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TBPN is a live tech talk show hosted by John Coogan and Jordi Hays, streaming weekdays from 11–2 PT on X and YouTube, with full episodes posted to Spotify immediately after airing.
Described by The New York Times as “Silicon Valley’s newest obsession,” TBPN has interviewed Mark Zuckerberg, Sam Altman, Mark Cuban, and Satya Nadella. Diet TBPN delivers the best moments from each episode in under 30 minutes.
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Speaker 2:Today is Tuesday, 02/17/2026. We are live from the TVBN ultra. I'm the temple of technology, the fortress of finance, the capital of capital.
Speaker 1:That's right.
Speaker 2:Let me tell you about ramp.com. Time is money saved both, easy to use corporate cards, bill pay, accounting, and a whole lot more all in one place.
Speaker 1:It is
Speaker 2:the year of It's year of the fireworks.
Speaker 1:And And we get to celebrate it twice because I think we I remember we talked about it at the beginning of the year Yes. But the Chinese New Year did not start until today.
Speaker 2:It's Lunar New Year. Right? Worshippers burned large incense sticks on Monday outside a temple in Hong Kong to mark the Lunar New Year
Speaker 1:There we go.
Speaker 2:Which falls on Tuesday. People around Asia celebrate the start of year of the horse.
Speaker 1:In the UltraDome, it's the year of the horse every Every
Speaker 2:year, I think so.
Speaker 1:It is. Is the year of the Look at this. We were we were early. We were early Yes. And right Yes.
Speaker 3:On
Speaker 2:horses. Everyone is talking about the Cournot equilibrium. At least Dario, Amade, and Dwarkash Patel are
Speaker 1:And you.
Speaker 2:And me, and some folks on the timeline. We're going back and forth and basically trying to
Speaker 1:get to this question I feel like we should give the context on this on the titling strategy
Speaker 2:Oh, yes.
Speaker 1:Because we call the run of shit we're like, we'll title an essay, Why is No One Talking About the Cournot Equilibrium? Because this one guy that had this super viral Yes. A year or two ago and he's and the title was, Why is No One Talking About Marc Andreessen? Anderson? We were laughing about it so much because he's one of the most talked about
Speaker 2:Oh, yeah.
Speaker 1:Investors Yeah. In venture.
Speaker 2:He's ever list constantly. He's written essays and talking
Speaker 1:about Been viral a million times. Someone that yeah. Someone that everyone in the industry has an opinion on Totally.
Speaker 2:Already. Totally.
Speaker 1:He's not like a Midas Lister
Speaker 2:Yeah. Yeah. Up there.
Speaker 1:But not a lot of people. It's just like everyone's talking about it. But in this case
Speaker 2:Really, I mean, truly, I I do think more people should be talking about the Cournot equilibrium or at least learning about what it means because it is this sort of obscure economic con construct. And it's really, really old. The guy who coined it is he died a hundred and fifty years ago. His name's Antoine Corneau. And the basic idea is that if there's only a few players in a given market, you can think about, you know, any any specific market, lemonade stands or whatever and they aren't competing on price.
Speaker 2:They will compete on supply. And they'll try to predict what their competitors are doing and then respond accordingly. And this is really, really relevant to the AI lab discussion because you can tell that even though all the leaders of the AI lab say, I don't think about the competition. I don't talk about the competition. I'll use general terms.
Speaker 2:They're all obsessed with what everyone else is doing, and they think about it constantly very clearly. And if someone's buying 10,000,000,000 of compute over here, they're gonna counter with eight over there or try and jump to 12. And everyone's sort of keying off of each other. You know, Microsoft pauses. AWS goes all in.
Speaker 2:There's all these, like, horse races. It's why semi analysis exists and provides great, you know, cross functional data.
Speaker 1:Daniel, in the chat, says state actors at work. Again? Apparently, we're having technical difficulties today.
Speaker 4:We'll fight
Speaker 1:for We're back We're back. In every way, but we're working on it.
Speaker 2:Okay. And so, yeah, there's this big question. In outside of tech, there's this there's this discussion that I see that's always funny to me where people would be like, oh, the the the price to earnings ratio
Speaker 1:Brian says they don't want you to talk about
Speaker 2:the They don't want us to talk it. They don't want us to talk about for sure. I like the Chiron two AI labs locked in Corneau battle. And the so outside of tech, there's this discussion. I I saw it first and say, the price to earnings ratio for OpenAI and Anthropic is just simply too high.
Speaker 2:And I was like, earnings? Like, these companies are losing money. They don't have a price to earnings ratio. If you divide by zero blow
Speaker 1:this is gonna blow your mind.
Speaker 2:Yeah. It's it's so much worse than you think. Right? They're not making any money. They're deeply unprofitable.
Speaker 2:These are the most unprofitable companies in human history, I think. But at the same time, there is an economic rationality behind all of this. And what is that economic rationality? Well, when you're running a AI lab, you actually have two businesses that are sort of hiding within the P and L. And so the first, you share this brand, you share the data centers, you share compute, but there's a whole bunch of risks and rewards to the various pieces of the business.
Speaker 2:So first, you have training the models. So you make an upfront investment in a training run that creates a particular model generation, And then that asset depreciates as the frontier moves. And then when a new and better model is released, everyone moves over, you stop reaping the benefits of that, and the value of that model goes much, much lower. How much money is OpenAI making from GPT 3.5? They spent money training that.
Speaker 2:Now, not a ton, but I
Speaker 1:would actually love to know.
Speaker 2:They're probably making almost zero. Who's still on GPT 3.5? I don't even know if the API is live anymore. But GPT four is the really instructive is the really instructive example because I believe that model cost like $100,000,000 to train, and it was really expensive at the time. But then very quickly, they were on a multibillion dollar run rate, and it was very clear that based on the inference margin and subscriptions, ChatGPT Pro, that they made all the money back from GPT-four and more.
Speaker 2:Now there's a question about, okay, well, if they go and spend $10,000,000,000 on training, how quickly will that come back And how much how quickly can they reap that? And there's this game of chicken that's happening. So that's one of them. Then the other side of things is the inference factory. So this is essentially a manufacturing business.
Speaker 2:You have you have variable costs, so GPUs, power, engineering overhead, and then your revenue is subscriptions, API usage, and enterprise contracts. And so when you just look at inference, you see positive contribution margin. And we can see that because we can compare the cost to inference a model of the GPT-five class size or the OPUS 4.5 size. You can see, what does it look like to run an open source version of that model on commodity hardware? Well, it's way, way cheaper than what you pay to Anthropic or OpenAI, so they must have good margins.
Speaker 2:And everyone sort of agrees at this point that inference margins are, in fact, healthy. The question is, how do you balance those two pieces, and when do you risk overinvesting? And that's sort of this Cournot game of chicken that everyone's playing. Now the Cournot equilibrium comes when a small number of labs, an oligopoly, effectively choose supply at the frontier level and then the market clears at a high price for frontier access. So choosing supply in this case means how many data centers get built, how many GPUs get ordered, but also how much low latency capacity is allocated to the top tier.
Speaker 2:So right now, they just OpenAI just did the Cerberus deal. There's Claude Fast, and there's a whole bunch of different modes that will deliver faster inference. And how many of those fast queries you get, how much of the best chips are allocated to a particular tier that you're paying for, is an economic question for the labs. So on the true frontier, there aren't great substitutes, and so price stays high based on customers' willingness to pay for frontier access. So you can just think about it in more simpler terms.
Speaker 2:Like, there's a ton of developers and knowledge workers who are happy to pay hundreds of dollars a month or more, but they always want the best available model. This is most people in executive roles in startups. Right? It's like, yeah, I got my $200 a month subscription. I'll pay $250 or $100 or whatever, a couple $100, and it just makes me better at my job.
Speaker 2:I just do whatever I need to do. But don't give me the old thing. I want the best. I wanna know that the hallucination rate is as low as possible. I wanna know that the when it when it builds me an economic model, it's doing it as best as it possibly can, so I need to spend less time, like, done.
Speaker 1:1% of the time, it makes a career ending mistake.
Speaker 2:Maybe. I No. No. No. I really do.
Speaker 2:There I mean, there are some crazy crazy, like, possible outcomes. We haven't heard too many nightmare stories, but there there certainly have to be out there, like the true hallucinations.
Speaker 1:We need checks and balances.
Speaker 2:Yeah. Yeah. But Can't. Increasingly Yeah. Increasingly, less
Speaker 1:Everyone's gone through the experience of of somebody building a model Yeah. And then being like, I I I don't know Yeah. Why, but it's wrong.
Speaker 2:Yeah. Yeah.
Speaker 1:And then it's usually a battle.
Speaker 2:Yeah. I was I was actually You gotta train you
Speaker 1:gotta train that instinct Yeah. That can just clock this even if you have have no if it just like if it feels off.
Speaker 2:I was talking to a buddy about using AI tools who works in, like, high yield debt, sales and trading and issuance. And he was like, yeah. Like, the models just, aren't that good. And I was like, really? And And he was like, yeah.
Speaker 2:They don't understand, like, q four seven six of the tax code and how it apply. And I was like, okay. Yeah. Actually, that seems like something that they might not be great at. I was like because I I built a toy model with just, like, project out the cash flows, discount them back, and it did a great job.
Speaker 2:And I was like, cool. And he was like, no. I'm, like, 25 levels above that and, like, deep in all these different codes and, like, it's not
Speaker 1:quite Good work, little bro.
Speaker 2:It'll get there. But it's just, you know, the base models are not just gonna be able to, like, one shot that. What do you think, Tyler?
Speaker 4:Fire it back?
Speaker 3:You would imagine that, like, something as, like if if it's just, like, text code, even if it's super complex, you can just put that in the context, and it just does a very good job.
Speaker 2:Yes. But there's
Speaker 3:Like, finding specific facts from a super big document is, like, that's one of the things that models are best at.
Speaker 2:Yes. But there's there's a lot of there's a lot of you're laughing at the chat.
Speaker 1:Ethan. Ethan says computer fix TBPN. Use Gunna and Grok.
Speaker 2:Can fix us. We're back. We're back. It's yes. But I there are there are nuances to the tax code and to a lot of legal documents that where the law says one thing, but it's but it's but it's implemented in a different way or it's not enforced or the or or some regulatory organization has enforcement discretion or there's some understanding.
Speaker 2:I mean, even if you just go into, like, training on, you know, IP, it's like if you have really good lawyers, you can figure out, okay. Well, they'll come to the table. We'll be able to negotiate this. This will be the price. This will be the settlement.
Speaker 2:So even though the model might say, like, don't do that, like, you have a chance to do it, there's whole bunch of different reasons why. But, yes, I I I generally agree with you. This is, like, a six month away thing. Not but it's just, like, the current
Speaker 3:the current Well, it's the current thing, but with, like, good, you know Yes.
Speaker 2:Yes. And and maybe some more harnessing and more some and and better context. Anyway, the question is, like, where does this all go? What is the natural state of equilibrium in the longer term? Right now, they're locked in Cournot, where there's a whole bunch of companies, individuals that want to buy the best AI inference possible.
Speaker 2:They want the best tokens. They want the best deep research reports. They want the best code, and they're willing to pay for it. But we're supply constrained. And so OpenAI brings a certain amount of GPUs and tokens and supply to the market, and then Anthropic also does.
Speaker 2:And the whole core know thing is that they're all keying off of each
Speaker 1:other and
Speaker 2:saying, okay. If they're offering this much, I'm gonna offer that
Speaker 1:much to be and to be clear, so having a product
Speaker 4:Yes. Not just
Speaker 1:an API business gives you leverage. Because Yes. At some point, the models are smart enough where you don't need to train them you don't need to train a model that is 4% better because people are still coming to your application and having a good product experience. Right? Yes.
Speaker 1:So historically, one of the critiques to Anthropix business Mhmm. Was that they have to just be on this constant constant fly,
Speaker 2:you
Speaker 1:know Mhmm. Sort of hamster wheel of training the best model Yes. Because they have an ape they're they're the majority of their business is this API business. They're not Mac.
Speaker 5:We just
Speaker 1:swap it out for a smarter model. Yeah. That said, they have Cloud Code now Yep. Which gives them some more Yeah. Leverage Yep.
Speaker 1:Over the market.
Speaker 2:And the the really interesting thing is that Dario is now talking about being near the end of the exponential or maybe producing, like, the final models because we we we've talked to a few people about this, but it's very unclear if if it's possible to create like a super intelligence that's like 5,000 IQ. It might just be they get good at all knowledge work and they can answer all tasks, but it's like the digital guy. And so at that point, it does commoditize, and you drop out of Cournot equilibrium, and you become more customers are more aggressive about switching to cheaper models to cut costs because the frontier is now commoditized in the entire backlog. Everyone is at the frontier, basically. And so in that scenario, you switch over to Bertrand competition, which doesn't really mean that profits go to zero, but there is more competition.
Speaker 2:And it looks a lot more like the hyperscaler cloud market, which is, I think, what people have been sort of signaling towards. And also, it sort of explains why a lot of the VC firms are getting in multiple companies because they don't think it's going to be winner take all anymore. They think it's going to be much more oligopolistic for the long term, and there will be competition between the major three or four labs that will and it will be much more about how can you marshal enough supply, create a huge barrier to entry. Like, you and I could start an AWS competitor tomorrow, but it's gonna be extremely expensive to bring up data centers that just serve web apps everywhere, let alone AI stuff. Right?
Speaker 2:Building all those data centers. You're thinking what I'm thinking? You're thinking you're thinking eight minutes I was hanging You were saying when does Deepgram
Speaker 1:was talking with my buddy my buddy Ben on Sunday. And he was we we both live in Malibu. He was thinking of just getting some chips and setting up Malibu inference.
Speaker 2:There we go.
Speaker 1:Just just the name alone. It sounds like you could get at least at least Malibu inference
Speaker 2:That's really funny.
Speaker 1:Would would be a good would be a beautiful name for a Neo Cloud.
Speaker 2:Yeah. It's funny. And so there is a question about in the final models, will there be differentiation? What does differentiation look like? There's a potential for differentiation around, okay, you get a model that's really good at bio or math or engineering or code or writing.
Speaker 2:That's possible. Another possibility is that there's just differentiation on quality, latency, safety, enterprise tooling, and you wind up with a small number of vertically integrated firms. And so in that scenario, I feel like OpenAI's recent moves make a lot of sense. Cerebris offers differentiated product around speed. Peter from OpenCLaw joining makes a lot of sense around building orchestration products that can route to particular models.
Speaker 2:So a you know, the next generation of the clawed code router that can route you to specific APIs and act as a model router on top for the agentic programmer AI assistant use case. You already see the model router happening in the ChatGPT consumer app. We haven't really seen that in the desktop CLI app. And so there's something interesting there. And then Frontier, OpenAI Frontier, that forward deployed engineer thing, that digs deeper into the enterprise and probably gets them, you know, more more hooks in there, more more pricing power.
Speaker 1:The the chat's going off today, Ryan says, the Cournot company of Malibu.
Speaker 5:Let's do it.
Speaker 2:I love it. Let me tell you about CrowdStrike. Your business is AI. Their business is securing it. CrowdStrike secures AI and stops breaches.
Speaker 2:Let's let's play the clip of Dwarkesh Patel and Dario Amade discussing the economics of AI Labs because I think it's informative. And this is where the whole Cournot current thing came from because Dario dropped that phrase.
