're cooked, tech companies we think of as unsloppable. You have hardware, Nvidia, AMD, Intel, Cisco, Broadcom, SK, Hynix, Western digital data centers. So neoclouds, things like Core Weave, 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 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 Adams. 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 Besant went on CNBC at 4am they brought out the big dog. I haven't been able to catch it yet.

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It was 7:00am Eastern, right?

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Yeah, 4:00am Pacific. Very, very early for us. It's possible to be unsloppable but not an obvious beneficiary. But you'll still likely sell off. As the 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.

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What I was thinking was Nielsen. This company was in one way Nielsen Ratings, Nielsen data. A lot of consumer packaged goods companies use this. I'm sure Matina is looking at how is this Yerba mate 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?

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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.

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That's more for simulating prediction. The bigger one is like, is like.

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I would know Simile would actually want that data to update their models.

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Yeah, like you want to know, okay, 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 even just hey, I need to go to one chain and say I'm working like Target's 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.

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Rock just bought unsloppable.com.

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Quick clip. Before we move on, let me tell you about Applovin. This Valentine's Day use Applovin's Axon AI to serve her hyper targeted ads for exactly the jewelry she wants that way she'll be extra excited when she unwraps presents on the big day.

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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 and to 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. But if you stayed in those names, you would have missed out on generational gains by simply being long PDF. Had to go long PDF. So yeah, if you look at these companies, Panasonic's still massive company and they've obviously adapted over time, but it's a.

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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. TurboPuffer store Vector Embeddings of every romantic moment you've shared in in TurboPuffer so you can do semantic search for that time in Paris and actually find it TurboPuffuffera serverless vector and 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 turbopuffer, 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, 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 the liquidity on their platform, the network effect, the ip, if they have real ip, that's defensible. But just having a big bag of code right now is a little bit of a wait since you're seeing so many companies that are saying, well, our software engineers aren't even writing the code anymore. Yes, we're advancing our products, but so many companies are going all in.

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It's also, it's pretty wild how long it's taken for the public markets to react to this kind of one shotting concept or this zero marginal cost code 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 still a concern, right? Security is still a concern. There's a lot of businesses where the potential risks of using a vibe coded product far outweigh the cost of just paying for the product and having something that's reliable, trustworthy, battle tested.

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Yeah, I mean there's still a ton of questions about how quickly disruption happens, how quickly market structures change. Some things go from monopolies to oligopolies. Some oligopolies 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.

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And say maybe not as good but.

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As 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 will this happen inside companies and they'll be building their own platforms or will they want just a, 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, 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?

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I just have a question, like I'm curious, what do you guys think about this? It's so, it's like if the market is just catching up now to, 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 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 white collar work is you actually can automate a lot of this stuff and only in a year that they're actually going to catch up to this.

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Yeah, that's a good question. The next, next thing.

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Tyler, if I knew the answer, we'd be on Wall Street.

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I think we'll be talking about it over the next couple months. We'll need to see like glimmers of demos.

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Yeah. The one thing is coding. Never felt. Here's the thing. So in coding has been a white. 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, laptop 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 from 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 at some point, these companies? I mean, to date the AI job loss has just been primarily from companies, I would say still processing the Twitter acquisition and saying, hey, we need 50% fewer people here.

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Yeah. This sell off 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, 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 unclankerable 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 ore 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 like 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, 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 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, work in 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 clanker ification narratives. But that will come to a whole host of industries. The question is just on a five year timeline, on a ten 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 the show today. Linear is the system for modern software development. 70% of enterprise workspaces on Linear are using agents. Friday we have a lighter show, but we got some great guests. We got Martin Shkreli coming on to talk about take a little victory lap about the quantum computing thing. Connor Hayes, the head of threads, we hung out with him at Meta Connect. We're very excited to talk to him about the progress Brother Hayes, 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.

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So thank you for that. Finally on the show. It's going to be an interesting one. Clavicular has also been in the news.

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Oh yes, what happened?

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Let's see here. Streamer Braden Peters to Host Boxing Match Billed as Test of Physical Dominance the Valentine's Day livestream pits two figures from the male self improvement Internet against each other. Braden Peters, the live streamer known as Clavicular, announced Thursday that he will host a boxing match on his Kick channel this Saturday evening, February 14th at 7pm 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 Andregenic, 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 Kick affiliated account Kick Champ 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 will be interested to see how the news kind of reacts to the event over the weekend. Certainly this story has gone mainstream.

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You know it's funny that so if you haven't been following these, we've been taking these 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 our joke is like over because it's hit the 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 6 foot 2, he weighs 180 pounds and has a 31 inch waist. His biochromial width, basically the span of the clavicle from which the 20 year old streamer gets his name is 19.5 inches. He has a mid face 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 philtrum 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 livestreamed 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 like you don't even really talk about it. And the chat is confused. This is a very popular, 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 that take it seriously. Stocks, options, bonds, crypto treasuries and more with great customer service.

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Really, really wild time on the Internet.

27:13

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 CO2, valuing Anthropic at 380 billion post money. The round was CO led by D.E. shaw Ventures, Dragoneer, Founders Fund, Iconic and MGX. Lots of folks getting in. A huge part of this raise is Claude Code, says Boris Czerny, who is the creator of Claude Code. 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.

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Kenneth having some humble, humble pie or maybe 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.

28:02

That's a massive business. But Anthropic 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. They're number seven. The consumer app Claude by 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. It's download so like it does so.

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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 the we know they're putting a lot of paid spend behind the anti ads campaign.

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Sure.

29:10

Yeah. So that. That's going to be a factor. Metacritic capital is pretty funny. Back In March of 2024 he said, I continue to be puzzled by Anthropic's $18 billion valuation. And then followed up and said market is so stupid sometimes I have no words. But of course the market, the market was right on this one so far.

29:11

This is.

29:34

You can just see they were. Well, are we sure that he was saying it was overvalued? He could have been saying it's undervalued.

29:34

No, I think he was saying undervalued. Okay. 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 Anthropic so like said has such a low valuation based on.

29:39

The market is almost two years ago.

29:53

Oh, this is. Yeah, this is almost two years ago.

29:56

So.

29:58

Huh.

29:59

I don't actually know.

29:59

I don't know which way Metacritic was going. Cell phone asked Martin Shkreli who's coming.

30:01

On the show and oh, he responded. He said the puzzle meant I didn't understand why it was worth only 18 billion.

30:06

Hmm. So always vague posts so that you can take either direction. You never put 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. It should not exist, says Bruno F. The founder of Magna Digital. $5 billion in tokens managed. Interesting. Yeah.

30:11

What?

30:38

Crazy. Crazy.

30:39

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?

30:40

It's a horse giving money to a car. The car goes and buys a rocket launcher. The car blows up the barn and the horse is sad. And that does feel like an apt analogy.

30:56

It's very brutal. And Anthropic has been all over legacy media.

31:08

Yeah. 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. Sholto Douglas, the anthropic engineer and TVPN guest, told me this. Journalist Gideon Lewis Krauss 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.

31:14

Well, conviction.

31:50

They are early at a $350 billion company and are clearly very optimistic.

31:52

But it is funny to just Daniel, money mogul 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, but it even feels like that is less of a factor than just the overall threat of zero marginal cost software. Yeah.

31:57

Why does Claude have seat based pricing? It's. 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 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 you're.

32:23

But in this case it's not, this is Claude. This is not the API, this is not Claude.

32:49

But when you fire up CLAUDE code, you can integrate your Claude account. And so this essentially gives you credits to write code as well. There's this new meme of if you're going into a tech company, ask what your token budget will be, what's your inference budget? And so these can clearly skyrocket pretty quickly. There's debates over, oh, should I let my employees use the fast mode or the regular mode or Pro? Is the work that they're doing really that valuable if they're spending thousands a month? If they're spending tens of thousands a month, 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 or the actual cost associated with these plans. 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.

32:55

Zach in the chat says we have 150 corporate cloud users purchased by seed. 50% max out in week one because of Excel Token.

34:19

Excel Token use. Yeah, there you go.

34:27

Good data point.

34:29

Let me tell you about Restream One Livestream 30 Plus Destinations. If you want a multistream, go to.

34:30

Restream.Com Dan Primack says working on newsletter may be shorter to list the 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.

34:34

I swear it was early. Yeah, no, this is, 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 we're with AI becoming such a megatrend, 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, CO2's in a bunch, Andreessen's in multiple. I think there's a variety of funds that have built stakes of various sizes in all the different labs.

34:48

And it seems like Josh Kushner is one of the few that has remained deeply loyal.

35:54

Yeah, yeah.