Speaker 1:And I won't So when you said why is no one talking about it?
Speaker 2:It was literally everyone that listened to the biggest podcast of the week. But I'm explaining it. Let's play it.
Speaker 6:Industry here. Like, we have a you know, let's just imagine we're we're we're in, an economics textbook. We have a small number of firms. Each can invest a limited amount in or like each can invest some fraction in r and d. They have some marginal cost to serve.
Speaker 6:The margins on that the profit margin the gross profit margins on that marginal cost are, like, very high because because because inference is efficient, there's some competition, but the models are also differentiated. There's some there's some, you know, companies will compete to push their research budgets up, but, like, because there's a small number of players, we have the what is it called? Cournot equilibrium, I think is what the Let's go.
Speaker 2:Cournot equilibrium. Equilibrium is.
Speaker 6:The point is it doesn't equilibrate to perfect competition with with with with with with with zero margins. If there's like three firms if there's three firms in the economy, all are kind of independently behaving behaving rationally, it doesn't equilibrate to zero.
Speaker 1:Help me understand that because right now we do have three leading firms and they're not making profit.
Speaker 6:That's a good question. Yeah. What is changing? Yeah. The the again, the gross margins right now are very positive.
Speaker 6:What's happening is a combination of two things. One is we're still in the exponential scale up phase of compute. Basically, what that means is we're training like a model gets trained. Let's say a model got trained that costs $1,000,000,000 last year. Then this year, it produced $4,000,000,000 of revenue and cost $1,000,000,000 to to to to inference from.
Speaker 6:So, you know, again, I'm using stylized number here,
Speaker 2:but, know, 75 numbers. Let me just paint a random number.
Speaker 6:Gross gross margins and, you know, this this 25% tax. So that model as a whole makes $2,000,000,000, but at the same time, we're spending $10,000,000,000 to train the next model because there's an exponential scale up, and so the company loses money. Each model makes money, but the company loses money. The equilibrium I'm talking about is an equilibrium where we have the country of geniuses, we have the country of
Speaker 1:geniuses but and data
Speaker 6:that that model training scale up has equilibrated more. Maybe maybe it's still it's still going up. We're still trying to predict the demand, but it's more it's more leveled out.
Speaker 2:Let's go. Let me tell you about Turbo Puffer, serverless vector and full text search, built from first principles in object storage, fast, 10 x cheaper, and extremely scalable. There is another fun clip that we should watch from A Beautiful Mind. Jordy, have you seen A Beautiful Mind? It won the Oscar for best picture, I believe.
Speaker 2:It's about the mathematician John Nash. Have you seen A Beautiful Mind?
Speaker 3:I have not.
Speaker 2:Wow. Unc status over there.
Speaker 1:You would have In person. I was walking on the beach with Senra on I think Saturday. And we walked by an incredibly famous, one of the top movie directors of the last probably ten years. Really? And Senra was like, do you do you see that?
Speaker 1:And I was like, see what? It's a guy with a dog.
Speaker 2:That's hilarious. I I feel like that your beach tour has been really star studded lately. This is a different from the previous one you mentioned. Correct?
Speaker 1:Yes. Yes. Wow. Yes.
Speaker 2:That's remarkable. Well, let's pull up the clip from
Speaker 1:Longcoming, gentlemen.
Speaker 2:It's from a beautiful mice.
Speaker 1:May I ask? You might wanna stop shuffling your papers for five seconds. Is that Eric Lyman?
Speaker 2:It's Eric Lyman.
Speaker 7:Gentleman here.
Speaker 2:In the in the ramp biopic, we got we got we got our cast right here. Oh. This is the original, like, Lux Maxine movie. I don't
Speaker 7:know if she should be moving in slow motion.
Speaker 1:Oh. Will she want a large wedding, you think? Should we say swords, gentlemen? Pistols at dawn?
Speaker 8:Have you remembered
Speaker 9:nothing? Recall the lessons of Adam Smith, the father of modern economics.
Speaker 1:In competition, individual ambition serves the common good. Exactly. Every man for himself, gentlemen.
Speaker 7:And those who strike out
Speaker 1:are stuck with their friends.
Speaker 9:I'm not gonna strike out.
Speaker 1:You can lead a blonde of water, but you can't make a drink.
Speaker 9:I don't think he said that.
Speaker 1:Alright. Nobody move. She's looking over here. Why is she looking at Nash?
Speaker 9:Oh, god. Alright. He may have the upper hand now, but wait until he opens his mouth. Remember the last
Speaker 1:episode? Oh, yes. That was one of the history books. I
Speaker 2:think this this is very very stylized.
Speaker 8:Are you talking about?
Speaker 2:And completely apocryphal. Like, he definitely thought of this theory, but not at a bar.
Speaker 7:We block each other. Not a single one of us is gonna get her. So then we go for her friends. But they will all give us the cold shoulder because nobody likes to be second choice. But what if no one goes for the blonde?
Speaker 7:We don't get in each other's way, and we don't insult the other girls. Marked. That's the only way we win. That's the only way we all get laid.
Speaker 2:So he's describing the prisoner's dilemma.
Speaker 7:Adam Smith said
Speaker 2:Where everyone must work together. Best result comes
Speaker 7:from everyone in the group doing what's best for himself. Right? That's what he said. That's right. Incomplete.
Speaker 7:Incomplete. Incomplete. Okay. Incomplete. Because the best result would come from everyone in the group doing what's best for himself.
Speaker 1:And
Speaker 7:And the group.
Speaker 8:Ashley,
Speaker 9:this is some way for you to get the blonde on your own. You can go to hell. Governing dynamics, gentlemen. Governing dynamics. Adam Smith.
Speaker 7:What's wrong?
Speaker 1:Yep. There we go. Careful. Careful.
Speaker 7:Thank
Speaker 2:you. Tiz. So good.
Speaker 1:Anyway, very fun. Dave says, just joined the stream. We watching a movie. Yeah. Movie day.
Speaker 2:Movie
Speaker 1:We should bring back bring back movie days in school. Yes. I mean, was iconic. That's great. Rainy day, substitute Gladiator and
Speaker 2:Latin class. That was the best. Really quickly, let me tell you about vibe.co. We're d to c brands, b to b startups, and AI companies advertise on streaming TV. Pick channels target audiences and measure sales just like on Meta.
Speaker 2:Anyway, very, yeah, very fun, Nash equilibrium. Lots of game theory going on in the, in the AI wars right now. Everyone's trying to figure out, how far to push it. There's a fair amount of risk. There's still the Cournot game of chicken around who will invest the most in advancing the frontier.
Speaker 2:But the end state looks a lot more durable than a than pure model commoditization and the perfectly competitive situation that many were predicting a few years ago. So if you go back to, like, 2023, a lot of people were saying, like, the models will commoditize, and there will be no value there, like, no profits because, like, the deep seek moment, and it'll all be running commodity hardware. That doesn't seem that likely. It seems like the labs will turn into sort of new hyperscalers. There will be increased competition, but still very, very good businesses a la cloud.
Speaker 2:So anyway, fun to dig into some little Econ 01/2001 or 01/2002, depending. But let's go to the timeline.
Speaker 1:Puko Capital says, I thought Dourkech had a good point that software engineering is the only job where the full context needed to do the job is available to an AI agent via the code base. And I didn't think Dari had a good answer for why automating other jobs will be as easy. This got a bunch of a lot of people reacting, disagreeing generally that all of the full context needed to do the job is available. But I do think it's Yeah. Something we need to figure
Speaker 2:were debating this because there was a post that was just sort of like a Wojak reaction that was just making fun of this. And it wasn't clear if they were saying that, like, that they were agreeing or disagreeing. But basically, my my take was, well, it's possible that a lot of the, you know, the full context needed to do the job of a lot of a lot of different white collar jobs is in fact logged. It's just logged in the final product, which is like a deck or a spreadsheet or a decision, and then a whole bunch of emails, a whole bunch of Slacks, and then a whole bunch of Zoom calls that's recorded. And so, yes, if you're running a business where a lot of work gets done in smoky bars late at night and and, you know, back alley deal making, sure, that's going to be harder to automate.
Speaker 2:But in the world where it's someone sitting in front of a computer and there's a screen recorder running, like, you should be able to pull up most of the context. At the same time, you can't just snap your fingers and go back and get every decision that was made in the eighties that allowed Coca Cola to become a dominant soda maker. But you You can't
Speaker 1:can't if we get
Speaker 2:If we literally can't
Speaker 1:win it. People on calls just being like knowing the call is being recorded and used to train something to replace them, they're just like, I'll tell you offline.
Speaker 2:I'm not
Speaker 1:in speak speaking this secret in
Speaker 2:Yeah. Yeah. Record. Golf this weekend? You wanna play golf?
Speaker 2:Really quickly. Figma, ship the best version, not the first one with Figma. Introducing Claude Coe to Figma. Explore more options. Push ideas further with Figma.
Speaker 1:But this was funny. Buko said, basically, a non zero chance of Joe Weisenthal victory where software engineers write themselves out of a job first and everyone else has the boring parts of their job automated. Joe of course was joking, just saying. Well, of course software engineering is being automated. So easy.
Speaker 2:It's so easy. Yes.
Speaker 1:It is The debate around the posture Yes. Dwarkesh. Dwarkesh, his posture was been
Speaker 2:having a gym a lot. He looks fantastic. I I I love this sweater. The crew neck works really well. The the the pushed up sleeves is a particular choice.
Speaker 2:Didn't translate into that Chad Wojak, but he looks fantastic here. And the Aeron chair is certainly helping with the posture. Lot of lot of fun on the timeline looking at the the Luxemagging or whatever, the Luxemaxing. I don't even know.
Speaker 1:Can't This was
Speaker 2:Framemogging. That's the
Speaker 1:Yeah. Framemogging. He he was bringing up the the example of of a video editor Yeah. Saying, yeah, but when will the models be good enough to edit videos well? Yes.
Speaker 1:Pick out moments? Yes. Give me two years and another 500,000,000,000. This is I mean We've we've tried every tool. There is.
Speaker 1:Yeah. They can't do it yet.
Speaker 2:Tricky. I don't know. I don't know what's
Speaker 1:And it's and it's not even that we're we're not trying the tools to replace the people on our We're trying to make them have higher output. Yeah. But to date
Speaker 2:I don't know if there's something super sticky. I mean, does seem like one interesting thing is that there isn't there aren't a lot of open source, like, premier profiles. Like, I I've edited a ton of videos for YouTube. There's a whole bunch of cuts in there, what I cut out, what I didn't. You could have that record.
Speaker 2:It's not stored in GitHub. Like, it's just a you can't necessarily train on it. You can train on the final product and and understand, but you don't understand what actually got left on the cutting for cutting room floor. There's this whole concept of, like, kill your darlings. Like, when you're in the edit, Like, you need to be cutting more.
Speaker 2:You're like, oh, I like that shot. It's so cinematic. It's so cool. But does it actually advance the story? No.
Speaker 2:So you cut it down. I was watching The Matrix this weekend, and there's this amazing shot of when Neo and Morpheus are going to visit the, the the Oracle. Is that one? The Oracle? And and Neo is that the one?
Speaker 2:Oracle? Yeah. The and and they and they reach for the doorknob, and the doorknob has this perfect reflection, and the reflection shows Neo and Morpheus. And they had to do this crazy VFX shot to hide the camera in more what looks like Morpheus' coat. Because if you point a camera at a mirror, you see the camera.
Speaker 2:And you don't want to see the cameraman there. That ruins the shot. And so they did all this crazy stuff to, like, to, like, you know, cover up the camera. And I'd seen the behind the scenes and been like, wow. That's really impressive.
Speaker 2:And in my memory, thought it was like, oh, it's such an important shot. They probably, like, lingered on that for, like, five seconds to really let it sink in. Like, they're they're pulling a trick on the audience. It's beautiful. Yep.
Speaker 2:It's like half a second. And they did all this work, and then they knew that, like, from a story perspective from a storytelling perspective, you don't wanna hang out and watch a picture of a doorknob for five seconds. And so all these decisions, like, they sort of get chronicled, but they don't get neatly organized in the way that a GitHub log does with with pull request discussions and what happens. It'll be it'll be difficult. So maybe two years and another $5,000,000,000 does it, but it's coming.
Speaker 2:So we'll we'll keep monitoring it. Let me tell you about the New York Stock Exchange. Wanna change the world? Raise capital at the New York Stock Exchange. We have we have a special guest joining.
Speaker 2:John Karamanica is joining. That's good to music. But I wanted to I wanted to tee up his appearance with a with a little music review that I found in the newspaper today. The algorithm wants you to grieve. Rest in peace, my granny.
Speaker 2:She got hit by a bazooka, a title that functions as its own thesis statement, is the kind of song that resists every framework we've built for understanding virality. It is not quite parody, not quite sincerity, not quite meme. It exists in some fourth space where emotional register becomes irrelevant, and the only metric that matters is whether the thing lodges itself in your prefrontal cortex like a splinter. The melody, if we're being generous enough to call it that, is a three note loop that sounds like it was composed on a Fisher Price keyboard during a power outage. The vocal delivery is flat, almost affectless, a kind of anti performance that paradoxically demands more attention than virtuosity ever could.
Speaker 2:The lyrical content is, well, the title, repeated with conviction. And yet something is happening here that's worth taking seriously or at least worth resisting the urge to dismiss. The song collapses the distance between tragedy and comedy so completely that neither category survives the collision. It's grief as non sequitur, eulogy as punchline, memorial as munition. The bazooka isn't just absurd.
Speaker 2:It's so specifically absurd that it loops past irony and arrives somewhere strangely earnest. Nobody's grandmother has ever been hit by a bazooka. The scenario is impossible. And impossibility, it turns out, is its own form of tenderness. A way of saying loss is so incomprehensible that only nonsense can hold it.
Speaker 2:Or maybe it's just a guy yelling about a bazooka. The Internet doesn't require you to choose, but we'll be following this story. So thanks for
Speaker 1:We'll John's take on is
Speaker 2:the song of the week. And the ad platform of the week is AppLovin. Profitable advertising made easy with axon.ai. Get access to over 1,000,000,000 daily active users and grow your business today.
Speaker 1:Andrew Reid says horses don't stop, they keep going.
Speaker 2:Wait, did he actually say that? Yes. No way.
Speaker 1:Yes. In response to 2026 being the year of the horse.
Speaker 2:I love it.
Speaker 1:One of the greatest lyrics of all time.
Speaker 2:Originally, to to to to explain the joke, it's a it's a young thug song. And the the actual lyric is hustlers don't stop, they keep going. Oh, really? But it sounds like horses. And so people put horses don't stop, they keep going.
Speaker 2:And they show the AI generated image of the horse bench pressing. And it's incredibly inspiring.
Speaker 1:There's a lot of young dog songs that are hard to really
Speaker 2:decipher. A 100%.
Speaker 1:Let's hit the size gong Yes. For this Pennsylvania Girl Scout. Six years old, breaks record selling 87,000 box boxes of cookies. She's unstoppable. Unstoppable?
Speaker 1:That is How much
Speaker 2:is that? What's the ARR?
Speaker 4:Break it
Speaker 2:Break it down.
Speaker 1:Is it $12?
Speaker 2:That's a lot. How long does this six years old. Wow. What what enabled this incredible scale? Was it potentially Shopify?
Speaker 2:Shopify is the commerce platform that grows with your business, lets you sell in seconds online, in store, on mobile, on social, on marketplaces, and now with AI?
Speaker 1:Estimating that it's somewhere around $600,000 of sales
Speaker 2:It's amazing.
Speaker 1:At only six years old. Really incredible stuff. Heartwarming.
Speaker 2:That's awesome.
Speaker 1:India's Adani Group to invest a 100,000,000,000 in AI infrastructure.
Speaker 2:We gotta hit the gong again.
Speaker 1:Hit it again. Hit it again. Indian government's investment will be a boost to the country's ambitions to become an AI power. India's Andani Group, an energy and logistics giant said it would invest a $100,000,000,000 to develop large scale data centers by 2035, the largest such commitment in India so far. Michael.
Speaker 1:Tyler, what do you think about the timing here? Is this gonna be too late? Are the clankers gonna like, is 2035? How how are we looking there? Is that that's I mean, it's singularity.
Speaker 3:Yeah. I I'm very bullish on on the clankers coming pretty early. Mhmm. So, you know, time will tell, I guess.
Speaker 2:I'll see.
Speaker 1:I cannot wait to pull up this clip.
Speaker 2:It is it is a big number that I feel like a lot of countries have been teasing big numbers, but
Speaker 10:this is Yeah.
Speaker 1:They're kind of mugging Macron.
Speaker 2:Yeah. This is like a really big number. You you see a bunch of, like, multibillion dollar deals, multibillion dollar releases, But this is, a serious, serious, serious investment. So, you know, good good news.
Speaker 1:For many countries, one of the biggest concerns about the looming AI era is that it will deepen existing technology divides in which tech services are developed by companies in a few countries. Some countries have also expressed concerns about how large tech firms will consume data generated by their citizens to build their AI products. India is focused on making sure that startups and researchers use AI to solve pressing development challenges and paving the way for its businesses to become providers of global AI services. India will shape solutions not just for India but for the world, said Indian Prime Minister Modi in a social media post today. Yandani Group said the dedicated computing capacity it is building will support Indian large language models and ensure data generated in India is stored locally.
Speaker 1:Let's see how the stock's doing. Up up 2% today.
Speaker 2:Is it a $28,000,000,000 company? Do I have that right? I don't know. It's it's like $22,500,000,000,000.0 INR. So I think that's about 28,000,000,000.
Speaker 2:So this is a huge number.
Speaker 1:Raghav says, Andani will more than likely use government leverage. Sure. Government backed data centers.
Speaker 2:There we go.
Speaker 1:You happy about that, Tyler?
Speaker 2:Government backstop coming to India.
Speaker 1:Backstop. Let's go.
Speaker 2:Before we move on, let me tell you about Restream. One livestream, 30 plus destinations. If you want a multistream, go to restream.com.
Speaker 1:Micron is spending 200,000,000,000. Congratulations for saying the biggest number. Micron Micron is spending 200,000,000,000 to break the AI memory bottleneck. For decades, memory chips were low margin commodity products. Now the industry can't make enough to satisfy data center's hunger.
Speaker 1:Just like
Speaker 2:this one company is like, yeah. We're gonna spend twice as much as India. This has the Adani Group.
Speaker 1:Boise, Idaho. Each afternoon at around 04:30, the earth hears shakes from a series of controlled explosions as engineers blast through basalt bedrock to flatten out the ground underneath in a gigantic new semiconductor factory. That's cool. Let's give it up for Idaho. Yeah.
Speaker 1:We don't talk about Idaho enough. Yeah. Micron Technology is the largest American maker of memory chips, the tiny slices of silicon that store and transfer data and help power everything from smartphones and car computers to laptops and data centers. Micron is rushing to add manufacturing capacity to avert the biggest supply crunch the memory industry has seen in more than forty years. In Boise, where the company is based, Micron is spending $50,000,000,000 to more than double the size of its four fifty acre campus, including the construction of two new chip factories.
Speaker 1:The first fab's inaugural wafers are expected to roll off the factory line in mid-twenty twenty seven. So this is their first fab or the one that they're spending the 50,000,000,000 on right now?
Speaker 2:I think the new one.
Speaker 1:Okay. So that's pretty quick.
Speaker 2:Yeah. Did you hear that the PS six, the PlayStation six is now delayed because of memory shortages? 2029 2028, 2029, it's still a rumor. Maybe they'll you know, maybe this solves it and they can get it out earlier. But pretty pretty big delay to 2029.
Speaker 2:They really don't refresh
Speaker 1:created a trillion gamers. No. Seriously, I think adding insult to injury
Speaker 2:Yeah. To The gamers might actually Rise the gamers might rise up. They might be an important voting block.
Speaker 1:Lot of
Speaker 2:them are a lot of them are of of age to vote and a lot of them don't would would rather have new gaming hardware than, you know, necessarily AI slop in the feed. And they're like, yeah, I I I can't afford the new PC that I wanted. What do you think?
Speaker 3:Yeah. I I don't know. I mean, I I feel like this says a lot about how good the PS five is. Right? Because they can, like, afford to just, like, postpone the PS six.
Speaker 3:What games Oh, now you don't want technological progress?
Speaker 2:Wow. I want
Speaker 3:it to go to the data centers. I don't want don't care about, like, the next like, game graphics have, like have they gotten that much better in the past, like, five years? Like, yeah, maybe, but it's, like, Yeah. For the actual gameplay, is it that important if, like, the actual pixels are,
Speaker 2:Yeah. You know Realistically, a lot of this stuff should be moving to the cloud soon if it's not already.
Speaker 3:Yeah. Like the it was the Meta Quest VR. I forget. Oh, yeah. Xbox Connect.
Speaker 3:Xbox edition. Yeah. Yeah. And it it was all in the cloud and it was like totally fine.
Speaker 1:It was
Speaker 2:it was Low latency. Yeah. And then if you're running in the cloud, you can upgrade the hardware. And in theory, you should be able to run like a Gen AI uprising pass to make it more photoreal. And I feel like that's gonna be where more of the the juice is squeezed out of the graphics than just continuing on the traditional path of like more pixels, more ray tracing.
Speaker 2:It'll be make a really beautifully, you know, designed video game that works really well, really tight deterministic interactions, so it's satisfying. And then give it a give it a layer
Speaker 1:of time. Like gotta a ram trader on the show. Like really somebody that's in the thick of of deal making in the space.
Speaker 2:There's a couple of folks that did semi analysis that cover it. One of them just went on Oddbots.
Speaker 1:Let's do it. Get them on the show. Let's
Speaker 2:do it.
Speaker 1:Let me tell
Speaker 2:you about Graphite. Code review for the age of AI. Graphite helps teams on GitHub ship higher quality software faster.
Speaker 1:That's not all near Sir Cues. Micron just broke down broke ground. They just broke down in Siri. No. They just broke ground on a $100,000,000,000 fab complex that represents the state of New York's largest ever private investment.
Speaker 1:Late last year, Micron announced a $9,600,000,000 fab in Hiroshima, Japan. Cool. While competitor SK Hynix announced in January that it would build a $13,000,000,000 fab in South Korea, in addition to a $4,000,000,000 manufacturing complex it is building in Indiana.
Speaker 2:This is interesting. I feel like this is acceleration in CapEx from the memory makers, but this I wonder how TSMC responds to this because the big criticism of TSMC is that they are increasing CapEx, but the rate at which they are increasing CapEx is decelerating. And so they're not really keeping up with the exponential growth in compute that every AI lab, every data center builder, every memory maker is pushing towards. And I wonder I wonder, like, what do they know? What do they know?
Speaker 2:Or TSMC is being so so conservative. I mean, they they might just have the AI industry in a chokehold. And so if there is a bottleneck, they can just raise prices. But they also might, you know, screw everything up by not investing enough, and then we get to some sort of solid bottleneck for a while, and we can't actually roll
Speaker 1:out more. Well, let's get someone on from semi analysis tomorrow to talk about memory. Moving on, Lucas Shaw was on a tear over the weekend reporting on the Warner Brothers Paramount conversations. He says this morning, Warner Brothers is going to resume talks with Paramount after two months of rejecting them playing mind games. The company still says it's committed to Netflix, but needs to find out just how much the Ellisons will offer.
Speaker 1:He originally reported on this Sunday Yeah. But it's being confirmed today. Again, we kind of knew this was gonna happen. If the Allisons had been saying, we're making a we're giving you a big number but it's not our biggest number. It's not our best and final.
Speaker 1:So no surprise here. Paramount has now just eked out a lead on who will successfully take over Warner Bros. Over on Kalshi. They're sitting at 49% chance
Speaker 2:Mhmm.
Speaker 1:With Netflix at 37% and then none before July 2027 at
Speaker 2:This is such an interesting flipping ing here. I was
Speaker 1:Yeah. Talking this to about flip happened
Speaker 2:this weekend and he was like, yeah, I think there's just too many people that are against Netflix for a variety of reasons that it'll reopen the Paramount conversations. And specifically, I was like, but YouTube, YouTube. And he was like, no one buys that argument. Like, everyone thinks about the entertainment industry as its own thing and then social media, tech, TikTok, Instagram, YouTube as a separate thing. And no one is making that comp.
Speaker 2:It's just Yeah. All in on much.
Speaker 1:YouTube is not a you know, having asked Ashley Vance, how do you feel about having kind of one less big buyer Yeah. In the buyer pool of for documentaries. Yeah. He was like, not great. Yeah.
Speaker 1:Already bad. This would be worse. But YouTube is not a buyer of IP. Yep. They host content and serve it to people.
Speaker 1:So it's a tough argument to make even though they've been absolutely on an insane tear from a from an overall watch time standpoint.
Speaker 5:Yeah. Me tell you
Speaker 2:about hold on. Let me tell you about MongoDB. What's the only thing faster than the AI market? Your business on MongoDB. Don't just build AI, own the data platform that powers it.
Speaker 1:AJ says Grace Blackwell is a beautiful name for a baby girl. And I totally agree.
Speaker 2:I mean, isn't that because it's actually the name of a girl? Right? Like, isn't Grace like, the name like, they're like, the chips are named after real people.
Speaker 1:Who's
Speaker 2:Well, there's like Ada Lovelace. I wanna say Trevor Grace Hopper. Yeah. Grace Hopper.
Speaker 3:So it was And David Harold Blackwell.
Speaker 2:David Blackwell. I always think Trevor Blackwell because he's a YC partner, but he did not invent the Blackwell. But Grace Blackwell is a beautiful name. Vera Rubin too. Vera Rubin is also the name of a female mathematician, I believe.
Speaker 1:The only person I can find named Grace Blackwell is an audio designer and composer based in The UK. So gonna have a rough go on the SEO front.
Speaker 2:Yeah. Let's flip over to Claude Bot. Kent Dodd says, name's the thing Claude Bot. Claude asks for a rename, renames to OpenClaw. OpenAI buys it.
Speaker 2:Legendary, legendary couple weeks. I was looking back on, like, when did we talk to Peter? It was like two weeks ago. That was
Speaker 1:when Feels like two months ago.
Speaker 2:Feels like two months ago. Things are moving very, very fast. Now, no confirmation on on buying. It's an open source project. They're keeping it open source.
Speaker 2:There's a whole bunch of different
Speaker 1:names Dave, Dave Moran, I remember reading, is going to step in to, I believe, run the foundation that will steward the open source project. And then Peter's obviously joining OpenAI. This wasn't super surprising to me when you looked at the potential places that he could land. It felt like there was he he had talked about like, hey, I'm kind of losing money on this. And he I our takeaway from the conversation is this is a guy that just wants to keep shipping, get get this product into the hands of as many people as possible.
Speaker 1:Yep. And when you looked at the kind of buyer pool, you know, he was he was coming to the West Coast. You can assume that he was making the rounds.
Speaker 2:Meta But on Lex and was like, yeah, I'm talking to OpenAI and Meta. It's just like a crazy thing to say.
Speaker 1:And Meta Meta always felt like a somewhat of a long shot because even though I think I'm sure he's done very well from this Yeah. It didn't feel like dollars were his number one priority. It's very possible that Zuck would have been willing to to overpay or pay whatever price needed to get him on board. Zuck had just also acquired Manus Yep. Which like feels like his like agents team Yep.
Speaker 1:Right? And Manus has already responded by rolling out some Yep. Open Claw like functionality. Yeah. And so that that didn't make sense.
Speaker 1:I think people were expecting Anthropic to make a move. Part of that is like Anthropic just had so much mind share Mhmm. And been on an insane run Mhmm. The last month or so. Mhmm.
Speaker 1:And so I think people and and the name. Right? Peter also at multiple points said Anthropic didn't send their lawyers.
Speaker 2:They sent
Speaker 1:an individual. But it got turned into this meme that Anthropic Cool. Had like really come and and and like really made made his life difficult. I think they were like, hey, this is gonna be con confusing to consumers. Yeah.
Speaker 1:And then the other thing is Peter's over and over and over talked about how much he loves Kodex. Like Yeah. He talked about that on our show. He's been very vocal about it. Yeah.
Speaker 1:Like he likes building with Kodex. And so I think when you understand all these different factors where not entirely financially motivated Mhmm. I'm sure that was a factor Mhmm. But not entirely financial financially motivated. So saying the biggest number is not gonna get them to make a move.
Speaker 1:Mhmm. OpenAI with with somewhere around a billion consumers that use these product, you know, that are using products in the in the ecosystem today. That creates an exciting opportunity for him to come in and actually roll this out to as many people as possible. And you put all these factors together and him landing there makes a lot of sense.
Speaker 2:Yes. Let me tell you about Gemini three Pro, Google's most intelligent model yet. State of the art reasoning, next level vibe coding, deep multimodal understanding. Alex Hermosy chimed in on the Open Clawed Bot discourse. What did he say?
Speaker 1:He says, I'll take this day off to figure out this whole Open Claw thing, every entrepreneur on President's Day weekend. We've talked about this on the show before. Long weekends are really good for AI progress and AI diffusion because people have a few less meetings. And they say, hey, maybe I can mess around and figure this thing out.
Speaker 2:It really is remarkable how quickly Clawd Bot, Open Claw broke through the discourse. Like, I was at dinner at a steakhouse like last Wednesday and I overheard a conversation with just a couple guys in suits who I don't think work in tech talking about different models and how they wanted to use Open Call and they were thinking about getting Mac Minis. Like, it was like, it really did break through beyond
Speaker 1:Our lawyer. Our lawyer. Yeah. Doesn't work at a he works at an entertainment focused law firm. He got a Mac Mini, set it up.
Speaker 1:And so, yeah, it's very mainstream. I did see some people reporting that the Mac Mini had sold out in their local area too. It's not fully sold out by any means. But you look at the the the traction on GitHub and you look at, yeah, just the overall demand and and how kind of like mainstream at least the the the concept of this has gone. Yeah.
Speaker 1:And Apple's overall production numbers on the device. I mean, I I think we can I think we we could enter a world where where at least the ones the more in demand models are are sold out?
Speaker 2:Yeah. Petition for three day weekends to speed up AGI timelines Probably would work for sure. West Fumblegate. Fumblegate. Did Anthropic fumble Open Claw?