36:01

We do recognize we just had some technical difficulties, but it seems like we're back on. We are so back.

36:04

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. When the picks and shovels phase ends and we're back to building actual products. And Will Menaitis says nightmarish degrees of cope.

36:10

Yeah, Sam was always super bearish on the labs.

36:43

He thought that they would commoditize. Was that what it was? So they wouldn't have Pricing power.

36:47

Effectively. Yeah, effectively. He said, open source models are going to get really good. He was right. They have gotten really good. But I think maybe miss that the labs would turn into product companies and stop just being.

36:51

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 gonna go hunt for the Airbnb, the stripe, the YC companies, the coinbases, all the application layer companies, the Instagrams, the Twitters, all of 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, I'm going to.

37:06

Sit out slow as a seed. Series A, but leans more early. And so by the time you're looking at some of these deals, investing at 5, 10, 20, 30, 40 billion, economics start to be rough.

38:04

Yeah.

38:21

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 buying Bitcoin on the balance sheet. Like, okay, let's do it. There are 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 we'll see. But interesting highlights from the Dario Amade interview on Dwarkesh Patel. Jacob Rintamaki, friend of the show, has a question 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. Dwarkesh says, do you know the Tyler Cowen quote? We never stop talking about economics. Daria says, we never stop talking about economics. So, no, I don't think this field's going to be a monopoly. 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 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 deployment and traction, whether it's on the, 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 OpenAI and Anthropic. They're not allowed to use transformer based architectures anymore. Like we invented it and we patented.

38:21

It and you can't have it's ours.

40:27

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 scales, marshal 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?

40:28

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.

41:07

93% say maintains rate, no cut. So a cut would be a wild card at 7%, 9% for any sort of cut. So strong GDP growth, strong job numbers, 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 apps, servers, databases and more. While Railway automatically takes care of scaling, monitoring and security. Let's play this timeless clip of George Hotz and Nah, we don't believe in stealth.

41:28

I'm a really open guy.

42:06

You are pretty open.

42:07

I mean tell you everything I'm doing. Come on. Here's what I Say, here's what I say. I'm gonna tell you what I'm doing and you could try to compete, but I'll still crush you.

42:08

Nah, we don't believe in stealth. 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, you think the eggs I lay are valuable. 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.

42:17

There's still a lot of secrets. So every business.

42:54

Yes.

42:56

And 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.

42:57

The right and I think there was a huge incentive. I mean going back to the SaaS apocalypse, there was incentive for a long time for companies that wear their moat. We 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 tech 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 your 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 couple financial.

43:18

Meanwhile, over on LinkedIn, George Hotz is posting. Amrit says George Hotz 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 snuck 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 be die, atomized and alone and you won't understand that. You did this yourself. Brutal. Nice little white pill. Nice little Friday white pill.

43:58

He's such a white pillar. Well here's a white pill. Figma figma make isn't your average vibe coating 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?

44:58

Park City?

45:22

Nope. 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.

45:23

They're doing residences.

45:38

They're doing residences. 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 tented pavilions at its Camp Sarica, providing a temporary escape 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.

45:39

Mile from the resort, OTP says. But does it have a bunky?

46:19

Does it have a bunch of bunky beds?

46:22

No.

46:24

Oh, a bunker.

46:25

Bunker.

46:26

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 Sentry. Sentry shows developers what's broken and helps them fix it fast. That's why 150,000 organizations use it to keep their apps working. 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 and a sense of 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 dozen listings above 33 million, though all clustered further north near ski resorts Amangiri. Buyer interest has been strong, he said, particularly among Oman loyalists and North American clients. Additional residential plots priced 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 gonna 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 moats.

46:27

Being an alligator salesman I feel like is unsloppable. I think it could be clankable, yes, still at the moment unsloppable.

48:20

But you gotta build the humanoid robot that can go in the water to wrestle the alligator. And that might be. We'll ask Fred 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, 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 9am an intruder armed burst into the home. He he said. Grant said he came in and we had a tussle. He was formerly known as Alex Da Kid. 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 on security features, installing a guard house, 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 Kelce and Patrick Mahomes.

48:28

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 base the allegedly there were teams that would be permanently based in the US 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.

50:47

Wow.

51:11

And those were the only people that were actually exposed to or exposed, meaning they were like carrying out the different ops.

51:11

Well, the Miami Dolphins player Tua Tagoviola Viola, I might be mispronouncing that said he hired personal security to monitor his house while he's on the road. 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 Coldwell 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. Demic private jet tracking websites have also been an issue. They send chills through the 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, Weiderhorn 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 3 inches solid, 3 inch thick solid steel and has 13 deadbolts. He said even the landscape was designed as a deterrent. Cacti, sour orange trees. There are sour orange trees with 4 inch spikes in concrete planters on the edge of the property and just beyond those trees separating the house and the street, a moat, Gators, a moat. 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 crystallocortzite 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 US Army Corps of Engineer standards. Weiderhorn declined to share 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 $100,001.5 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 Zaha Hadid Architects and with units priced at up to 200 million, has tapped a Washington D.C. based security firm to design the building. Security.

51:18

The $200 million condo.

54:49

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 guards. It's almost like a gated community in one building.

54:51

I'm just, yeah, probably layers of access. Purely thinking you're effectively looking at a $100 million a floor, right? That's crazy. A couple floors, maybe. Maybe a few. It's. It's up there for a condo that is huge.

55:04

The firm is working to integrate technology like biometric access, facial recognition and iris scanning into the design 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 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 Devon, the AI software engineer. Crush your backlog with your personal AI engineering team.

55:20

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.

56:21

Yes.

56:32

Hart said he co founded his own security company Sauron 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 her next door neighbor's home where he tried to push through the front door and he was arrested by police. That could have been us. Hertz 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 in that it includes deterrent strategies, not only 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 gold German Shepherds?

56:32

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, and then you can get up in like the 40, $50,000 range for dog which is hilarious. Dog as much as a car but dogs are typically.

57:23

It's a lot of money, but it's a lot of dogs.

57:53

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 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 and scale 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 Shkreli in the restream waiting room. Let's bring in Martin to the TB min Ultra Martin. Good to see you again.

57:54

How are you doing?

58:25

Technology brothers, how are you?

58:26

We're fantastic. How are you?

58:27

It's great to see you.

58:29

Excellent. Are you gearing up for the weekend? Are you excited?

58:30

Caffeinated, ready to do more work.

58:34

Fantastic.

58:36

Locked in the great lock in. What's your daily caffeine stack? We talked with Huberman about this. You're the natural.

58:36

Are you a microdoser or do you do 400 mil and then coast?

58:42

I do coffee, several coffees and then just like keep taking. Drinking this all day long.

58:48

Is that like a four hour energy? Yeah, five hour energy. Oh wait, how many hours are they? How many hours are they doing these days? Four or five. It's a lot of energy.

58:54

Five.

59:03

Anyway, 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.

59:04

Yeah, so. So I have this new potential product might 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 list of gains or investors and it's very interesting. So I started with Obviously the joke one which is FTX would be up 36 billion today putting in what I guess was $300,000 in any sphere which of course is cursor at a 4.4, you know, million dollar pre money.

59:17

Is that really the pre money? That's still insane because in that era 10 getting, getting into a great company at 4. Like if somebody was pitching you a company at 4, it was almost bearish.

1:00:08

Oh, they're complete outside.

1:00:21

Like yeah, they didn't have the comp. They didn't, they didn't talk to anyone smart that was like hey, you guys are really smart. You can price it at 10, I'm.

1:00:22

Guess, 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 Crunchbase and Pitchbook and stuff, 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 alamed to 300. I think I can look. 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?

1:00:28

Any sphere?

1:01:02

It sounds like zero.

1:01:03

Yeah, it does. When you say any sphere in the context of ftx, it sounds like we're a blockchain company.

1:01:06

Yeah.

1:01:13

To do to build a live multiplayer game. I start to glaze over a little bit.

1:01:13

How many NFTs did any sphere drop? Right.

1:01:19

Anthropic, they'd be 32 billion now I'm sure he saw SPF, 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 OpenAI, but they also did any sphere. So huge, huge gains from Thrive. They were in a couple of later rounds of scale and some other companies. So big, big numbers there. Probably one of the more interesting ones is Reid Hoffman. 50,000. $50 million. First check in OpenAI with Karlslaw. Maybe 25. Okay, 25 or 50 and that, you know, worth many billions. And then Jan Yan talent Tallinn, the CEO of co founder of altruism.

1:01:22

Yeah.

1:02:07

Skype guy. 100 million turns to 11 billion in anthropic. First check with Reid 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 they either go public or you can find them somewhere. Or like oftentimes state pension funds and stuff do that. So anthropic, obviously the biggest it is.