Speaker 2:Darius says, don't think about you at all. Probably overstated. It doesn't seem like they it was like key to their strategy. They're sort of just focused on their own thing. I don't know.
Speaker 2:It doesn't it doesn't seem like like, oh, they completely fumbled.
Speaker 1:Yeah. Part part of this was the original naming Claude bought. Right? But but when you look at how many different projects Peter shipped, it's not like he was thinking at every moment, oh, I have to name this because it's going to get a million GitHub stars in He a was just ripping products, building really quickly. And and it wasn't even Claude wasn't the default Yeah.
Speaker 1:No. In in in OpenCLO ever.
Speaker 2:Yeah. Yeah. Codex was actually the the the number one. And there are like 10 LLMs that you can choose from when you when you actually set it up. It very much seems like he's just having fun with the name.
Speaker 2:I mean, the fact that he was calling it Molt Bot for a while is just tells you
Speaker 1:That was a great
Speaker 2:That was a great
Speaker 1:twenty twenty four hours.
Speaker 2:Four hours. But seriously, like he I don't think he was like, yo, I need a branding agency. I need to think of the name that will go forever. It's just like, yeah, this is like a lobster meme. It's fun.
Speaker 1:Wes Winder says LOL Meta couldn't acquire Open Claw, so they pulled a classic Zuck move. Just cloned the whole thing. Then it added as a feature to an existing product. Surprise, they didn't try to shove this into Instagram. So Manus announced Manus Agents yesterday.
Speaker 1:They moved quick. Your personal Manus?
Speaker 2:Manus.
Speaker 1:Manus. Now inside your chats. Long term memory, full Manus power, create videos, slides, websites, images from one message. Your tools connect at gmail, calendar, notion, and more. Available now in Telegram.
Speaker 1:I'm just I would assume. It's surprised they wouldn't roll this out into WhatsApp.
Speaker 2:Yeah. They they don't even own Telegram. Available now on wait. That is so confusing.
Speaker 1:I think I think it's possible that WhatsApp didn't have the didn't have some functionality that they needed to actually do this integration
Speaker 2:Yeah.
Speaker 1:And they're moving so quickly? Like, they they they seem to have turned this I don't think I think like Wes is maybe overstating a little bit the classic Zuck move. You can imagine like Manus would have done this probably independently.
Speaker 2:A 100%. You were calling this. Manus is a good acquisition because if in the a if you want
Speaker 1:It's an personal agent, super intelligence we're like Manus is great. Yes. And so Zuck has been great at buying a product that has a lot of potential Yeah. That has some, like, customer traction and like scaling up massively.
Speaker 2:Yeah. And even just for the most mundane Instagram usage where you could say, you know, oh, I wanna look across my audience and see who's the most engaged or understand what trends are happening in my in my vertical or, you know, like respond to every comment with a heart if it's positive. Like anything that you'd want as an agent to go around on these social platforms and do, let alone like go buy something for you. Having a team that works on agents makes a ton of sense. But it's, yeah, it's funny.
Speaker 2:It's just funny that they're rolling
Speaker 10:it out.
Speaker 1:Matthijs says, I think that's connected to WhatsApp de platforming other AI companies. Remember, ChatGPT had like a huge Yeah. In WhatsApp and they got and they got booted.
Speaker 2:That's crazy. Harry shares a little bit of lore about Peter Steinberger. Says he bootstrapped PSPDF kit over ten years ago. It's the gold standard PDF library used by Box, Apple, and even DocuSign. Wow.
Speaker 2:That's crazy. Insanely hard tech. If you know, you know. It's very hard to work on PDFs. I guess he's worth a couple 100 mil from that.
Speaker 2:Everyone's everyone's trying to guess the number, then nothing's been confirmed. If he goes to OpenAI, he might make more from OpenClaw, which is three
Speaker 1:Peter says he signed the contract today with software my company built years ago.
Speaker 7:I love
Speaker 1:Now it's Nutrien Docs.
Speaker 2:Best for anything PDF. It's like I'm PDF maxing. Let's take a look at this. Harnesses won't matter in less than three years, says Ahmad. Yes.
Speaker 2:There's money to make at the moment, but keep in mind that this is this is the play of two years ago, and you should be playing for what the models will be capable of in two years from today instead. Claude plays Pokemon kind of proves this. Opus four point five and four point six has the same insanely bad harness, no babysitting like Gemini and GPT. And 4.6 is like eleven ninety seven hours ahead of 4.5. So oh, it's how far they get
Speaker 1:into Yeah. See some people trying to back a bunch of, like, Open Claw startups. And given that just feels like a potential bloodbath.
Speaker 2:I I think Especially
Speaker 1:especially knowing that Yeah. OpenAI will be able to build I would assume build the best possible kind of wrapper around Totally. Yeah. Everything that OpenClaw has built so far?
Speaker 2:Again, would assume that the three major labs, DeepMind, Anthropic, and OpenAI, all have serious orchestrators very soon. And they will acquire talent and acquire products and build products and license stuff and figure out all sorts of integrations, do all the business things necessary to make it happen. But as I wrote in the year of orchestration or orchestrators, like, this is coming. People are managing multiple agents already and tools that make that easier, tools that make that more reliable and more efficient. Like, that's gonna be a big focus for this year and everyone's gonna be focused on.
Speaker 2:So the the idea of, like, oh, I should just, like, fork this open source project and, like, bring it to Like, that's gonna be rough when OpenAI has a thousand forward deployed engineers going into every enterprise that they already have contracts with.
Speaker 1:Yep.
Speaker 2:Tyler, what do think?
Speaker 1:Yeah. I was gonna say, like, I I think
Speaker 3:it's a similar thing to the hardware. So, like, Gemini is is developing the TPU, like, with the architecture of the model in mind, and they're developing the architecture with the with the hardware in mind. Right? So it's kind of like these things are, like, helping each other. You're gonna see the same thing in in the harness, right, where, like, the the harness is made with the model in mind, obviously, but then you're you're gonna start to see as these things, like as agents become more and more popular Mhmm.
Speaker 3:Like, OpenAI already has, like there's the normal, you GPT five one three and then there's five one three codecs. Right? Mhmm. So the models are, like, built with the with the harness in mind.
Speaker 2:Yeah.
Speaker 3:So I think if you're not the one building the model and you're just adding your own harness, right, the model's not gonna be, like, customized for your harness. Yeah. So if if if OpenAI and Anthropic are building their own harness, they're gonna do it with the model in mind. It's gonna be, like, much better than having some third party thing that you you build. Right?
Speaker 2:I would think so. Yeah. No. That's totally reasonable. Harness for forces,
Speaker 1:Bobby Cox. Yeah. It really is the
Speaker 2:Horses don't stop. Harnesses don't stop.
Speaker 1:Will Brown says, honestly crazy that Open Clause sold for 1,000,000,000. Like, he's really the first solo $5,000,000,000 founder. Time will tell if it's worth the 15,000,000,000 that OpenAI spent on the acquisition, but it's pretty wild that you can just vibe code an open source project and make 40,000,000,000 in a couple months now.
Speaker 2:It really, really nails it because everyone jumped immediately to a billion, immediately.
Speaker 1:Off of nothing.
Speaker 2:Off of nothing. Off of like one rumor for, a Thinking Machines person that went to Meta, we don't even know what the earn out schedule for that is and how much that happens. But it's, it's very, very funny. Who knows?
Speaker 1:We gotta give some credit to Simp four Satoshi. This up before. Simp has been working on truffles for a handful of years now. I've by I've been by his studio in Venice. It's very cool setup and team over there.
Speaker 1:But he posted a little bit about this. Yeah. Where is it?
Speaker 2:In tiny box, George Hott's project is also apparently gonna ship a more consumer product. Maybe I think they're around $10,000 right now. They're probably gonna bring that down to a few thousand dollars or maybe even few $100. You get a lot with the Mac mini, but we'll see where the prices land after the memory shortage takes hold and whatnot. But lots of people are doing this.
Speaker 2:Alex Cohen breaks it down for Gen z. If you're wondering what happened today, Claude was mocking OpenAI for weeks. Then this gym cell dev ships Claude bot, which was the fastest growing open source thing ever. Absolute looks max for the whole ecosystem. Anthropic tries to derry goon him with legal.
Speaker 2:Dev renames to OpenClaw. OpenAI slides in like a void pulling Chad with acquisition interest. OpenClaw gets acquired by OpenAI. Now Anthropic is getting jester goon by the entire timeline, and OpenAI is gigamaxing off their fumble. Open Anthropic could have just let them cook, him cook.
Speaker 2:Instead, they went full moid and got outframed by the Jester Maxers at OpenAI. 8,000 likes. The the the Luxmax lingo is really it feels like, hilarious. I I do wonder the half life. I feel like it's
Speaker 1:I think it's over.
Speaker 2:It's gotta be
Speaker 1:I think
Speaker 2:it's gotta be towards the end of this boom, but the rise of of the, of the kick streamers is, certainly the story of the year. Certainly the story of the year. Dave Moran shared more context on, like, what the future of OpenClaw will look like. So Dave Moran, who you might know from From Offline Ventures. Slow.
Speaker 2:He's been on our show, Path. He is now on the board of OpenClaw. And he says he's been working on the OpenClaw foundation structure for weeks, a home for thinkers and hackers that choose and those who wanna own their data. He's honored to serve as a as the founding independent board member. This community built something extraordinary.
Speaker 2:Our job is to protect it, open source forever. Excited to share more soon. Raul says, let's go. There was there was some funny, there was some funny pushback about, someone was like, oh, it's so unfair that Peter's, like, reaping all this reward from from these work. Like, it's an open source project.
Speaker 2:There were lot of committers. And he shared the number of commits, and it's just like him and, like, 90% of the work. Then, like, a few of his buddies who are all in the chat in the reply be like, yeah. Like, we love this. This is great.
Speaker 1:We're And a number of them are going to OpenAI too. He's like the headline pick up. But And then a number of the other committers
Speaker 2:And then those AI models
Speaker 1:Yeah. And then and then the the other the other key contributors Yeah. Started committing after it was like fully Totally. Totally. Yeah.
Speaker 1:Hundreds of thousands of people And
Speaker 2:it was
Speaker 1:building on top of
Speaker 8:it.
Speaker 2:It was it was like pure I I don't know. There's no term don't know if there's a term for it but it was like it was like third party like angst or something. It was like people were feeling angst on behalf of people who felt no angst. Like the people on the team were all like, this is awesome. We're all on board.
Speaker 2:And then other people were like, they got screwed. And it's like, I don't know. Not quite.
Speaker 1:Intern is sharing what your twenty twenty seven team off-site will look like Mhmm. Taking the taking the Mac minis somewhere nice, taking them out. Yeah. We'll see.
Speaker 2:And here's the here's the post you were talking about from Ashen. I didn't believe it, but Mac Mini studios are actually sold out in most places. Walmart, Apple Store, Amazon, Best Buy, Micro Center. Apple has a month wait now too for most AI type beat models. 48 gigs plus of RAM.
Speaker 2:Funniest part is that there are still 24 gig Mac minis. What's up? 48
Speaker 1:They said it was possible. Oh, that they would saw it. Yeah. Like, couple of weeks ago.
Speaker 2:Yeah. I I went Ram covers the Apple Store, and they were they were fully in stock. But, you know, the timeline moved on, and people, people went more aggressively into the Mac mini. Let me tell you about Vanta. Automate compliance and security, Vanta is the leading AI trust management platform.
Speaker 1:It started today. We have some breaking news out of New York.
Speaker 2:Oh, yes. What happened?
Speaker 1:Josh Kushner has announced Thrive 10 exceeding 10,000,000,000 Thrive. 10 compromises 1,000,000,000 designated for early stage investments and 9,000,000,000 designated for growth stage investments. He said, we do not view this as a milestone, but as a commitment to the long work ahead. We view Thrive as a company, our products as partnership, the willingness to commit deeply to a small number of founders, and to stand with them through momentum and adversity. This is the discipline we bring to our work and the responsibility we accept when founders partner with Thrive.
Speaker 1:We do not hedge. Concentration demands loyalty to the founders and missions we back in this moment. Exposure alone is not a strategy. Judgment without commitment is not enough. Advantage will accrue to those who choose deliberately commit deeply and endure through difficult moments.
Speaker 1:Thrive was founded to be an enabling technology for the world we wanna see. We are deeply aware that we are not the main character. The founders that we are fortunate enough to partner with are the artists. Our role is to help create the conditions where great work can come to life. We take a long view grounded in the belief that category defining companies tend to create structural compounding advantages over long arcs.
Speaker 1:This fund reflects the continuity of our approach and the ways our work has deepened alongside the founders we support. We are grateful for the trust our limited partners place in us and for the opportunity to work alongside those who are building with purpose, integrity, and courage. Hit that gong. To see it.
Speaker 2:Josh has been
Speaker 1:$5.10
Speaker 2:10,000,000,000. I like that.
Speaker 1:Yeah. Having zero exposure or anything to TBPN, he's been nothing but kind and and helpful to us Yeah. It's true. On the journey. And it's yeah.
Speaker 1:Testament to the work of the whole Thrive team. And I will say, their merch is phenomenal. Really good. I was wearing the
Speaker 2:You were wearing the pajamas? The pajamas. No way.
Speaker 1:I was wearing the pajamas this weekend.
Speaker 2:Yeah. They got some good stuff. Creative stuff, like different different stuff, unexpected drops, which I love.
Speaker 1:Yeah. And we have to have to read this off
Speaker 2:Of course.
Speaker 1:It's just so good. Sayla says, Joshua Kushner strode billionairely across his room. His contrarian high concentration vibes engulfed Rick Rubin's Bohemian Monk retreat. Joshua's high conviction and mystery filled the room.
Speaker 2:I know what this is referring to.
Speaker 10:Is a reference
Speaker 1:to the philosophy. Profile.
Speaker 2:Which is Which really got a lot of people upset. A lot of people are not they're like, this this doesn't count as as writing.
Speaker 1:How? It was it it transported me to to Malibu.
Speaker 2:It was fantastic.
Speaker 1:I thought it was Let
Speaker 2:me tell you about Lambda. Lambda is the superintelligence cloud building AI supercomputers for training and inference that scale from one GPU to hundreds of thousands.
Speaker 1:Let's head over to Tyler Cowen.
Speaker 2:Tyler Cowen. He is giving us some more economic data on AI productivity. You see tech and AI everywhere, but the productivity statistics, that's what people say. He says, How many times have I heard versions of that claim? Eric picks up the telephone in the Financial Times.
Speaker 2:He says, While initial reports suggested a year of steady labor expansion in The United States, the new figures reveal that total payroll growth was revised downward by approximately 400,000 jobs. Crucially, this downward revision occurred while real GDP remained robust, including a 3.7% growth rate in the fourth quarter. This decoupling, maintaining high output with significantly lower labor input, is a hallmark of productivity growth. My own updated analysis suggests a U. S.
Speaker 2:Productivity increase of roughly 2.7% for 2025. That is a near doubling from the sluggish 1.4% annual average that characterized the past decade. It's fine to suggest this suggest caution in interpreting such statistics, but they hardly push the other way, says Tyler. And it's yeah. It's just a very fascinating that we're potentially the end of stagnation in seeing seeing productivity growth.