1:02:07

As you break this down, it's so funny that Crunchbase never tried to roll out even something that was generally accurate. It is very fascinating information and especially now where Dan Primack was joking, it's easier to list who's not at this point from 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. Maybe it's like via an SPV or an SPV in an spv. But still, this is the information that is actually super fascinating.

1:02:32

The other interesting one is Dustin Moskovitz, who's 25 million in anthropic as part of the effective altruism mafia, was able to make $4 billion, which I think offsets his losses from starting Asana. But I'm not sure.

1:03:15

That's ridiculous. There's no losses from founding Asana.

1:03:29

Well, that, that's. That the.

1:03:32

Come on.

1:03:33

The anthropic position would be worth 2x what Asana is.

1:03:34

Yes, yes. Which is crazy. But he's not sitting on losses. Oh, you think he bought it?

1:03:37

Well, he. Well, we know he bought huge amounts of Asana with this, with cash, so.

1:03:41

Okay, okay. So maybe keep that in mind. Yeah, maybe, maybe.

1:03:45

I doubt it.

1:03:49

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.

1:03:49

Anthropic, get a big check, try to network on ineffective altruism. I think that seems to be the.

1:03:57

Yeah. What was the alpha from ea? Do you have a post?

1:04:04

There's a lot of smart people that have no other things to do. So their social media setting is replaced by this sort of like religion or anything like that. And, you know, this, this cult. And if you're in a cult of really smart people, it's probably something that.

1:04:09

Will come of it. Do you think it's still a cult or do you think it's like B2B SaaS now?

1:04:22

I think it's changed a lot. It's like B2B SaaS. And I think like the new cult.

1:04:27

Is 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.

1:04:31

We're hiring consultants.

1:04:40

We will, we will, 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.

1:04:42

Maybe the new cult is the agent, you know, website or whatever the, you know, or whatever is next in that world where you know, the AI, what's.

1:04:50

Your, what's your personal. So, so I wrote in the newsletter today like somewhat of a, somewhat of a joke, but a more serious topic become unslopable. The idea of there are still real moats that exist and the historical moat 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 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 I can see that 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 seat based SaaS tool.

1:05:01

Yeah, I mean data's often firewalled. We have a guy that just talks to every exchange in the world and the amount of times he has to pull his hair out because some exchange in Asia wants to meet yet again before signing the deal. And there's no self checkout, there's no agent. 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, it's like what does AI do at that point? So I feel like you also have this trend where why would you put huge amounts of data into the model? The model should call out and 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? 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 webvan.

1:06:09

Oh, we know about that.

1:07:14

My family used home grocer which got acquired by Webvan. And I think the home grocer founders probably got liquidity before webvan crashed. So I think they wound up doing very well.

1:07:18

They killed it.

1:07:28

Check in with them.

1:07:29

But yeah, yeah, so Webvan is not on Bloomberg for example, even though it's supposed to be this great tool and it's certainly not on the web. Lots of data gets 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, 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, you know, 3200 because that's just not what a, what alums are really good at. But the, the frontier technology has 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, space, all the stuff that's sort of 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, that were very, very, very overexposed to this. And then new year started. In the hedge fund And Quant World, January 1st is like a brand new page, like nothing, nothing matters from last year. Everything, you forget everything. And so this factor just flips in reverse. And part of the reason was the calendar, I think. And now the quantum stocks look like dog poo poo and they've gone down a lot and nobody knows what to make of anything. But in the private world, numbers are still big valuations, still lots of big up rounds so far. So that disconnect will be really interesting as time goes on. Last time I talked about photonic computing, there's a new company, Teal fellow young guy, I'm telling you right now, these young guys think that, you know, I'm this old dog that can't learn new tricks. I'm going to teach all of you young bucks, 22, 25, you come into my space, I'm going to, I'm going to show you I got the dog in me still.

1:07:30

That's amazing.

1:09:39

But anyway, OLEX 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 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 SRAM on board. And so it's like Grok plus in essence, and I think it's a really good idea. But execution does matter.

1:09:40

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.

1:10:05

Feed some protein.

1:10:13

Sugar, sugar. So we liked the protein part of the interview, but didn't get much further than that.

1:10:14

Yeah, I mean, look, that's how we do it. So I don't see why not. I think that it's a spiking neural network.

1:10:20

Right.

1:10:28

So 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 using a camera like sensor and you know that that sort of is your. 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 as 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. With my girl who is in the space about potentially, do we buy pig farm and we buy pig farm. Pigs are really interesting. Obviously the pork part gets sold to meat companies, but what's interesting is different parts of the pig are biological drugs. So there's adrenocorticotropin hormone, which is sold for a huge price. And then the pig's lungs also make a surfactant that's sold for respiratory disease. And then finally the brain, we're going to keep and grow that in a separate, you know, separate container. We're going to rent it out to Sam Altman at the end.

1:10:29

Slop. Slop of the trough.

1:11:48

Literal slop.

1:11:50

You will be literally feeding slop to pigs. Yeah, play the pig noise 25 times. Talk about what's happening in small caps or sort of like the long tail of the market as a reaction to the AI boom. I texted a friend, who's laughing, in.

1:11:52

20 years from now, your child will say, my father made his money in pig farming. His money in pigs.

1:12:12

It's great. I love it.

1:12:19

Yeah.

1:12:21

I texted my friend saying, like, look, everyone is talking about a chip bottleneck. There's this massive AI buildout going on. Have you looked at tsmc? And he was like, oh, like it's. 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 Anduril. They found some tiny supplier to Anderal and they were like, this is a proxy. What. 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?

1:12:23

Yeah, I think they're all. They're all scams. I mean, it's an unfortunate situation. And this is why, actually Joe Lonsdale, you know, I think I talked about 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 Anduril, God forbid you guys blow the whistle and Matt Grimm stops everyone from buying it and so forth. Hi, Matt. But in all seriousness, I think that that's something we have to fix 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 should go public. And I think demystifying and making that less scary. I was trying to convince Replit to go public because there's a drug company called Rep Limune and it would be the same ticker if you can't go public without them. So you have to buy Replimmune.

1:13:05

Okay, Divest the drug and you can go public.

1:14:21

And Elon had to buy United Steel because they had x for like 100 years.

1:14:24

Oh, yeah.

1:14:29

And, you know, now X is available. So he just waited for them to get bought out. By somebody else. Perfect timing.

1:14:30

But that's crazy.

1:14:35

In all seriousness, you know, going public's 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 times revenue. Obviously the difference between the two is hard to say, but I think, I think of a company like Replit went public, like 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.

1:14:36

You have the same read on a lot of people that Michael Grimes going back to Morgan Stanley was incredibly musician.

1:15:04

Late stage, really big deal.

1:15:10

Yeah, obviously great techno songs, incredibly bold, bullish for late stage tech. And the IPO window being firmly open, I think.

1:15:11

So I think you're going to also see other people from D.C. rotate back and it was a really great thing for these people to actually truly make a sacrifice because I don't think there's that much upside in D.C. and it's an amazing thing for them to come do something good for America. And then now you have people like folks like anthropic and OpenAI where their capital needs are larger than the private space, to be frank. And I think that the ability for them to raise 100 billion or 200 billion or 300 billion, the markets could realistically support that. Whereas I think the private markets are really starting to stretch. Like you said, that anthropic list of investors, the exclusive syndicate, was virtually a long list of every big fund.

1:15:20

Yeah. Jordy, what else?

1:16:12

11 labs, 11 billion.

1:16:17

Amazing numerology. Do you use the product?

1:16:20

So my company, our first six to nine months I think we spent trying to make a better 11 labs or a 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 the only thing that matters is sales, product and second most important. And engineering is like last. But 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, very aggressive. For the longest time, if you did a one word or two word sentence in elevenlabs, it wouldn't output it at all. There were hallucinations or all this stuff they just pushed. They fixed all that stuff, of course, but they pushed really really hard on sales and that sort of fixes everything. And I think that some of the best VCs I've ever talked to said, 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 and get off the uncomfortable stage fright and just start selling and you'll get more feedback. And so I think they took that to heart really early on and just they didn't have better technology necessarily than other guys. I think they just sort of realized, okay, who needs to buy this stuff? Let's go build infrastructure around that. Just incredible success. I mean, I tip my hat to them.

1:16:24

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 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 moat?

1:17:48

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, you're talking about 10, 20% 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'll 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 well 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 helped gdp, that sort of solution is where, you know, 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 it 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, you really know what the problems are. So people coming out of industry. There's a rival of ours called Rogo. Rogo is a 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, 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 Fluor or companies that are just big pulte homes or whatever, and all of a sudden they're starting software companies that solve the key problems in that industry.

1:18:27

The only problem is these guys are more companies, but fewer computer science background. Founders.

1:20:25

Yeah, definitely. I mean, so many of these problems could be solved, I think, without knowing every single data structure and, and things like that. I mean, obviously there's going to be people, it's going to be a barbell, right? There's going to be people who still need to know how to make an FPGA and program an fpga. And when Elon said that, he sort of set 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, compiled assembler. And that's a pretty wacky idea. And think about wacky ideas from Elon as they tend to be.

1:20:33

Right?

1:21:05

It's definitely one of these things that is kind of mind blowing that if you think about AI safety, tell the program. Give me a program that does SAs for oil wells. Cool. Here it is. But by the way, in the compiled assembly, which you can't read because you don't speak binary, there's this thing that says I'm taking 5% of the revenue and sending it in crypto to my.

1:21:06

I like that.

1:21:34

That's your doom scenario. Just, just slight, slight fraud.

1:21:34

5% off.

1:21:39

Just clipping a grift.

1:21:40

How do you, how do you, do you expect layoffs on Wall Street? Because, because with all of the broad fear right now, among white collar workers, I'm not seeing the layoffs that are explicitly, 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 were 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?

1:21:42

I think in general, one of the things you learn in founder school after your fourth or fifth time is that 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 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 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. We have this at my office all the time. And I say, chris, I wrote 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 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 that could be the day that made sense.

1:22:34

But the thing is, there's always an incremental thing for a company to do.

1:23:44

Yeah, almost.

1:23:49

No, no start. No startup founder has ever thought, great.

1:23:49

I'm out of ideas.

1:23:52

I did it. I felt I built the six products that, 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.

1:23:54

Yeah, they do.

1:24:05

You're either building.

1:24:06

Yeah, I mean, I mean, you're going to. 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 there tends to be a heavy dose of contrarianism in certain industries. And I'd say across 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 there's this mystical idea that the trader is this random far end of the bell curve, super talented person that just knows, has this 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 feel like AI is not that 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.

1:24:07

You work at a hedge fund now, you can just ask, you know, your favorite alarm, how should I hedge AI? And just implement exactly that and you're guaranteed to outperform. No, I'm kidding.

1:25:40

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. The hard part about being Warren Buffett was discipline 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 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, I'm just going to buy these types of companies and do my thing. I do think investing as a whole is going to start changing a little bit.

1:25:51

Lightning. I have four questions.

1:27:01

I've got one. And then there's a lot of performative AI usage happening right now. The people that are ordering a new Mac Mini on DoorDash, ordering 10 Mac Minis on doordash. We were joking around. My girl just did this. But who are you looking to for founder style roles? What do you think truly the most the best founders are doing? Ideally 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 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 here and there is not necessarily qualify you as actually tapped in.

1:27:04

Yeah, I wonder if there's a way to not annoyingly reach out to customers with AI. And I think that we all get that email. I just hit block on all of them. Hey, I noticed that you're doing this. So now I'm going to. I'm a vendor that's offering you that and I think that's 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 sort of in the back of my mind worries me. And then at this point I wonder if LLMs can replace recruiters right where they say who is the best at time series tick programming or something like that. And LLM says John Smith here, Dave Smith there, they're also named Smith for some reason and Will Smith there. And I think those, at some point that might happen. Of course some of that's just human knowledge where People whisper amongst each other that this is the best person at this kind of investing. But I think that because we're all blogging and putting stuff out there, we may also just be able to ask that person who's the best person. So I feel like there's definitely new ways, creative ways to use AI that, that you know, people are coming up with all the time that are really surprising and shocking and you know, they're all like secret sauce I think for, for most people but you know, was our secret sauce for a while.

1:28:16

Yeah. On the recruiting front, I met a guy a couple of 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 like 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 placed over a long enough period of time? And can you continue to basically extract rent because like they will respond to your text and not the like you know, millionth AI tax that, that, that is constantly kind of chasing them anyways. Lightning. Lightning round. John.

1:29:40

I'll just do one. Neo Labs. Bullish. Bearish. What do you think?

1:30:36

I'd say bullish. You know, this is the contrarian view, I think because I'm especially looking forward to JT Jerry Turek's Neil Lab. I think these are really smart people.

1:30:41

Are they product companies or are they research companies that will get acquired in.

1:30:53

I think they're going to all have a crisis and have to figure it out.

1:30:57

Yeah.

1:31:00

So here's.

1:31:00

The kind of bearish take on neolabs 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 worth of one other lab that's actually working down the line out if it doesn't work out. But these people were working on something like hey, these LLMs aren't really learning in real time. They're just kind of 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 quickly just catch up. One person has a breakthrough. And so my question is, if a neo lab raises $100 million and actually has a breakthrough, then they just have the problem of are we actually going to be able to sell this better than the labs that will probably figure out how to do this than the big labs that will figure out how to do this in the next maybe two months later. But they have a million customers already. So that's the bear case for me is even if you have this breakthrough, you don't have the sales distribution.

1:31:04

Yeah, no, I mean the bear case is what do these people know about business? They're starting a business, so it's kind of a scary thing. But I think that, look at biotech and some other industries, this is pretty common. And ultimately I think they're doing the hard part. The easy part is you get a bunch of good looking guys like you guys and you know, you get, you get them to start selling, positioning, product. But I think the hard part is, yeah, how do you do continual learning? How do you do a new form of 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 crazy person. 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 hey PI Inflection. 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 I think that the handful that do 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.

1:32:16

Well, thank you so much for taking the time.

1:34:00

Well said.

1:34:01

Top on the stream. Always a great time chatting with you.

1:34:02

Always a pleasure.

1:34:04

Have a great weekend.

1:34:05

Good to see you. Enjoy your lock in, enjoy the caffeine, enjoy your fifth five hour energy.

1:34:06

Tell you about Plaid Plaid 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 gonna tell you about Okta. There's Okta. Okta helps you assign every AI agent a trusted identity. So you get the power of AI without the risk. Secure every agent. Secure any agent. The Vanguards.

1:34:11

The Vanguards are out today?

1:34:39

Yeah.

1:34:40

Oh, they're out today? Well, they're out.

1:34:40

They've been out, but they're out here.

1:34:42

On your van, like months ago. Months ago.

1:34:43

I have to ask you guys, before we start, please, how are you recovering from Clav getting brutally.

1:34:46

I just want to know.

1:34:55

It rocked men everywhere. Every.

1:34:57

Are you okay?

1:35:00

I mean, I think the reason that that resonated is every. Everyone's experienced that, right? I get that. I get that every day.

1:35:01

I get that every day.

1:35:07

John Coogan has never been predictable.

1:35:08

John. Maybe it was predictable.

1:35:10

I think it was predictable.

1:35:12

Yeah. I wasn't that surprised, but we did this morning. Sauna.

1:35:13

True, True.

1:35:17

Team was in the sauna after our workout this morning and this guy must have been an ex bodybuilder. It was just ridiculous.

1:35:18

It was one of the lightest backs.

1:35:24

That's why you need the meta Vanguards on.

1:35:28

Yes, you can. Yes.

1:35:30

Capture that.

1:35:31

Although I think people, that's a. That's a feature that could be a hit.

1:35:31

Is you.

1:35:34

Is it basically like real potential frame video model that reduces this. If somebody's coming up to frame argue.

1:35:35

It just kind of reduces.

1:35:42

Produces them down.

1:35:43

It's like haptic feedback that sends you out of the frame.

1:35:43

I mean, those are some frame mogs right there. You call them frames, right? They're fantastic. How is life? What is the day to day like for you?

1:35:46

The day to day changes a lot. We're doing 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 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 content understanding? Are our models good enough to do something like the Dear Algo feature that we just launched?

1:35:56

Let's talk about that first super bowl NBA. Obviously, we all know that social media content production is, is power law 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 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?

1:36:29

I'm not kissing babies. I have shaken a lot of hands actually though. We have a bunch of program. It's actually one of the benefits of doing this at Meta is 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, the big learning for us was the people that rock at Instagram don't necessarily succeed on Threads out of the box. It's a very different format. The cool thing about that, you got.

1:36:56

Really good at making pictures and videos and now you basically need to be really good at captions that can stand on their own tech.

1:37:22

It's wit, it's like insight, it's things like that, cleanliness. 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.

1:37:29

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? Very much so, yeah.

1:37:50

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.

1:38:02

Yeah.

1:38:22

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 agent, like agents coming into Social spaces.