Speaker 1:Relevant to this conversation, you were looking at employment data out of
Speaker 2:The Philippines. In India. I I've been very cautious about the AI will take all the jobs narrative. When will that happen? Is it happening yet?
Speaker 2:Is there a Jevan's paradox to the type of work that we're doing? How much software do we want? You know, we have the ability to write way more lines of code. How many more lines of code do we actually want? It feels like there's a lot of opportunity.
Speaker 2:It feels like the labor market is weak, but it hasn't collapsed. A lot of people still have jobs. It's there's a lot to unpack. And so I was I was interested to know, are we seeing a massive spike in unemployment in The Philippines or in India, where a lot of white collar labor is outsourced, whether it's, answering the phones or doing business process outsourcing? A lot of companies have back offices in I was talking to somebody who works in architecture, and they said that a lot of the architectural drawings that that happen happen overseas.
Speaker 2:The same thing happens in the big three management consulting firms. You want a lot of management consultants will sort of sketch out a slide, and then they will send it over to a team offshore that actually turns that into the final PowerPoint product. And you can see how if you have a sketch and you just need to turn it into a real chart, that's a textbook use case of artificial intelligence, whether you just style transfer it with something like NanoBanana or you go and do a deep research report and then then basically code the actual chart. And all the models are very, very capable of generating charts based on data. That's actually how I generated the chart of The Philippines' unemployment rate.
Speaker 2:And and I saw from both The Philippines and and India, there was not a major spike in unemployment. Maybe it's coming. You know, we've we've heard from the ground that job market's not good, and and and maybe maybe the jobs are getting worse. But there's at least there's not high unemployment yet both in The United States and and abroad. So it's something to keep a keep an eye on.
Speaker 2:But I don't know. I've just been, like, looking for more solid data points around labor displacement because it's such a huge narrative. I don't know. We'll see. Let me tell you about Railway.
Speaker 2:Oops. There we go. 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.
Speaker 1:What did Claude do? What did Claude do? Pentagon has said that Anthropic will pay a price. Of course, this was There was reporting last week that Claude was leveraged in some way during the Maduro planning the planning of the Maduro Sure. Raid.
Speaker 1:I was imagining in my head Dario as Walter White, you know, in the SUV just being like No. Watching watching the logs and seeing Pete Hegseth running a deep research report on Maduro.
Speaker 2:Who is
Speaker 1:Nicholas Maduro? He's just like, no.
Speaker 2:No. I'm not doing it.
Speaker 1:Yeah. Very very unclear how how it was used. But a lot of pushback. You know, Palmer Palmer was pushing back pretty hard. Let's see if I can pull up what he actually said so I don't botch it.
Speaker 2:The, the Wall Street Journal headline is Pentagon used Anthropics Claude in Maduro Venezuela raid use of the model through a contract with Palantir highlights growing role of AI in the Pentagon. Now, I remember seeing a clip from Shamsankar at Palantir talking about how, every query that the government runs has actually run through three or four different LLMs and then synthesize. They sort of put their own model router on top of the other models because if you're doing
Speaker 1:Fed rapper.
Speaker 2:I guess it's basically a wrapper. Because you sort of want every possible, you know, piece of information. All the LLMs have different parts of the Internet, different training corpuses, different opinions, different all sorts of different things. So you put all those together. The mission to capture Maduro and his wife included bombing several sites in Caracas last month.
Speaker 2:Anthropics usage guidelines prohibit Claude from being used to facilitate violence, develop weapons, or conduct surveillance. We cannot comment on whether Claude or any other AI model was used for any specific operation classified or otherwise said an Anthropic spokesman. Any use of Claude, whether in the private sector or across government, is required to comply with our usage policies, which govern how Claude can be deployed. We work closely with our partners to ensure compliance. The deployment of Claude occurred through Anthropic's partnership with data company Palantir Technologies, whose tools are commonly used by the defense department and federal law enforcement.
Speaker 2:Following the raid, an employee at Anthropic asked a counterpart at Palantir how Claude was used in the operation according to people familiar with the matter. An Anthropic spokesman said it it hasn't discussed the use of Claude for specific operations with any industry partners, including Palantir. Outside of routine discussions on trick on strictly technical matters, Anthropic is committed to using frontier AI to support in support of US national security. Okay. So we'll see we'll see where this goes.
Speaker 2:Anthropic's concerns of how about how CLOG can be used by the Pentagon have pushed administration officials to consider canceling the contract worth up to $200,000,000 which is a drop in the bucket at $14,000,000,000 ARR, but still probably has larger implications for, you know, their relationship with the the government broadly.
Speaker 1:Yeah. Was someone who was saying, I don't know who needs to hear this, but punishing private companies because their CEOs don't share your politics is really bad capitalism. Palmer said, this is not a reasonable characterization of what is happening. It isn't a matter of punishing companies for not sharing political views. It is a rational response to a vendor trying to control the government via terms of service and the products they power.
Speaker 1:Mhmm.
Speaker 2:I hope you realize oh, yeah. People are going on okay. Wait. So Disclosed TV, shared it as well. Pentagon used.
Speaker 2:And what is this? Someone launched a Federal Reserve simulator? Is there anything more on
Speaker 1:the No. We can we can move on. This is more important. Somebody important. Bill Meade Gaming just released the Federal Reserve simulator in Steam.
Speaker 1:If you like flight simulators, you're Yeah. Probably gonna love this.
Speaker 2:Productivity is gonna go to zero.
Speaker 1:It's turn based
Speaker 2:People aren't gonna be going to work. They're gonna be taking days off to play this.
Speaker 1:A turn based economic simulation game where the player assumes the role as head of the United States Federal Reserve.
Speaker 2:This is awesome.
Speaker 1:Tyler, fire it up.
Speaker 3:This I would actually play this.
Speaker 1:Yeah. Fire it up. Fire it up. Download it. I want I want your I want your review.
Speaker 2:I like Garrett Garrett Jones here. He's like, promising. And he's a professor of economics at Jordan Mason.
Speaker 1:He's like, actually serious. I feel like That's amazing. I feel like this would be an amazing game Okay. To play if
Speaker 3:you were reading on Steam Yeah. Say, I learned more about monetary policy in fifteen minutes on this sim than I did in five years of university.
Speaker 2:That's actually
Speaker 3:Please do investment banking simulator next.
Speaker 2:Yeah. I I was thinking about the the
Speaker 1:LBO simulator would go so hard.
Speaker 2:Let me tell you about Cisco first. Unlock infrastructure critical infrastructure for the AI era, unlock seamless real time experiences and new value at Cisco. So I was thinking about Scholto's Age of Empires real time strategy game based on the AI era. And I was wondering if it's easier to ship basically a skin or a mod for Age of Empires because the actual fundamental mechanics are pretty tight. And you actually don't want to mess with those because the game's so balanced and it works so well.
Speaker 2:What you really want is just instead of like instead of like archery units and horses, you want robots and Terminators and, you know, you want like a sci fi theme on top of it. And I feel like that would be something that an agent could work very well at. Just export the image and the description and the words of every single unit and item in the game, export all the textures, and then upload each texture to nano banana one by one and say, this is a tree. What does the cyberpunk tree look like? What does the diamond age tree look like?
Speaker 2:What does the, you know, the the 2026, you know, tree or or building look like? And then it just iterates through all of those to create, effectively a mod a or a skin for the game. But if you do wanna change the actual underlying structure, you gotta go deeper. But that's that's a lot of tokens. So we'll see.
Speaker 2:We'll we'll see where it goes.
Speaker 1:We gotta keep pressing him on his game.
Speaker 2:We got he's gotta ship it.
Speaker 1:You gotta ship. It was it was beat the vibe coding allegations. Right? The never ask somebody what never ask a Claude Code Maxey what they've what they've shipped.
Speaker 2:Claude Code. Beat them.
Speaker 1:He's gotta ship.
Speaker 2:I wanna show you this Instagram video because it had me dying laughing. And so if we can play this. We're gonna get demonetized, but we'll talk over it. So he vibe coded a calculator. Can we zoom in?
Speaker 2:I don't know. He vibe coded a calculator, and you and you type in your numbers. You type in 5Times9, and then it says unlock results. $299 one time payment. You pay, and then it gives you payment successful.
Speaker 2:The answer is 45. This is the future of vibe coding. I loved it. Anyway.
Speaker 1:I wonder I wonder did he actually ship the product because this this got millions of views and
Speaker 2:You think someone would just dug.
Speaker 1:I wanna know if the
Speaker 2:payment rails work. Let me see. Quickly, let me tell you about fin dot a I. The number one AI agent for customer service. If you want AI to handle your customer support, go to fin.ai.
Speaker 1:SAG AFTRA
Speaker 2:What happened?
Speaker 1:Put out a statement Yeah. On C Dance two point o. And
Speaker 2:It's not a comment. It's a statement. The
Speaker 1:Chinese yeah. No. The Chinese are have been quivering in fear ever since. Oh no. SAG came after them.
Speaker 2:What did SAG
Speaker 1:stands with the studios in condemning the blatant infringement enabled by ByteDance's new AI video model, Sea Dance two point o. The infringement includes the unauthorized use of our members voice and likenesses. This is unacceptable and undercuts the ability of human talent to earn a livelihood. It is kind of interesting that just in this statement they're admitting to saying like, it's so good. You're you're gonna make it impossible for our members to earn a living.
Speaker 1:Which doesn't actually
Speaker 2:It says undercuts. Undercuts. Doesn't say eliminates. Says undercuts.
Speaker 1:CDance two point o disregards law, ethics, industry standards, and basic principles of consent. Hit that Responsible. Responsible
Speaker 2:AI development demands responsibility that is nonexistent here. Completely correct. Some of the C Dance videos are insanely infringing. It's just like, wow, it's Larry David. And it looks exactly like Larry David.
Speaker 2:Did we license this? Let's figure it out. Beginning of the end says says Growing Daniel. Yeah. We have the I have the Larry David video, but I don't think we wanna play it.
Speaker 2:It's very it's very uncouth. Yeah. We won't
Speaker 1:skip that one. Disney Disney also as expected, sent a cease and desist letter to ByteDance over Sea Dance two point o. I wonder It's crazy. I wonder how ByteDance will actually react to this pushback. They expected it.
Speaker 1:Yeah. They know that they're not abiding by a number of different US laws. Whether or not they care is another thing.
Speaker 2:Yeah. I wonder how like, what what will the will the equilibrium be here? Like, if they don't allow usage in America, but everyone goes and gets VPNs. Is Cdance two point o open source? Because if it's if you can just run it, like, it's, like, so hard to play whack a mole and actually and actually get the and actually get this taken down in any meaningful way.
Speaker 2:Like, the cat's pretty much out of the bag if this is something you can just download.
Speaker 1:I don't think it's open source.
Speaker 2:Okay. So it's running on
Speaker 1:But but again, in some ways, a lot of this stuff will need to be solved by Meta and YouTube. Yeah. Yeah. So if somebody makes a video Yeah. With a famous actor
Speaker 2:Yeah.
Speaker 1:Yeah. And they're like just monetizing that Yeah. I would assume that YouTube should be in the fullness of time forced to demonetize that content or just give the revenue back to Yeah. The actual IP holders.
Speaker 2:Yeah. You'd think you'd think that you'd be
Speaker 1:able to And then meta meta, the other thing is meta like, if you if you make an an AI version of Andrew Huberman Yeah. And you get in a fresh ad account, you can probably start spending money before the Huberman Lab team finds out what you're doing.
Speaker 2:I would disagree. I think Rob's on top of it. I think he's goaded. So but anyone else. Any other team would be cocked.
Speaker 1:I don't know. I mean, he might respond faster than than than the others, but this has certainly happened.
Speaker 2:He is he is superhuman.
Speaker 1:And this has been this kind of thing has been happening to Joe Rogan for Yeah. Years this point, which is like very poor
Speaker 2:Yeah.
Speaker 1:Deep fakes. Yeah. But
Speaker 2:Yeah. I watched a video on on Corridor Crew about how to identify like the latest the latest AI slop, and it was very interesting all the different techniques that are used. Now, there's some really obvious ones where it's just it's just, you know, clearly AI video from end to end. And so if you look in the background, like the wood grain on the wooden poles or the walls changes from shot to shot, and that's like a tell that it's not consistent. But there were some where there was an AI influencer that was taking real photos and then just adding this AI influencer into the photo.
Speaker 2:So it'd be like Joe Rogan with Tony Hinchcliffe replaced Tony Hinchcliffe with this AI influencer girl. And then you look in the background and you're like, there's no hallucinations. Like, everything looks perfect. Because it is. It's just the base it's just the base image and then you're just adding this one character.
Speaker 2:There were a bunch of interesting things. There was also a video that everyone was calling AI that was just a dog painting. And it just turns out the dog can paint, which is awesome. But it was a little bit of a magic trick because the dog couldn't actually paint a picture, but it could sort of pick up the paintbrush and draw strokes. But the dog was next to the dog's owner and the
Speaker 1:dog's You're gonna say owner that's not art.
Speaker 2:It is absolutely art. But the dog's owner was actually a great artist and would switch paintings with the dog. So the dog would make one like big messy brush. They would switch paintings, and then she would turn that messy brush into a tree. And
Speaker 1:So they do that time lapse?
Speaker 2:Yeah. Well, yeah, there were just some cuts. And so they would switch, then whatever the dog did would sort of serve as the interpretation and the case for the artist to take it to the finish line. And so you wind up with these two beautiful paintings that the dog and the artist sort of collabed on, which is kind of cool.
Speaker 1:Yeah. Gavin Purcell says, If bite dance doesn't restrict or nerf a C Dance, this is going to escalate to a political conversation. Unlike the Soar two launch, because OpenAI restricted likeness ahead of time, C Dance shows just how clearly every major movie star is generatable by AI. So this is interesting. If you're already an A list massive superstar, I think you see some stuff like this.
Speaker 1:And you're actually like, great. I'm going be able to shoot a movie in a week from LA. I'm not going to have to travel to these insane, exotic locations Yeah. And spend a week in the desert filming all these clips. So if you're like a a Timothy Chalamet, this is maybe like, yes, you're worried for the overall industry, but at the same time you're thinking, Okay, my name and likeness is now infinitely scalable.
Speaker 1:I can still restrict the supply to some degree. I'm not gonna tell any movie studio, Hey, you can make a movie with me, whatever. You're still gonna restrict it and have pricing power. But if you're a the question becomes new talent that's emerging, trying to build their brand. At what point do studios say, we're just going to make a character we're going to make a new actor out of thin air, place him across different movies, build him up over time.
Speaker 1:You could imagine I don't think a company like CAA would do this, because all their talent would be like, what are you doing? Like, you're taking our job. But I could imagine a group trying to make like a little Mikayla style actor that you build up over time.
Speaker 2:Yep.
Speaker 1:One thing that we'll find out is how much does the actual actor's real life matter in the context of their career. Yeah. Like, if Timothee Chalamet is dating Kylie Jenner, does that like increase his appeal 100%. On the big screen? Yeah.
Speaker 1:And I would say, yes. Yeah. Probably. Right? There's so much fixation on the lives of all this talent.
Speaker 2:You could sort of fake a decent amount of that. You could fake paparazzi photos. You could fake, you know, vacation photos. You could create a whole world around a fake person potentially. But if people find out, will that break the illusion?
Speaker 2:Will they be not to it?
Speaker 1:But it's not real drama. People the drama. They like following stars.
Speaker 2:I'm still I'm still just pretty optimistic about like AI is a tool in Hollywood. Did you see that fully fully AI generated movie about the woman who goes in the cyber truck that went viral this weekend.
Speaker 1:Wasn't it, like, only three minutes?
Speaker 2:I think yeah. Exactly. It was only three minutes. But, everybody was consistent from one shot to another, which is impressive. And somebody said, like, not enough people are talking about why this how much this sucks.
Speaker 2:And Ben Stiller chimed in and was like, because it's bad. People don't talk about things that are bad. And it was it was sort of interesting. I I think the there's still a lot of interesting like, I was thinking about, like, imagine if Kevin Feige is that how you say his name? He's the creator of the Avengers.
Speaker 1:Don't ask me.
Speaker 2:Don't ask you. Anyway, I don't know. Christopher Nolan or James Cameron. If James Cameron got up and was like, I'm introducing Avatar. It's a great movie.
Speaker 2:And, yes, we it's a we use CGI. It's like, no. The CGI is, like, just a tool that he uses. It's like, you don't say, like, yeah. We're doing Avengers, and guess what?
Speaker 2:We use green screen, and that's a selling point. It's like, it'll always be a tool. And so I would I would I would assume that there will be amazing directors and creators in Hollywood that use AI as a tool in certain areas.
Speaker 1:Yeah.
Speaker 2:But they won't they like, you'll know it's arrived when they're not making a big deal out of it. Like, it should just stand on its own. Right now, things go viral because you say, this is a 100% AI generated, you're like, okay. I wanna know. Like, how good is this AI stuff?
Speaker 2:But no one's just like, here's my green screen test. And then they're like, okay. Awesome. Like, we know green screen works. We know it's it's a thing.
Speaker 2:It happens.
Speaker 1:Yeah. When I when I see the Sea Dance content, I think, okay, if movie budgets stay the same Mhmm. I think we can potentially get a lot more great movies. Yeah. And that's specifically because how much of these budgets goes to, let's say, somebody's making like a movie like 300 Mhmm.
Speaker 1:And we need to get, you know, a thousand people out in a field. Oh, 300 people. But,
Speaker 2:yeah. Who's counting?
Speaker 1:Who's counting? We need to get a lot of people out in the field Yeah. And spend days, weeks, you know, recreating all these different scenes Yeah. And now that budget can go towards
Speaker 2:Yeah. The famous Henry Like multiple movies. Superman. They they they finished shooting Superman. He moved on to, I think, a man from UNCLE.
Speaker 2:He grew a mustache, and they were like, we gotta shoot another Superman scene. And he's like, contractually, I cannot shave my mustache. And they were like, fine. We'll do it in post. And they have him come on, and they CGI'd a, like, a a shaved lip on the top of his mustache.
Speaker 2:Right. And it looked really bad, and it was like So people
Speaker 1:called it out?
Speaker 2:I actually think a lot of people saw the movie, and they were like, yeah. It's fine. It's pretty quick. But the VFX artists were like, this is bad. But with AI, obviously, that's much, much more doable these days.
Speaker 2:So, anyway, Console. Console builds AI agents that automate 70 of IT, HR, finance support, giving employees instant resolution to access requests, ask, and password resets. Andrew Curran gave us a shout out. Very nice of Andrew Curran. He said, one of the reasons Cdance two has impressed everyone is that it does the same thing that Sora did, make very detailed video gens from very simple prompts.
Speaker 2:There's probably some prompt hydration going on. There's reasoning in the LLM that then prompts the model. So you type in one sentence, it hydrates that into a lot to work with for the model. In fact, most of the CDAN's clips that went viral were made from one or two sentence props. We never did find out exactly what's going on in under the hood with Sora.
Speaker 2:TBPN asked about it when Sam was on, and I think he I think he means Bill Peebles from the Sora team. And he says, thank you, guys. So thank you for shouting us out there. But what they chose but they chose not to answer this specifically, so they dodged our question. No.
Speaker 2:We asked the hard question. Give us the IP, and they said no. This is the funny thing about the the hard questions in tech interviews. You're like, okay. So tell me how many parameters in the model.
Speaker 2:And they're like, that's a great question. We we're we're really investing in advancing the frontier. You're like, I I saw what you did there, but it's understandable. With two, we don't have a paper yet, but there is, one out for CDance one, and it says that they do use an LLM to convert the user prompt into a much more informationally dense and structured style of the prompt that the video model was trained on. They use a quen to do this.
Speaker 2:This is what most of us guess was going on with Sora, a version of GPT-five, maybe fit for this, was rewriting our prompts and adding details. Vanilla five. X would already be great at this out of the box, so it doesn't even need to be fine tuned really. If this is how Sora really works, then everything does make more sense. And there's a whole bunch more context from Andrew Kern's post that you can go check out.
Speaker 2:So Bojan Tungus is saying, I can't wait to use C Dance to fix the last season of Game of Thrones. Go do it. Go do it. I think that the last season of Game of Thrones was not I mean, it was I I thought it was good, but also I think that everyone's saying, oh, I wish it would end this way. I don't know.
Speaker 2:I I think if you did that, you would actually be like, it's harder to land this plane than you think. There are
Speaker 1:A lot interesting when people are are watching a series in real time. Yes. And then in advance of the final episode, let's say there's a week Yes. They're like, okay. I'm just gonna make the version that I want.
Speaker 1:Yeah. And I'll put it out.
Speaker 2:No. People on Reddit had written, like, full endings of Game of Thrones. And some of them were really convincing. Some of them I was looking forward to, and it went a different direction. But, you know, it is what it is.
Speaker 2:Let's pull up the linear lineup so we can tell you about the guests that are coming on the show today because we have one in the restroom waiting room already. I'll let you read this while I tell you that Linear is the system for modern software development. 70% of enterprise workspaces on Linear are using agents.
Speaker 1:Have John Karamika, New York Times music critic and buyer of fake TBPN merch coming on the show. We have Spencer Skates from Amplitude. We have Hasib from Dragonfly. We have Celine from Loyal. Anchor Brain Trust.
Speaker 1:Brain Trust. And we're closing out with Reed from Knight. So fantastic lineup here. And without further ado
Speaker 2:We have John.
Speaker 1:We should bring in
Speaker 2:From the restream waiting room. Let's bring in the Man, give yourself. How you doing?
Speaker 4:I'm so sorry to not wear the merch
Speaker 2:today. You're book really
Speaker 1:bad. Bookmogging. You're book I think
Speaker 2:Book maxing.
Speaker 1:Jenny Jenny
Speaker 4:Book max every day.
Speaker 2:Shelf mogging. Clarify how to say your last name.
Speaker 4:It's Karamonica. I appreciate, Jordy. That was that was noble. Karamonica. You must not have a lot of Italians in your life.
Speaker 1:Harmonic. Now I get it. Harmonic.
Speaker 2:Good nominative determinism. Very yes.
Speaker 4:Harmonic. Were you in my kindergarten class? You got a lot of that.
Speaker 1:Okay. We will No. I mispronounced your name. I'm gonna find the people that bullied you in kindergarten and I'm gonna go bully them to make They
Speaker 8:all lost.
Speaker 1:They all lost. All lost. Total victory.
Speaker 2:Yeah. You have real TBPN merch now.
Speaker 1:Do they?
Speaker 2:Yeah. No. They're stuck buying the fake stuff.
Speaker 1:Yeah. The cigarette
Speaker 2:Exactly. Anyway, we gotta talk about the hottest song on the Internet. We gotta talk about my granny got hit with a bazooka. What are
Speaker 4:your thoughts? Yeah. You know, if we were taping like an hour later
Speaker 1:Yeah.
Speaker 4:My song of the week video is going up this afternoon. It happens to be about Bazooka. No way. What a special and strange song. You guys are into it?
Speaker 4:You guys like it?
Speaker 2:I like it. Yeah. I like it a lot. I I like that it's so quickly been adapted into all the it it has the meme you know, when a meme goes viral and then you get it in an image format, it turns into a cartoon, there's the video overlays. Like, I saw someone singing it.
Speaker 2:They they they did sort of a like an acapella rendition with nine recordings of themselves. Seen people play it on on orchestral renditions and rearranging it, guitar, and I love that. And you get that with some songs. You go and you find a song and you go on YouTube and you say, like, heavy metal version, and there's someone who's just jamming, playing, like, the rap song of the day or acoustic version. I've always found that fun.
Speaker 2:So, generally, I'm a fan.
Speaker 1:But what do you think?
Speaker 4:Yeah. So my thing with this song, it's it's a perfect blank slate. Right? Because nobody knows the artist. It truly did come out of nowhere.
Speaker 4:I mean, this happened I this is a rare thing. Like, I went on vacation over the holidays. It literally happened while I was away. I came back. I had no idea.
Speaker 4:All of a sudden, the Internet is is completely cluttered with it within Yeah. The space of a week. Miami XO, who's the artist, doesn't really have much of a foot, like Okay. Not much of a footprint leading into this.
Speaker 2:Yeah.
Speaker 4:So unlike a lot of meme records that are from kind of well known artists where the meme ability is somehow predicated upon a preexisting understanding of the musician Yeah. This is pure it's pure joke. You know what I mean? Like, you can just
Speaker 2:access it at that level. I I don't know if this is a good good, example to draw on, but I'm thinking of, like, Lil Nas X Old Town Road where Sure. He had been immersed in the Nicki Minaj fan club, understood how the Internet worked, and and was already sort of sampling from Nine Inch Nails. And so Yep. There was an there was an established sort of repertoire.
Speaker 2:It just felt like he was ready for prime time in a way that Miami XL might not be, but.
Speaker 4:Yeah. I think that's totally fair. I mean, here's someone, I mean, hasn't even really done did his first interview from what I can tell maybe two days ago to kind of a random YouTuber. Like, doesn't seem to be ready to rise to the moment. And one thing that I find so strange is when a record gets memed this intensely, this quickly Mhmm.
Speaker 4:I know major labels are obviously knocking on the door, but things tend to happen a little bit quicker. Mhmm. You sort of you get a press release that they've maybe signed a distribution deal. Like, things move. But there's something that's I almost feel like a little hands off about what's happening now.
Speaker 4:Like, people are just like, let this cook. Like, let me get the Indian classical version. Like, let me get the SpongeBob version. Yeah. Like, let's just see what the sort of logical end
Speaker 2:point
Speaker 4:of this is gonna be. Yeah. Are you guys up on the the dancing video like, the dancing bones o seven dance videos?
Speaker 2:No. No. Tell us.
Speaker 4:Like a middle aged gentleman, navy veteran, kinda dancing in his living room I have Chick fil A in a car dealership. Yep. Really made his own kind of side cottage industry dancing to Bazooka. Mean, he's probably done about 20 or 25 videos Okay. Just to this one song creating a bit of an unholy alliance.
Speaker 2:Oh, interesting.
Speaker 1:I know.
Speaker 2:He's he's a key collaborator.
Speaker 1:What is He really is. What's the playbook? Yeah. What what's the what's the pitch that record labels are giving to Miami XO to turn you to capitalize on this this algorithmic moment and turn him into a star?
Speaker 4:So the cynic the cynical playbook, I assume, is what you're asking rather than the real playbook. Yeah. So the cynical playbook is we're gonna give you a short term distribution deal. Maybe we're also gonna give you a publishing contract in which we extract maximum value from your writing on this song and the next
Speaker 1:What what's the difference between those two in a music context?
Speaker 4:So publishing deal is gonna be on the songwriting, the lyrics, the metal the melody, whereas a distribution deal is for the finished product of the song itself.
Speaker 1:So there's But the song already exists.
Speaker 4:The song already exists, but a lot of times what they're doing is they're retrofitting contracts on top of things that already happened.
Speaker 2:Like,
Speaker 4:he's someone who has a SoundCloud page, but you and I could have a SoundCloud page. That doesn't mean that we're registered with ASCAP or BMI. It doesn't mean that we have a lawyer who's negotiating splits on any deals that we might have done with collaborators. He's just a guy with 40 songs on a SoundCloud page. So if I'm a publisher, I'm looking at those and saying, do I monetize those on a writing perspective?
Speaker 4:And if I'm a label, I'm saying, how do I put gasoline on this thing that already has fire? Probably what's happening is one of the major labels is gonna scoop them up, get a remix going with two or three of your favorite SoundCloud graduate rappers and see if they can turn it into a radio hit. Oh. There's a the
Speaker 1:challenge is that, you know, sometimes you have one of these songs, it's like catchy and Yeah. And funny and it and it and it naturally can play on the radio. But if you actually just start playing this on the radio, you can imagine I mean, I I I remember getting into rap music in maybe high school, middle school, whatever, and playing songs in the car with my parents. And then you really hear the lyrics for the first time, and you can imagine the moments with this song. And they're like, did I just did I did I hear that correctly?
Speaker 1:Yeah. So it's hard to imagine this as a like, it it feels like a it's an audio version of a meme. It's not Here's
Speaker 4:here's my here's my counterpoint. Mhmm. Grandma got run over by a reindeer.
Speaker 2:What's that?
Speaker 4:You know that song? Yeah.
Speaker 8:Yeah. Yeah.
Speaker 1:That's a classic.
Speaker 2:That's a classic? That's a classic.
Speaker 4:So if that's a classic, why can't this be
Speaker 2:a choice? Okay. Okay.
Speaker 1:Yeah. That's a great that's a great one
Speaker 4:of the great Christmas songs of all time.
Speaker 1:R m m x o Christmas edition of Granny Got Hit With is
Speaker 2:a great name. I like it.
Speaker 4:It is a great name. He's not from Miami, apparently. Apparently, he's from South Carolina. Okay. Which only visits.
Speaker 4:Yeah. We're all on the Internet.
Speaker 2:There, was a big Shaq who came out with that song, man's not hot. Do you remember that whole
Speaker 4:Oh, yeah. Yeah. Of course.
Speaker 2:So Yeah. Yeah. I I believe that started with a a joke version of fire in the booth, a segment on BBC Radio one maybe. And, normally, rappers show up to boo lesson. Yeah.
Speaker 2:Yeah. But, normally, rappers show up, and they deliver freestyles that are somewhat prepped and, like, iconic. The Migos have a great one. But then, Big Shaq shows up and gives this, like, completely jokey, but he's in on the joke, but no one really knows. It goes massively viral, and then he sort of commercializes from there.
Speaker 2:My question is, like, like, with Lil Nas X, there was clearly a contract that they needed to clean up with Nine Inch Nails to properly sample that. And then there's the remix. Like, is that a big part of the pitch? Like, we're gonna sort of protect you from what's coming if you're an agent and you're going to one of these breakout stars?
Speaker 4:Yeah. I mean, I think viral stars are really vulnerable. Right? Because they're often operating outside of any formal arrangements with any institutions. Yeah.
Speaker 4:So typically what happens in in a situation like this is the first person who comes in is is either a manager or a lawyer often. Yeah. Because sometimes you don't need both of them at this early stage. You simply need someone to represent your interests when you're walking into the room at Atlantic Records or Universal Records or with UMG Publishing, UMPG, or something along those lines. So that's probably what's happening right now.