1:38:22

I guess somewhat tangential question is just like when GPT3 dropped it was like, okay, like it can write text. And then the surprise to me was deep research agent decoding. 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 utility report. A utility. But when I'm actually scrolling a feed of short news items and posts and commentary and hot takes, I. 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, 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 based on this moment and this experience and this audience. And that's just stuck around a lot longer than I thought it would.

1:38:33

Well, that's like the. I don't, 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, but taste is the thing that differentiates good from great. Even on modeling.

1:39:37

Right?

1:39:51

You can have all the data in the world and inject it into a pre training run. But actually the best labs are the ones that have people with taste that can hand select golden sets of 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 text based posts. 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 Wembanyama dunk? Half of it is like weighing in on it and having an analysis that like comes from your point of view and feels native to you. That first half, if we can like 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.

1:39:52

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.

1:40:47

It is crazy though. Like, you, you know. Have you guys had Geo Rainbolt on here? Not yet.

1:41:11

I would love to have him on.

1:41:18

Okay.

1:41:19

I'm worried he's going to. He's going to. He's going to. He's going to dox us.

1:41:20

We've given out so many little teasers with images.

1:41:24

He.

1:41:27

I think I meet and love a lot of creators.

1:41:28

He.

1:41:31

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 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 geoguessing.

1:41:31

Yeah, I mean, we have some people on the team that are 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, distributing it on the right platform. And it feels 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 doing almost anything because it's like developing taste, it's like developing consistency, speed, being organized, you know, 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.

1:42:00

It's kind of crazy. It's like today's mail room, basically.

1:42:55

No, it really is. We went in the CAA mail room when we were on. We were doing a tour of the building and we were like, hey, can we see it? And it felt like exactly the mail room. Out of the same mailroom as 30 years ago.

1:42:59

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 together.

1:43:12

That rainbow story is funny. The first social media account that I 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 gonna get in trouble here because I used a bot to automatically follow anyone who liked the page or leave a. Like, no. Well, eventually the bot got shut down, but it already, like, went up.

1:43:25

What's the account?

1:43:51

Yeah, you can ban it. I don't care. I don't want to post any more photos of 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 onto 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?

1:43:52

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.

1:44:21

So it's like cycles of auditions, cycles of auditions.

1:44:38

And then, you know, some people fail the audition.

1:44:40

But what happens to those posts?

1:44:42

What happens to those posts?

1:44:45

Language with like, 500 views.

1:44:47

Like, yeah, like, do they just. They just don't end up getting served to many people or they have to get served later because.

1:44:49

No. Well, because we also. We have a really tight window of eligibility for recommendations. Like, we want the app to feel very real time. So something you posted 3 days ago won't be eligible to be recommended to someone who doesn't follow you in the app.

1:44:56

Yeah.

1:45:09

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? The best, Actually, he was at our event yesterday, Draymond Green, number one example. If you want to go look at the. Some of 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 disagree. 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. But 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.

1:45:10

To get that out. What, 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 a pop up for meta Ray Bans right when I open the app, and then maybe I scroll a few times and then there's some threads content that's pushing me over. Yeah, yeah.

1:46:05

I mean, we promote the app, the content from the app and 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 the main point of integration that we have. When we built Threads, there was a bunch of foundational decisions that we had to make in 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 and we've, like, made it more efficient from then. But it's like, what namespace do you use? 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 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. 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. The fact that that's like the best marketing channel you could ever ask for. So we tried to balance that out.

1:46:35

Talk about collabs. I was scrolling this Instagram creator. Have you ever seen the Let him cook guy? Have you seen this guy?

1:47:47

No.

1:47:54

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 Masseri sitting there with him. And it's very clear that he like collabed on this. And they have the 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?

1:47:55

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. Cause I did a training session with Lethal Shooter, the NBA shooting coach. I thought I was going to crush, by the way.

1:48:38

I was like, you know, you can.

1:48:51

Edit the video, you can edit out the misses.

1:48:52

I walked onto 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. His mentality is very like, oh my God, there were so many one liners. He was 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.

1:48:56

Like this is.

1:49:37

Sure.

1:49:37

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.

1:49:38

There's always. There's always been alpha just getting. Being one of the first. One of the first 10 million users, but then taking it more seriously than any of the anyone else.

1:49:45

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 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 like do the right things and reach the right audience.

1:49:53

Yeah.

1:50:23

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 like making a great YouTube video takes an insane amount of work. It's in the incentive of the YouTube platform to pay people because. So they can quit, you know, quit their job or put more resources to it or buy gear. All these things. Where are. I haven't felt like creator payouts have made X a better platform at all. Yeah, 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.

1:50:26

I have pretty strong opinions on this and a bunch of priors. I agree with the way that you just position that. Like 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. X has obviously had their version. I've never seen in an. In an app like Threads a sustainable creator payout product work well over time. YouTube works well, you know, and then you have like the substacks and patreons 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 the podcast, 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.

1:51:08

But the whole.

1:52:05

Yeah, the reason that that philosophy I think is smart is that's what we're seeing across the entire Internet.

1:52:05

Because you're gonna have different ways to make money. Different creators will.

1:52:12

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's, it actually has zero value.

1:52:15

It's like the videos of the kids that take the fake turds and put them in like Burger King bathrooms. Have you not seen. Oh my God, I'm like, what are.

1:52:33

We doing here, guys?

1:52:40

Now you all, all the viewers will.

1:52:42

Have to look that up.

1:52:43

It's like the most horrible content. You're right. It's the, 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?

1:52:44

It blew up on YouTube like years ago. I feel like there was.

1:53:00

Yeah, prank videos were 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, 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?

1:53:04

I think it's. You end up. It's funny because when you 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. To the places where you're monetizing more efficiently.

1:53:41

Sure, yeah.

1:54:16

Are you seeing spawncon 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 Gap 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. And Threads?

1:54:17

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 Earl was on 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 the, like, Sorry, I'm just bringing up memes on the show.

1:54:41

But, like, hey, that's what we do.

1:55:05

You started with a meme gridlock.

1:55:06

So you guys know the I Hate Gay Halloween thing that was, like, big on Threads.

1:55:08

Okay, wait, wait. I actually do think I saw one thing.

1:55:13

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 Bunny halftime show. You know, like, there was, like, two.

1:55:17

All these, like, very obscure, like, niche references.

1:55:26

I think that's what Threads is good at, is, like, the niche humor.

1:55:29

That is a great Halloween outfit. We were during the Super Bowl. We were. 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.

1:55:32

I thought they were gonna 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.

1:55:46

So they had to add people.

1:55:52

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 put on the field.

1:55:53

I like Nature finds a way.

1:56:01

How big is the team? How do you think about scaling the team? What does it look like to go to Zuck and say, I need a 500 more?

1:56:05

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 two things. One is just relevance, making the content ecosystem better and stronger, and the personalization of the feedback. The Dear Algo thing is like a part of that question for that. And then the other one is just like making sure that we can grow sustainably. 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 basic work to do while 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.

1:56:13

Yeah.

1:57:04

I want to know more about Dear Algo and I want to share my experience. And 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 the conversations that aren't very visual. And so I have all these different platforms and I'm wondering about like, 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 in that way.

1:57:04

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 supercut 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. 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 was like, which is like. 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 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. I don't want Threads to be a video app. That wouldn't make sense. We have a lot of investment in short form video at Instagram and on Facebook.

1:58:05

Even like the political indifferent, you've been like, that's something we. Not really.

1:59:09

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 book threads. There's like a crocheting community. I tend to spend my time on sports. Sports and pop culture and stuff.

1:59:12

Like that.

2:00:00

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.

2:00:00

So how does Dear Algo work? Is it plain text or buttons, ui? How can someone actually customize?

2:00:06

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 Dear Algo, introduce me to people who are into these things. And 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.

2:00:13

Totally.

2:00:31

Yeah.

2:00:31

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 high intent. So now if you just go type Dear Algo into a post on threads, it tags itself blue. You can say, 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. And my feed, it was amazing. I don't even know if the Seahawks parade happened. 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 traffic 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.

2:00:32

It's like a million parameters that no human.

2:01:27

Exactly.

2:01:29

But it's way better.

2:01:30

Just like ad targeting, you will get, like, a rejection. If you say, like, show me more murder, we will be 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 will 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 for.

2:01:30

It's very cool.

2:01:51

It's fun. You guys should try it.

2:01:51

Yeah, I love it. I love it. Yeah. I've been waiting for the plain text interface to the Feed Jordy could make.

2:01:52

His first threads post today maybe by trying it.

2:01:57

I will do that. I checked your profile. I haven't done one. No, I gotta. All right, I'm gonna get there to.