Speaker 4:The truth is there are plenty of viral moments, quote unquote, that other people capitalize. Like, I think a lot about on fleek. There's, like, a young woman, a young black woman who invented or at least popularized the term in a in a viral video who then watched it get away from her. And it's in, you know, L'Oreal commercials and all this other stuff with none of the sort of benefits redounding back to her. And so a lot of times now what's happening, that was like six years ago before these processes were really formalized.
Speaker 4:People didn't know how to handle virality back then. But I think now people understand that virality is about the best marketing that's available and it can't be faked. Well, it can't be. But that's
Speaker 1:So so artists new artists has a viral moment. They start talking with all the record labels. How much difference is there between the different deals that they're being offered? In in our world, if you are if you create a viral product, your every VC will reach out to you. They're just kind of offering you different valuations, different kind of ownership levels that they're looking for and it just becomes
Speaker 2:20% in the board's
Speaker 1:And and and some element of some element of it is just like what price are you willing to pay? The others like who do I wanna partner with? I'm assuming it's something similar, but how much how much is there is there a record label that's gonna be like way more risk on? Like, hey, we don't we don't think this is just a one off moment. We Are they all telling them that you're you're a future superstar but then some of them are secretly saying like, yeah, we're just gonna max kind of extract what we can out of this.
Speaker 4:Yeah. I think I think there's there's two levels of answer to the question. Like, I don't I haven't spoken to Miami XO. I don't know if he wants a thirty year music career or if he sees music as, like, one part of a larger suite of, like, viral offerings. When you look at his TikTok and Instagram right now, the last two weeks of content is all him making jokes about his own virality.
Speaker 4:Maybe he's a maybe he's a viral comedian cosplaying as a musician.
Speaker 2:Sure. Sure. Sure.
Speaker 4:Dough to Oh,
Speaker 2:that's Yeah. Yeah. Yeah. Makes sense.
Speaker 4:So if I'm a label, I might say, do you want this to be your career?
Speaker 2:Yeah.
Speaker 4:If so, I'll invest x amount of dollars for x for y percent over twelve months.
Speaker 8:Mhmm.
Speaker 4:Or if if he says, you know what? This was kind of a lark. Like, let's just let's squeeze every little inch out of it. They may say, great. We're gonna give you a distribution deal for this song.
Speaker 4:Mhmm. We're gonna absolutely gasoline on it. We're gonna get a remix going. We're gonna put it in commercials. We're gonna do all this other stuff, and let's get you a quick half 1,000,000 or a million dollars Mhmm.
Speaker 4:And then do whatever you want with it. It really it really varies.
Speaker 1:Interesting. Is there some sort of iron law that says a song like this can only break through, like, once? It it seemingly like a silly song emerges, like, once a year. And you would think Oh, got you.
Speaker 4:Would think every day. No.
Speaker 1:I know. But I know. But we're talking about it. That means, like, this is not a music show.
Speaker 2:This did break through and it
Speaker 1:And and it's broken through and it feels like every I don't know. Is it twelve months? There's like some song. And I would think with Suno, a lot of people could be like, I'm gonna make a song like Bazooka.
Speaker 2:Yeah.
Speaker 1:Yeah. And they're just like taking a format for a song, which in this case, I don't know the exact genre, but it's like not it's not, you know, melodic kind of like
Speaker 4:It's like melodic underground rap.
Speaker 1:Yeah.
Speaker 4:You know, like
Speaker 1:You would think there would be this would like, when you get like a meme, like a more traditional meme, it just catalyzes a ton of different remixes on top of on top of that and kind of branches off of the format. But Mhmm. I haven't I I because of because of the way that the algorithms work and like syncing video or image content to the music, it just perpetuating like the same the same thing over and over.
Speaker 4:I mean, I think to your first question about how many of these do we get in a year, maybe we get four or five in a year that really, like, break escape velocity and get out to the wider public. And radio is is a funny thing. I mean, you were joking that, like, this would sound strange to hear on the radio. You know, five to ten years ago, you'd have a station like z one hundred in New York, which is, the big pop hit station that studiously, like, walled off TikTok is. They were like, we don't play those.
Speaker 4:Those aren't real songs. Yeah. You know, real songs are Lady Gaga songs. Like, real songs are Katy Perry songs or or Taylor songs. And then something happened.
Speaker 4:Maybe it was COVID. I don't exactly know what, but, like, 2021, 2022, you turn on Zoom 100 in the car, and it's literally just like listening to TikTok. Just the whole thing inverted. And, obviously, that's part because radio record labels are invested in both TikTok promotion, which is screwing with your algorithm and putting songs in front of
Speaker 2:you Yep.
Speaker 4:But it's also invested in radio promotion, which is putting things in a more mainstream level. But the chasm between those two universes
Speaker 2:Mhmm.
Speaker 4:Is so thin right now. I would not be surprised to hear Bazooka on, like, a mainstream rap station by mid March. I really wouldn't be surprised.
Speaker 2:Yeah. Yeah. Sounds right. I wanna
Speaker 1:What
Speaker 2:like, where this goes from a just, like, the cynical machine that takes place and, like, turns this into a repeatable formula. Is there Yeah. Do you think there'll be a new movement where a mainstream big artist hires a comedian to write some lyrics, and then they do specifically architect the virality where they have some UGC creator with a guitar, doing an acoustic version on day one, and they hire that guy to do the dance outside the car dealership. Yep. And so it's, like, much more orchestrated to like create that viral boom.
Speaker 4:What I would say is things like that are already happening.
Speaker 2:Oh, yeah.
Speaker 4:Like, I know people in Los Angeles. Mhmm. It may not be the literal, the exact literal thing you just said. Yeah. I But know people in Los Angeles who work in production and songwriting.
Speaker 4:A lot of songwriting rooms are three or four people. Oftentimes, you'll have one of those people who have fluency in viral content, or fluency in meme able internet content. And the the gap between, like, I'm a comedian, I'm a content creator, I'm a musician, we used to think of those as three different jobs. Yeah. They're not three different jobs anymore.
Speaker 4:Yeah. It's basically just one job, is getting attention. Yeah. That's the main job. So So I think what you'll see is actually there are a lot of people even who build themselves as songwriters, but who have been posting TikTok content for four, five, six years already and they're 20 years old.
Speaker 4:Are they a songwriter or are they a TikTok maker? You know, are they engineers of are they recipients of virality or are they engineers of virality? Yeah. I just don't think those lines are as meaningful as they used to be. But, yeah, things like what you're saying, they're definitely already happening.
Speaker 1:Mhmm. What are the what what are all the ways that you're tracking algorithms influencing the music business? Because like optimizing for that like ten to fifteen second repeatable thing that you can attach to a reel or a photo dump or things like that. I remember first processing artists gaming the streaming platforms by making every song much shorter. Right?
Speaker 1:Not like I'm not I don't I listen to music. I'm not like a a music head, but I distinctly remember being, wait, this guy just dropped you know, Future just dropped a mixtape. Why does it have, like, 30 songs Yep. That are all, like you know, minutes. So that that was, like, one of those moments that was, like, the platforms influencing the the the the music itself.
Speaker 1:But what are all the different things that you're tracking right now? It's good. Which make your blood boil the most?
Speaker 4:I gave up blood boiling
Speaker 1:a lot.
Speaker 4:I'm too old to have my blood boil. You're not allowed. At my age, you're not allowed for that. You're not allowed to have that. Okay.
Speaker 4:Let me take you back even further, first Let's of go back to actual Napster, like primetime Napster, when aspiring artists would tag their songs as Britney Spears songs or Eminem songs so that they would pop up in search algo, and you download it thinking you got some Eminem leak and it was by somebody else. Right? I've got untold on old hard drives, untold m p threes of who knows who After advertising themselves as, like, Metallica songs or So there's that. Your question about the future sort of, like, gaming the algorithm, that's functioning on two levels. One, you wanna provide as much raw content to any algorithm as you can.
Speaker 4:But two, when you think of how streaming platforms serve you music, the entire goal of a streaming platform is to make sure you don't press stop. It's to make sure you don't go away. And so not only did that affect the length of albums, because 30 songs is a longer play time than 10 songs, it also affected the structure of music. Think about Post Malone in the mid to late twenty tens. Right?
Speaker 4:What do you think when you think Post Malone? You think that's a little bit hip hop. It's a little bit r and b. It's a bit pop. Nowadays, it's a little bit country.
Speaker 4:But when you think of the kind of overall sonic framework of the song, it's real blurry. Right? It's smeary. He's singing in this very stretched way. The beats aren't like it's not like nineties rap beats where it's like on the it's not that.
Speaker 4:It's a lot blurrier. Streaming did that because streaming wanted to trick you into thinking that a song was never ending. And so you can press track one on a Post Malone album, and before you've even woken up, you're on track seven. Wow. The structure of the music it's
Speaker 1:so interesting because I remember, I don't know, being being young and like buying an album, and then like when you buy an album, it's such a different like for whatever, $10.12 bucks, 15, what whatever whatever however it's priced. Like, you're actually like list you're not just listening, you're like studying it. Mhmm. When I come away being like, do I really like this? And you wanna be taken on a journey and I would immediately clock, okay, I like these songs in this context, like these songs when I'm driving to school, this song in the gym, you know, you're you're kind of like mapping, I would map the album to my life and then at some point it was like, oh, you made you made 30 of the same song.
Speaker 1:Thank you. Thank you for that. And like sometimes it's it's kind of like a the cool vibe and it's fun to to listen to, but it's not like it's not like watching a movie that's taking you through all these different emotions.
Speaker 4:Mhmm. It it reminds me a little bit of jam bands in that way, which is like not a genre of music I care much about or or certainly not one I enjoy. But anytime I've been forced to go to like a concert of that style, I'm always kind of shocked that maybe it doesn't totally matter which point in the show you're dropped in or which point in the show you're pulled out. Like, it's kind of always happening. And, like, the dynamism is like, oh, in minute four, he did this lick, but also in minute forty seven, he did this other lick that kinda talks to that.
Speaker 4:Maybe it doesn't totally matter when you entered, and I think streaming really, especially for hip hop, really, really pushed things in that direction. And what you're seeing now, like, when I hear Bazooka, I'm hearing twenty sixteen SoundCloud records. Like, I'm I'm hearing Saababy records. Like, I'm I'm hearing things that post Young Thug that really, really made it seem like any kid with Fruity Loops software and, like, a tiny bit of a melodic sense could all of a sudden have a viral hit. It's really I mean, we are living in 2016, not just, you know, in Instagram hashtags and everything, but the fact that we've cycled back and the biggest record of 2026 so far is basically a 2016 SoundCloud hit is, I think, striking and also talks about how nostalgia is, like, extremely collapsed right now.
Speaker 4:Like, we're nostalgic for things that happened forty five minutes ago, you know?
Speaker 2:Yeah. The 2016 trend was huge on Instagram when 2026 happened. Yeah. It was like me in 2016, and I was like, that wasn't that long ago. Not long ago at all.
Speaker 2:But and and the photos, like, they look a little bit older, but, they were taken with iPhones. And so Right. They look like relatively recent. I'm like,
Speaker 4:oh, okay. It's also like younger. Well, one thing it also adds to that is, like, are we remembering a specific song, or are we remembering, like, a set of memories? Yeah. And and I think that's the fuzziness.
Speaker 4:Yeah. And, like, AI complicates that. Like, there's there's there are I'm beginning to think that original text, which is say Bazooka, is far less important than the memes, which are in turn far less important than how we talked about the memes. And I wonder if ten or twenty years from now, we're not really remembering Bazooka as a song Yeah. But we're remembering discourse far better.
Speaker 2:I mean, I I I I'm here talking about it for half an hour, and I don't think I've ever listened to more than thirty seconds of it. Like, I I could not tell you if it has a verse. Hey. I I know the chorus. It does.
Speaker 2:Okay.
Speaker 4:That's It
Speaker 2:does. I can confirm it has a verse. I will I will add it
Speaker 1:to that. I had that experience. I was in a I I did a I did a yoga class, and they were playing music.
Speaker 2:You're playing bazooka?
Speaker 1:And not not bazooka. The yoga class. Would that would go that would go. They were playing songs and I was like, oh, that's a that's a song. Because I I had heard them as Oh.
Speaker 1:Like background music to to so you know social media content I'd never heard it and I was like, oh, that that
Speaker 2:That's funny.
Speaker 1:That ten seconds. Yeah. I've heard that ten seconds. I've never heard the full thing. Yeah.
Speaker 1:What what's the are there any are you tracking any groups that are just fully in in the music industry broadly that are fully leaning into AI and saying like, we know a lot of people hate this and are scared of it, but we're gonna try to create like a super like a a faceless superstar here like a like a Daft Punk or or something like that? Any any any kind of because I I've seen the the people that will like go up the charts and saying, this is a fully AI AI. Artist. And it's hard to actually read too much into any one of these artists because it could very well just be a really talented musician who's like using the tools to the best of their ability and it's not just like one shotted AI music.
Speaker 2:Or or bots too. I mean, you're willing to do AI, you could also would be willing to bot.
Speaker 4:You can bot the success of it. Yeah. I mean, I think so so there towards the end of last year, there were maybe three or four, like, AI musicians that ended up on some chart. Look. There's a lot of charts.
Speaker 4:You could chart like, again, we could we could pick a chart and chart on it next week if we really tried hard. Let's
Speaker 2:chart, brother. Let's do it. Let's see what's happening. Do you
Speaker 4:wanna get involved? Alright. We'll we'll talk offline. We'll we'll we'll crack
Speaker 2:the code. I got the I got the refrain right here. You're watching TBPN. We'll do a remix. There we go.
Speaker 4:Stand So, on Solomon Ray, who's like a r and b artist, CNN a lot of them are R and B, gospel leaning R and B with a little bit of kind of like a MAGA adjacent country. These are the artists that have tended to been to break out into broader consciousness. A thing that I I noticed is a lot of these songs are
Speaker 8:what's
Speaker 4:the way to put it? They're sad. They're they're for depressed people. They're they're for people who are looking to get lost in a song, maybe without thinking too hard about who's the musician behind it or what's going on. They they feel like emotionally manipulative to me in a way.
Speaker 4:And I think those but I also think they're also calling cards. Right? Like, if you made Solomon Ray music and then you ended up on some billboard r and b chart, you can then go into a publishing meeting or go into a label meeting and say, look what I did with no resources. Mhmm. Imagine what I can do with that.
Speaker 4:So as far as, like, super groups and, like, big picture, like, I don't think people are thinking quite at that scale, but I think a lot of people are prompting AI to make music that will resonate for people who are in the music business specifically. Mean, we see this,
Speaker 2:yeah, we see this on x articles where people will use AI to generate something that's like, oh, that technology is so crazy. And I've seen it on Instagram Reels where you'll get sort of, like, a video that's very clearly, like, just glazing you and confirming all of your biases and stuff. I'm like, I I know why this is getting a lot of views because it's not acting as any sort of complex narrative or anything like that.
Speaker 4:No. And the other thing I mean, AI, I mean, I'm sure you guys see this a lot more in your side than I see it on my side, but there's a lot of, like, unseen process that AI help can help with. You have songwriters who are like, hey, I need a 20 part vocal harmony on the bridge. Mhmm. Can you just do 20 parts that kind of sound like they're in the same genre as the original audio?