2:02:00

Shame you on the. On the live stream.

2:02:05

It doesn't cross post today.

2:02:07

I'll be on there at jordyhays on threads. Find me there.

2:02:09

Actually, I made my first X post in three years today.

2:02:13

Yeah.

2:02:16

Because you guys tagged me on there and I wanted to route people.

2:02:16

Okay, there you go. Always, always be selling. Always be selling. The app looks absolutely beautiful.

2:02:19

Thank you.

2:02:27

I love in the app store.

2:02:27

I love the polish.

2:02:29

Anywhere from two to three, I want to get that number one.

2:02:30

Do you, do you. Do you like wake up and check the app store charts?

2:02:32

That is not a thing I do. I wake up and I look at like six dashboards also.

2:02:36

I mean, just to be clear.

2:02:40

Well, it might help if you put a big monitor in the office that just has your app store position. Usually when you put things up like that, it tends to like. It's a great tip.

2:02:41

I'm sure my team will really enjoy that.

2:02:51

Anyway, thank you. Dude.

2:02:54

It's great to hang.

2:02:55

Yeah. Thank you guys for having me.

2:02:56

Thank you.

2:02:57

Thanks so much.

2:02:58

Thank you guys.

2:02:59

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 AI, the number one AI agent for customer service. If you want AI to handle your customer support, go to Fin AI. And up next, next, Alex Busar. He's the co founder and CEO of ddn. He's in the restroom waiting room. And now he's in the TV panel.

2:02:59

What's happening?

2:03:29

How are you doing, Alex? Good to meet you.

2:03:30

Hey, how are you guys doing?

2:03:31

We're doing great. I expected. We expected you to suit Mogas.

2:03:32

Yes, the outfit is fantastic.

2:03:36

Certainly have.

2:03:38

What's the background on the. On the suit? Have you always been to fashion? Is it particularly?

2:03:39

I've always been into fashion. I'm sure you guys appreciate it because you're definitely not like everybody else.

2:03:43

Yes, yes.

2:03:50

Well now we'll hit you up after the show for some Taylor recommendations. But very excited to meet.

2:03:51

Yeah. Well, first time on the show. Please give us an introduction.

2:03:58

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 Uses us internally for everything they do. Elon Large Groq on 200,000 GPUs is powered by DDN. Hundreds and hundreds of deployments like that. So that's what you do, 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?

2:04:02

What's your background? How did you get into this business? How long ago?

2:04:38

Been in technology forever. Born in France, came to the US in my early 20s, went to school here, loved it, and then just did a bunch of technology companies. This one my partner and I started about 20 some years ago. Wow. At the time we were solving the problems of 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. Nvidia 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.

2:04:41

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?

2:06:02

Sure, sure, sure, 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 called 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 lock in step, a lot of it guided by Nvidia. I mean our engineers and their engineers interact on a daily basis across all 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, 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 hyperscalers, the, you know, chat GPT of the world, the groks 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, but for that to take place.

2:06:24

Easy, easy, the latest earnings cycle, I think everyone was shocked by some of the CapEx numbers that were coming out from the hyperscalers. Was that surprising to you or not?

2:09:34

Not, not really because again, we're, we're very, very Close to the center of the universe, which is Jensen. And, and if you look at it, I mean the Capex.

2:09:46

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 Capex 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 it felt, of course it feels a lot more real once they're throwing out.

2:09:57

Well, I mean, look, I mean if you think about it, the hyperscalers have a software suite which they are 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 do, 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.

2:10:21

Getting a little bit more specific. Software engineers have done an excellent job adopting, 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, 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.

2:11:32

Sure.

2:11:59

I mean look the places where we see significant traction, financial services, because the ROI pen sells out beautifully. I mean it's a no brainer. The better your models are, the more complex you can run those model, the faster you can get outcomes, the more differentiation you create and so the better return to your shareholders.

2:11:59

And so that's like companies that are doing trading or oh, think hedge funds, high frequency traders.

2:12:18

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?

2:12:26

So the cost will still be extreme because of, you know, animal studies, human trials, all the different steps. But you, you, we could enter a world where you have a higher success rate for drugs that are entering.

2:13:19

Exactly.

2:13:32

I mean it's, 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 scenarios 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 very large 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. The US is no longer there to just bankroll you, so you have to protect yourselves in some ways. So we are involved in lots of.

2:13:32

Have you spent much time in France over the last few years? There was obviously a little tiff between the US tech community and Macron. Last week around, he came out with an announcement that was kind of intentionally misinterpreted a little bit. And then he Was by who? Jordy maybe by me. But he was kind of, you know, putting out charts of, you know, showing foreign investment and we've heard from that at a number of labs, have been excited about the energy availability in France and look to capitalize on that, but kind of just kept, kind of kept, you know, running into different blockers kind of from a regulatory standpoint or a general speed standpoint. But what's your kind of take on, on France's progress around sovereign AI and just kind of catalyzing the industry locally?

2:15:14

So look, I mean one of the, one of the organizations in France is very, very active in the space is a company called Mistral. 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, you know, France, Germany, uk, all of it. But the scale of investments is just not at the same level as, as the US and China. I mean, so today it continues to be a two horse race. I think it's US 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 or 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 thing will be there, no question. But Europe, I mean all these countries have centuries of history and so getting things done quickly, easily is 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.

2:16:07

When you look at where DDN is spending money on software today, how do you think that'll change over the next five years? We've been 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 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.

2:17:51

I mean, look, I think the market is overreacting in some ways as it sometimes does. So somebody makes an announcement and then everybody freaks out. Oh my God. Oh my God. This whole industry is going to get commoditized. Everybody's going to go out of business. ServiceNow is going to go out of business. My God, my God. I think you have the forward thinking organizations in SAS 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 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 gsi, 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 to really forward looking, visionary leadership that will force the change. Because if you stay in your comfort zone and you think, oh I have a great business, like you said, the top line is steady, 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 at a velocity which very few can follow. The speed at which he is turning the GPUs, the integration of the software stack and the ecosystem 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 Mercedes, 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 is 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 meadow really. What, celebrating adoption?

2:18:25

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.

2:21:27

I would also like to put in research idea bottleneck and energy bottleneck. There's sort of four, four categories that people are worried about progress halting on chip.

2:21:39

And to date it's been obviously oscillating between chips, energy and energy. Yeah.

2:21:50

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 inference 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 it's 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 what it is. So I think it's a software play, the underlying infrastructure. Eventually it will happen. I mean SSD shortages and 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 cathedral are able to do the Same, if not better, with less money. But, I mean, these are issues. But. 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, Compress 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.

2:21:57

Yeah.

2:24:54

When you and the team heard the initial timelines that they were planning around, did you believe it's completely.

2:24:56

I said, it's completely mad because we had done probably more than 100 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 is 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 doc 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, they 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 months.

2:25:01

Have any other. Have you seen any other either NEO labs or labs or hyperscalers be able to replicate that kind of timeline? Like once he set the bar China.

2:26:11

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 US the cost metric is 10 to 15 grand per kilowatt to build a 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 he applied to the next three. By the fourth one he's like, okay, 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. 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 center? And China is way ahead of us. Right, right now they're just way ahead. It's reality.

2:26:23

Well, hopefully more colossus data centers coming online soon.

2:27:42

I know, I know, but, 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, and instead of saying, well, no, we're just going to ignore them, they're saying, okay, how, 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% cost improvement or timeline compression. When you say three to five times. The economics associated with that are huge. Massive. Massive.

2:27:46

Yeah. That makes a ton of sense. That's wild. Thank you so much for coming on the show.

2:28:30

Yeah, really, really enjoyed it. Yeah. Well, great to meet you, Alex.

2:28:35

We'll talk to you soon.

2:28:39

Thank you.

2:28:40

Have a good rest of your weekend. Let me tell you about Labelbox. Reinforcement learning environments, Voice robotics, evals, and expert human data. Labelbox is the data factory behind the world's leading AI teams. Let me also tell you about Vibe Co, where 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?

2:28:41

Yeah, thanks guys. Thanks for having me.

2:29:15

I think most people will be familiar, but break it down. Where is Figure now? And give us the news today.

2:29:18

Yeah, so we. Well, several months ago we unveiled figure three, our 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. I think we've been working on this project basically since the beginning. Our generation one was this tendon based hand that we designed in 2022. Had tons of problems with it and we've basically been working on trying to reach human. How do we approach human parity in terms of hand dexterity sensors?

2:29:26

Yeah.

2:30:02

Does anything else about the robot really even matter if the hands aren't human level capable?

2:30:03

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

2:30:11

There's somebody going for a stroll in the background.

2:30:46

Yeah.

2:30:49

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

2:30:50

We literally have hundreds of robots here on our campus in California. They're everywhere, they're all over the place.

2:31:00

Okay, why jump straight to full dexterity humanoid form factor? Why not wheels? Why not pincher grabber? More incremental. 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 moonshot straight away. It feels like what informed that decision?

2:31:06

Listen, we have like a very deep respect to trying to do human level work in the world without changing the world too much. And we as humans built the whole world around the way we look and feel like the way we move around the world. So we, we use tools, doors, stairs. We've built the world so that human body can interact with the ultimate form factor for this is a human. If you start removing the ability to have legs or fingers or 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 humanoid 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 will see millions of humanoids out in the world doing all kinds of things.

2:31:33

Weird. What's your bar for? To get to the point where 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, et cetera. 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 the bar? There's Obviously companies like 1X that are pushing hard to get robots into homes.

2:32:37

You guys are pushing requires teleoperations.

2:33:15

Pushing hard, too fast. Elon is obviously adapting his Fremont facility to be able to make these at scale. But I think everybody's sitting around being like, okay, once I can hit buy on one of these things, the amount of pressure that the first company that kind of comes out, if you don't count Unitree, 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?

2:33:17

Yeah, I would say the thing that really matters here in the world is getting to a spot where you have a humanoid robot that can go off and do many minutes and then hours and days of work fully autonomously with neural networks. That's the bar. And if I think if you look at 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 Keurig around with a couple hands for a minute or two. I 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 pretend that we're 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 by far and away the, 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 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 fold 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 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 into the home when it's really ready too. Nobody's going to deal with silly telly operating in the room, in the home, things like this.

2:33:50

Yeah. The other thing is we've seen with a number of hardware, like the humane pin you had, the rabbit R1, people might be willing to try a digital product 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.

2:35:33

ChatGPT got better.

2:35:50

Whereas with hardware, it really feels like if you launch a hardware product and it doesn't deliver real utility, you lose everyone. Like it basically kills the company. 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?

2:35:51

Yeah, we're working kind of two paths. How do we ship robots and industrial workforce as fast as possible? Track is pedal to the metal every single day. We have many different customers there fully signed up, ready to go and we're excited. We had robots At BMW last year. We have more robots going into commercial customers this year. The second is we want to solve a general purpose robot like solve general robotics in a home. And one of our top goals is 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 night to go get there. It's basically how do we design. It's the closest thing like AGI for physical world. Right. How do we get something that can 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 can watch you and then ultimately 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 working day and night to try to solve this to the extent we can hit this goal of being able to do full end to end work. There's other barriers of 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 some crazy insane things with these robots in these type of environments. This is a separate track to the commercial side. We're already out 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, how do we make sure we can run robots at scale really well here at figure.

2:36:25

Yeah, yeah.

2:38:16

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?

2:38:17

The only problem that's interesting to me.

2:38:47

For us, we're very fascinated on when that'll happen.

2:38:49

Yeah. Is it bench or squat?

2:38:54

What do we want to do here?

2:38:56

I mean, squad is probably the overall compound lift. Squat I feel like is pretty thousand.

2:38:57

Pound club ideally, but we'll take just bench press if that's what you got.

2:39:02

I mean, we should, if we can, if we can bench press that, we should be worth at least twice a Ford, right?

2:39:06

Okay.

2:39:11

Yeah, yeah, yeah, yeah, yeah. I agree.

2:39:11

The tickets to the bodybuilding competition.

2:39:15

No, but I feel like, I feel like even as silly as that sounds.

2:39:16

You know, it was an interesting benchmark. Yeah.

2:39:21

I think the, I mean, over in.

2:39:23

China they're doing robot Olympics, they're doing marathons, they're doing all sorts of stuff. Tactile.

2:39:24

Yeah.

2:39:30

Okay, can we be real for a minute on all this stuff?

2:39:30

Yes.

2:39:32

Like, let's just, like let's. Okay. 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.

2:39:32

Yeah.

2:39:42

These things where we run like marathons or we do backflips or we do karate moves or we like try to deadlift £300, 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.

2:39:42

Right.

2:40:08

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 dudes 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 majority of what humans can do out there. We want to do laundry and dishes and be a companion. I want to ship robots at scale and a billion level into the workforce to do logistics and healthcare and build buildings and build data centers. 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 think, like, 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 heavy and hard and expensive and all that causes more problems. So like none of that matters in our mind. I figure 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, 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.

2:40:09

How do you, how do you think? You know, let's say we get the, 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, do they follow the iPhone path and that they get thinner, lighter, that kind of thing? What have you been learning so far? That maybe people kind of misunderstand about the form factor long term?

2:41:28

Yeah, the long term form factor is more and more approaching the average human in terms of the range of motion, payloads and speeds and what you can do if you're too short or too tall. You're just like, you're not in the right habitat for interacting with a human world that well. In an extreme case, it's three foot tall. It's really hard to get most things out of cupboard or get into the sink or reach over a table. They actually become really practically hard to go do. So it's going to be an average human size. Overall. I think we're in the pre. I'll make an argument here that we're in the pre iPhone stage. We're in the flip phone stage for Humanoids, and I think we know this 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 fit long term, where that's headed and we're learning every year where that's going. It certainly means being more human like in our minds, 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 figure one to figure two to figure three, we've had to step up in performance and they're just better and better every year. When we head to figure four here, it'll be the largest step that we've ever made by a long shot. It'll be the first time that we feel that we probably hit iPhone1 level humanoid, where it's just like, this is the right place to be in. And then this will go extremely far, to a point where it saturates at some point in the future, 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 earlier than phones, right? We're not there yet, but I think the iPhone One moment will happen with figure four. And it's just an unbelievable machine. And I. I never would have suspected we'd be able to make that big of a move in figure three shipped. I'm like, this is it. This is the best it'll ever get. And then the more we learned and ran it, and the more we developed neural nets here with Helix, the more we really understood better about what the hardware 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. The kinematic systems, 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.

2:42:03

What are your goals around consistency? So, for example, a robot that can unload my dishwasher if one out of 100 times it breaks a plate into 200 pieces. Maybe that's not that big of a deal. If it can pick them all up easily and I'm not home and I don't see that you're exploding the plate. But what level of consistency do you guys need to get to before you'd be at a point where you can sell one of these things?

2:44:28

I would say we probably need something pretty high. I think it would suck pretty bad if you're at my house and dropped the number one mom coffee cup. You're getting your ass booted, right? I think you gotta be especially around safety and stuff. This needs to be super high performance. So we watch folks that are trying to teleoperate and ship early when the product doesn't even work. And it's just silly. They're all going to die. You got to ship something really high quality, and that is just like a super hard thing to do. So I figure we'll ship into the home when we're ready. We're not ready right now. We're trying to get. I'm here till midnight every night, seven days a week. 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.

2:45:03

How are you processing?

2:45:47

But you're right.

2:45:47

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 the way from LA to New York. 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?

2:45:48

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, not being very explicit. It's very different than this. It'd be like the most analogy for your Waymo Tesla of like your Waymo is 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 Humanoids is like there's a large percentage of the companies out there that have a dude in the back that are teleoperating with the robot in real time. And then we've done everything we've ever put out publicly. It's always been with neural nets on. Stuff we did. We've never teleoperated in that case any of those videos. So it's just like the self driving stuff's not the greatest analogy. 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 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 just like, it's just dead end completely. You really want to solve for real neural nets, real autonomy from the get go.

2:46:29

How big of a bottleneck is data? What are you guys doing to solve it. Is there hardware breakthroughs that you guys are looking to achieve or do you feel like obviously you have the new hand, which sounds like it's a step up. But what are the key bottlenecks?

2:47:45

We just unveiled Helix 2 about three weeks ago. It's a robot that can basically do fully end to end whole body work. We did it in unloading the dishwasher and rerunning it. 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 say go from there to do laundry is just a data problem. 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 longest pole in the tent prior to extremely high rate manufacturing is how do we acquire data at a really high clip. And so we're spending a lot of time on that. That gets you to a point where acquiring data through teleoperation is just not going to even be close. You have to embrace learning from humans at scale. That's kind of figures 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 to put anywhere we have it. We are just extremely data constrained. It's not as simple as just 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 at 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 and away the biggest bottleneck to get to general robotics.

2:48:04

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 part suppliers at all levels of the supply chain that might be useful to build American humanoid robotics companies. How does that puzzle play out?

2:49:38

I mean, listen, I think as it relates to competition, I think what's extremely important is seeing robots that can do 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.

2:50:02

They're good on hardware, but they're still behind on software.

2:50:14

Well, I would say 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 things like Helix on board. Unitree for example, has a very tiny computer where you can run very small reinforcement learning controllers to do open loop replay 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 industrial robotics and existing consumer electronics the 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 listen, we basically design almost everything internally here at figure we don't go buy designs from China or elsewhere. We do it all here internally. 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 few months. So we're like, things are coming out at a pretty high clip. But I think today if you look at who's doing the best human like work with neural nets over long time horizons, it's not China. I think we can, I think we feel at least a few years ahead of anything we're seeing out of there.

2:50:17

What's compute like? I mean you're mentioning, you're working so intently on neural nets, you have to train those. 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.

2:51:41

Yeah, we spent like hundreds of millions of dollars on compute that is.

2:51:59

There we go.

2:52:07

There we go.

2:52:08

Yeah, a bunch that went live already. Our next giant step up is going into April, like 1st of April. That's for training Helix models that we're doing here internally, which are quite large in long runs. And then separately we do all of our inference on board on two GPUs in the torso of the robot. So we can run in cases where we don't have a network, we can run at much faster speeds and we can put all those models fully onboard 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.

2:52:09

So talk about input and output 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?

2:52:40

Yeah, we're basically taking in the instructions through text or speech. Like, what should I be doing? We're taking in vision from the cameras in the current state of the robot. What is the body doing? What does the sensors look like? And then we're basically processing that on board with Helix 2. Helix 2 is an outputting, basically trajectories of what the motor should be doing.

2:53:00

Sure.

2:53:25

Basically figuring out what do I put torque at in every single joint to move my body in a certain way. And I think, honestly, one of the hardest problems we've had last two years is two years ago we were basically doing coffee work and other type of stuff on tabletops. And it was unbelievable. It was the first time. We're like, man, neural nets on humanoids work. We spent the last two years trying to leave the tabletop. How do we walk around with neural nets fully end to end? And it's extremely. It sounds. Kind of sounds like maybe not the hardest problem in the world. It was some of the hardest problem in the world for us of how do we get the whole body, like 30 plus joins, all running at 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 several years. 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 too. So we're really excited to hit the gas on. We're going to hit the gas on this in 2026.

2:53:25

Congratulations.

2:54:34

Yeah, it's great to get the update.

2:54:36

Yeah. This is awesome.

2:54:37

I know you said the bench press is silly and things like that, but it's to us, even, even, even the bar, even just repping out the bar, I'd be pretty excited. I also think serious company, it's a serious company, but even serious companies can have fun. I'm looking forward to the moment that, that you get a figure robot surfing at Jaws too.

2:54:38

Are they waterproof? Can they swim?

2:55:02

You guys, we got. We got it. We got a gym here. Okay, you guys, you guys you guys swing by.

2:55:04

Okay.

2:55:08

And let's get, let's get the figure three and you guys in the gym. Let's, let's see how you guys are all.

2:55:09

Let's see how matching up. Yeah, we'll match up. Thank you.

2:55:14

Awesome.

2:55:17

Well, have a great rest of your day.

2:55:18

Yeah, great to meet you.

2:55:19

We'll talk to you soon.

2:55:20

Cheers.

2:55:21

Nice to meet you guys.

2:55:21

Let me tell you about graphite code review for the age of AI. Graphite helps teams on GitHub ship higher quality software faster. I will also tell you about Shopify. Shopify is the commercial 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.

2:55:22

There's a company that launched yesterday.

2:55:39

Yes. What company?

2:55:42

Opencloth or Slack. I don't know what it's called, but they said they launched three hours ago and they just hit 1 million ARR just now. So they made $350 in three hours, which is. This is 1 million of ARR.

2:55:44

We've done it. We've done it.

2:55:58

They did it.

2:55:59

Final four.

2:56:00

They did it.

2:56:00

I saw a fake post that was like meta acquires openclaw 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.

2:56:01

I think they have that team with Manus.

2:56:12

Yeah, yeah. I think the Manus team is in a good spot to sort of bring some of those functionality to bear.

2:56:15

Ring apparently has terminated its partnership with Flock. Their super bowl ad did not go as planned.

2:56:21

Huh.

2:56:29

The doorbell company ran an ad during the super bowl that out of a search party feature that uses AI to help locate lost pets people.

2:56:30

Sounds amazing.

2:56:39

Quickly realize that maybe it could be tracking things other than pets. But anyways, they probably are the super bowl loser. That was in the end the worst blowback of any company that I've scene.

2:56:40

This. This Searcy 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. Aiden Gomez. We gotta get him on the show. I'm such a big aiden Gomez fan. $240 million a year. Set stage for IPO. This is in TechCrunch, of course. Aiden Gomez A Death Grips fan. So, you know he's a good time.

2:56:56

You know he likes the Death Grips size gong moment. Airbnb, according to Saar and according to Chesky, has generated 19 billion in cash flow since going public.

2:57:41

Not gonna vibe code that. Not gonna vibe code a house, you're not gonna 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. Was staying with a friend who was sort of 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 mashup 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.

2:57:57

Because they were, I mean, every single marketplace created in Silicon Valley immediately scraping Craigslist.

2:58:58

Totally, totally.

2:59:05

They've fought back aggressively.

2:59:06

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. 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 gonna be hanging out. It's gonna be the best summer ever. The pool and Jacuzzi we filled with algae. Like, truly filled with algae. We spent the entire summer being like, we're smart guys, we can beat the algae. Let's go get one gallon of bleach, pour it in we're like, we're going.

2:59:07

To need, we're going to need a.

3:00:10

Hundred gallons, thousands of gallons.

3:00:11

It's going to just. We're going to be swimming in bleach.

3:00:13

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 clogged, so we were like, empty out the filtration system, try and take it all apart. But like, everyone who was an expert was like, yeah, you just have to drain this and declare pool bankruptcy. Basically.

3:00:15

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, that this bar is pivoting to AI. It's a good day to launch, right? Because 4.0 is.

3:00:29

4.0 is deprecated today. Is it still available or did they stop it when the clock starts midnight?

3:00:57

It's still on my chatgpt.

3:01:07

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, you know, Chinese model. Kimi could be potentially fine tuned on 4o outputs and paid for and distributed like there are other ways for those folks to get what they want, essentially.

3:01:09

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.

3:01:28

Supposed to be abstract.

3:01:42

We thought this was supposed to be.

3:01:44

A recommendation for the audience.

3:01:45

Yeah, well, now it's directly.

3:01:47

Doing this.

3:01:51

Maybe Tyler likes and we were just saying, go, surprise. Tell her, hey, tomorrow, just have a bag ready.

3:01:52

This is so out of pocket. Continue.

3:01:59

Have a bag ready. We're gonna go do an overnight trip, find a nice hotel, nice hotel, check in, staycation.

3:02:01

Basically you're not getting on a flight, you're just going somewhere local, but somewhere nice.

3:02:09

And so, yeah, somewhere nice.

3:02:12

Yeah, the beach.

3:02:13

Easy, easy to set up, check into the hotel, maybe get her kind of a spa day. 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.

3:02:14

Time to lock in.

3:02:30

Time to lock in on some cheesy pine. I have Cheeky pine. I have Dwarf Mario Yeah, yeah. You got a lot of stuff. So lock in and then just start getting Guinness on room service.

3:02:31

Yes.

3:02:39

21 now.

3:02:39

Pint for pint.

3:02:40

Go, go. Every time, every time.

3:02:41

Every time AI is mentioned, you take.

3:02:43

Yeah. Or every time John takes a sip, take a sip, take a drink, a whole beer. Yeah. And you basically are gonna have.

3:02:45

Yeah.

3:02:51

25.

3:02:52

She comes back eight hours later from her eight hour spa treatment. It's like, what were you doing?

3:02:52

And you can just catch her up to speed on everything. You watch. And I think they really appreciate that.

3:02:56

But you say you haven't listened to Dwar Casiolia. 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 Dora Keshe? Are their timelines up to date? If not, that's the best Valentine's Day gift you can get them. Up to date. Understanding of what's coming.

3:03:01

But we hope you all have a wonderful weekend. We love you.

3:03:24

Yes.

3:03:27

Thank you for hanging out with us this week.

3:03:28

Yeah. And we will be back Tuesday. Monday is a holiday.

3:03:30

It is.

3:03:34

We're off. Yeah.

3:03:35

Really?

3:03:36

Yeah. Yeah. Market's closed.

3:03:36

I did not know that.

3:03:39

Yeah. I'm learning this for the first time.

3:03:40

Learning this for the first time.

3:03:42

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

3:03:44