Speaker 4:That comes together really quickly. Hey. I need a lyric to fill in, like, the fourth bar of the quatrain. Can you give me 10 ideas for that? I think you're seeing that in places already in studio sessions, but you haven't yet had the breakout of, like, it's Taylor Swift, but it's not Taylor Swift.
Speaker 4:Like, you haven't had that. I think we're still, like, a few years away on a major scale from that. But the small stuff is it's it's softening our resolve.
Speaker 1:Mhmm.
Speaker 4:I don't know. Do the Do care you if there's AI music? If you are listening to a Spotify playlist and track five is human, track six is AI, and track seven is human, are you stressing about that?
Speaker 1:Yeah. I mean, I showing points.
Speaker 2:I I like I like songs that other people know are songs. So even if you told me that Bazooka was AI generated, I'd be like, I'm still down because you have an experience about that, and we can talk about that. And if I'm humming it, you're like, oh, he's humming Bazooka. I don't want to be off in my own world listening to music that's just generated for me because no one else will get what I'm humming. And so Mhmm.
Speaker 2:As long as it's a Schelling point and everyone knows or everyone in my group knows about the song where I can share it and then they can find it and they can enjoy it, I'm cool. But I don't I don't want hyper personalized music necessarily. At least that's what I think.
Speaker 1:Yeah. Mean, I
Speaker 4:had Bazooka is a good hardcore band name. We should do that. Bazooka. Yeah. Bazooka.
Speaker 2:I I I have some lightning round questions
Speaker 1:that we can do. Yeah. I had the probably almost two years ago at this point, maybe a year and a half, but somebody made an AI Gunna album, posted it on YouTube. Mhmm. And you easily could have even that was, you know, I imagine all the models have made a ton of progress, but you could have slotted that into a gun.
Speaker 1:You could have, like, snuck one of those into a real Gunna album. Mhmm. And I would have been thinking, yeah, this this yeah. This is this is a vibe. The tracks.
Speaker 1:Yeah. But Yeah. One
Speaker 4:Sorry. Just the tech, it's like I'm not, like, a purist in any way. I think people use whatever technology they wanna make whatever they wanna use to make great music. But we become so desensitized in the sort of post t pain era to, like, hearing digitally processed vocals that, like, this is kind of what we were asking for the whole time, you know? Like and again, I'm not passing judgment on it.
Speaker 4:I just sort of think anyone who's complaining about it, but then goes and dances to, like, I'm in love with stripper at the club. And it's like, we're not that far away.
Speaker 1:Yeah. That's good. Everyone knows that just being in the streaming business, making all your money from streaming is rough. Think the Yeah. Is it it's like a billion streams on Spotify or Apple Music gets you, like, low single digit millions in revenue that you're then splitting up with tons of different people.
Speaker 1:So not not super significant. And so Yeah. The answer is do do constantly be touring, doing big tours. Are there artists that have insane streaming numbers that don't actually crush it when they go out touring? Like, is that That's
Speaker 4:that. So so that's interesting because I think you have streaming has created its own tier of superstars.
Speaker 2:If you
Speaker 4:think about NBA Youngboy, the most streamed artist on YouTube, maybe three of the last five years, two or three of the last five years. Yeah. Are you serious? Oh, NBA Youngboy. Look, NBA Youngboy is the most popular and meaningful rapper in America for the last five years.
Speaker 1:Had no idea. In my head, he's still, like, SoundCloud.
Speaker 2:No. Haven't you seen his earnings? He's outpacing the S and P 500.
Speaker 4:He had the number one no. No. He had the number one debut solo rapper tour by revenue, the tour that that just completed last year. I think he did 70,000,000 in ticket sales.
Speaker 2:Never broke again. He's never broke again. He called a shot.
Speaker 4:Never know.
Speaker 2:I will never be broke again. Put some of that in
Speaker 1:CDs. Yeah. The normative determinism.
Speaker 4:Someone who streaming created a marketplace
Speaker 7:Sure.
Speaker 4:And then went out into the world and received all the riches that came with it. But then you have other people who, you know, to your point earlier about Miami XO, is this guy a star or not? Like, who knows? Like, is he gonna be on one hit wonder bills ten years from now?
Speaker 8:Yeah.
Speaker 4:Maybe. But you have people, like, say even Playboi Carti, who, like, can tour well, but isn't really trying to be, like, a public facing
Speaker 2:Mhmm.
Speaker 4:Celebrity. It's like he's a little bit in the shadows. Everybody takes their streaming success differently. And but Youngboy is a is an example of someone who literally saw that and then went out and sold a million tickets off of that, you know, or something along those lines. I went to three dates on that tour.
Speaker 4:It was the most enlivening tour I've been to in years.
Speaker 1:What Did you feel like you needed to go to three dates to do your job properly? I mean, after the second, were you like was it just like, it's fun? I wanna go
Speaker 4:joy, man. I chased pleasure.
Speaker 1:I love it. I love it. The chat says he also has 13 kids. He may be broke again.
Speaker 2:This is wild. Thank you so much for coming on the show. This is always so much fun. I we got through exactly one question. I had 10, so we'll have to have you
Speaker 4:guys soon. Yeah. It's okay. We'll be back. Appreciate you.
Speaker 2:I can't wait.
Speaker 1:Great great to see you, John. We'll talk you soon. I'm here
Speaker 2:Yeah. We'll tell you about 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.
Speaker 2:And I'm also gonna tell you about Cognition. They're the makers of Devon, the AI software engineer. Crush your backlog with your personal AI engineering team. We had some breaking news.
Speaker 1:If you told me that
Speaker 2:Yes.
Speaker 1:NBA Youngboy Yes. Was the biggest artist on YouTube
Speaker 2:That took me by surprise as well.
Speaker 1:I would I would have said that's a that's a great bit.
Speaker 2:That's a great bit.
Speaker 1:I think
Speaker 2:he deserves it. I love NBA Young Youngboy. Fantastic artist. We have some breaking news. The Netherlands House Of Representatives has approved a 36% tax on unrealized capital gains, and Aaron Bali says, how do you short a country and got 27,000 likes.
Speaker 2:It's it's getting spicy over there in The Netherlands. But for
Speaker 1:ASML ASML employees are giga cooked.
Speaker 2:Oh, that's right. They're over there in the I don't I
Speaker 1:don't I still
Speaker 2:Oh, they're exempting startups. That's fun.
Speaker 1:But ASML is not a startup. I think I
Speaker 2:actually think of every business as either real estate or startup. You know, McDonald's, that's real estate play. You know, if we get if we get crazy with it, I imagine that there will be a lot of companies that are redefining their category as real estate if it's truly exempted here. It's full employment for tax lawyers over there. Get in that business because you're gonna be having a lot of clients.
Speaker 1:Yeah. The
Speaker 2:Our next guest is here.
Speaker 1:Our next guest is here.
Speaker 2:Let's bring in Spencer from Amplitude. Welcome to the show. He's in the restroom ready room now. He's in the TVPN UltraDell.
Speaker 1:What's going on? Hello.
Speaker 11:Hey, guys. Jordan, John. Great to see you guys.
Speaker 2:Great to
Speaker 1:see you.
Speaker 2:Thank you.
Speaker 11:So excited to finally make it to TBN and the big leagues, man.
Speaker 1:I'm so way overdue. Way overdue.
Speaker 2:You you you have a very unique, superlative. Right? Aren't you one of the first YC founders to ever take a company public? Like, in the first 10 at least, something like that?
Speaker 11:We were we were one of the earlier ones. In our batch in YC twenty twelve, it was us, Gusto, and PlanGrid, and those were kind of the big that was the the emergence of YC as SaaS, which is now dead. We We can talk about that.
Speaker 1:Okay. Okay. How how big was the class at that time? To think we made b
Speaker 11:to b hot. 60 companies. So very, very different from what it is today.
Speaker 2:Wow. Wow. That's really fast. Yeah. Yeah.
Speaker 2:We always we always recommend, taking companies public. If you're if you're building a business, just go head over to the New York Stock Exchange, take your company public. But how has it been for you? You know, there there's always like, oh, stay private forever. Do the SpaceX thing.
Speaker 2:Obviously, Elon's changing his tune on that. Give us a review. What's it like being in the public markets, and what what's your journey been like?
Speaker 11:This may sound very surprising
Speaker 1:Mhmm.
Speaker 11:But it's actually incredibly positive for a whole bunch of reasons. Cool. My opinion is once you get a company to about a 100,000,000 ARR or beyond, you have an obligation to the business, to the stockholders, to everyone that works with you to take it public. Mhmm. We did it for a number of reasons.
Speaker 11:I mean, one, there's liquidity aspect where now we can get talent and say, hey, this equity is worth something right this second Yeah. Not in some future scenario. Yeah. And that's huge because that allows us to attract a different level of executives, track different types of software engineers, like acquire companies. That's actually a really big deal.
Speaker 11:Mhmm. There's tons of companies up for sale these days and saying, hey. We're gonna give you real liquidity now Yeah. On the first day we do this transaction is a huge deal for them.
Speaker 3:That's nice.
Speaker 1:The other the other
Speaker 11:thing it does is it makes it clear that we are sticking around for the very long term. We're not continued dependent on the private markets
Speaker 2:Sure.
Speaker 11:For either liquidity for either liquidity or for, you know, future cash.
Speaker 2:Mhmm.
Speaker 11:We're profitable as a company. We're able to set that stake in the ground and talk about the next five, ten, twenty years. Oh, yeah. The profitability.
Speaker 2:There we go. Yeah. Amazing.
Speaker 11:No. So it it and and then it just it's the last thing I'd say is it sets a higher bar for execution.
Speaker 1:Yeah.
Speaker 11:Now, the downside is, you know, a liquid stock price massively distracting to the team because everyone's like, oh my god. You know, I'd make a point of not looking at it. Someone told me there's a SaaS or a SaaS apocalypse last week, and so I'm like, oh, I better say something on this. I know. But, you know, overall, it's actually a very positive thing.
Speaker 2:For since this is the first time in the show, take us back to YC Demo Day. Give us the elevator pitch. Like, what what were you describing then? And then, obviously, I wanna go forward to, like, what the company is like today.
Speaker 11:So we actually had a different company during YC demo.
Speaker 2:Okay. Where were present?
Speaker 11:We were were doing this voice recognition app called Sonolite. Okay. It was like an early version of Siri before Siri. Interesting. And it, like, listened to you in the background so that you could safely talk to it.
Speaker 11:Like, you guy had this really sick demo where, you know, you had your phone and you put it in your pocket pocket and you had a conversation and people were like, woah. This is the coolest like Star Trek. This is the coolest thing ever. So
Speaker 2:we're close to the AI pin.
Speaker 11:You It's funny. It Timing. Voice was was just not good enough as a technology then.
Speaker 4:Yeah.
Speaker 11:Ten years later, it actually might break through, which is funny. But, anyway, we pivoted that into Amplitude, and the very first version was mobile analytics. Mhmm. We saw mobile taken off like this.
Speaker 2:Yeah.
Speaker 11:And we said there is a whole set of infrastructure companies gonna be built to make those companies successful. So, you know, companies like Snapchat or Instagram or WhatsApp or YouTube or Yelp that were just and and then a lot of people were accessing the Internet for the first time on mobile. You had people coming online in Asia and Africa, and we said, okay. Let's go bet on this, and let's build a company that, that solves a lot of their infrastructure and and data analytics problems because we had those same problems at Sonolite. Fast forward today, now we're
Speaker 1:doing That means that means you got you were getting some some users for the first product. Like, if you
Speaker 11:For Sonolite?
Speaker 1:Yeah.
Speaker 11:Yeah. We got we got, like, a few 100,000 downloads.
Speaker 1:So Oh, pretty good. Yeah.
Speaker 11:You know, someone who wasn't us well, I think you guys are much more successful consumer guys than I am, but, someone who wasn't us was using it. So that was good.
Speaker 2:No. I I I launched an iOS app in YC summer twenty twelve, and I think I got, like, 500 installs. It was a disaster. I didn't understand. Was like, first half.
Speaker 2:It's really, really hard. So, yeah, a 100,000.
Speaker 1:Well, yeah. And I and I just asked because you don't you don't discover all these different pain points and problems unless you actually have some some element of scanning. Yeah. What was the first
Speaker 2:use case for mobile analytics? Is it like conversion rates, AB testing? Like, what were what were the killer features?
Speaker 11:The key question people wanted to know was what actions lead to long term successful usage.
Speaker 6:Sure.
Speaker 11:So we wanted to know, the accuracy at Sunlight, does the accuracy of voice recognition matter for someone's long term engagement? Turns out it's massively matters. If you have a first successful voice recognition event, you're twice as likely to stick around long term.
Speaker 2:Yeah.
Speaker 11:And it turns out every single product needs that same intelligence. And so all the different startups in our batch were like, hey. Can I get that data analytics when we'd show them you know, they're more interested in that than what we're doing on voice recognition with Sonolite? Because to my surprise, like, even companies like PlanGrid, which were very, very successful in our batch and kinda one of the stars coming out, were like, I don't even know the the first thing about what causes my users to stick around. Yeah.
Speaker 11:So we ended up building that. You know, we've helped companies over the years like DoorDash, Calm, Peloton
Speaker 4:Oh, okay.
Speaker 11:Tons of others. Now we're working foundational model labs to help them as well Sure. Understand the same things.
Speaker 2:Yeah. How power law driven is the business? I imagine that there's, like, a really long tail of just so many app developers that need analytics. Then at the very, very tippy top, you probably have, like, you know, some of the hyperscalers that are like, hey. We'll do it in house.
Speaker 2:But is that the right way to
Speaker 1:think about the market structure?
Speaker 11:Yeah. It it it definitely is. I I think one of the surprises is just how widespread this need is. Mhmm. And so it's not just within technology.
Speaker 11:It's like quick service restaurants. So we have Panda Express and Chick fil A and, you know, Jersey Mike's as as customers of ours. We have media companies like NBC. We have Sure. And and Fox.
Speaker 11:We have you know, it's like everyone needs this. And then in terms of the actual breakdown of our ARR, it's we have over 40 companies above 1,000,000 in ARR Mhmm. Which is very concentrated for someone of our size and stage. And I think from my standpoint, speaks to how deep this pain is. If you really need this, you really need it, and you're willing to spend, we're often the largest spend in someone's stack.
Speaker 2:Wow. Talk to me about how the analytics are changing in the age of AI. Are you rolling out tools that will, like, build an iPython notebook, write pandas, like, do SQL queries? Like, I imagine that the previous era was very much like, great. You you got the data together.
Speaker 2:Now hand it over to me, and my data scientist will write a bunch of Python to actually interpret it. How much of that is changing and happening in house now?
Speaker 11:Oh, it's it's it's completely changing. So the key issue is that you had to be familiar with SQL. You had to be familiar with data taxonomies. You have to be familiar with how to do a funnel analysis, like all these pieces of specialized knowledge. And so today, we launched an AI agentic analytics platform with Amplitude where you can just type any free form question and then get an answer back, and it'll do the the the deep work of figuring out how to translate it to a query, how to use the right tools, how to map it to your taxonomy.
Speaker 11:You don't need to know any of that. You can just say, what are my DAUs? Or what's the worst step in my conversion funnel, and then how do I improve it? And it'll come back with a whole notebook and analysis of results all with an amplitude. Mhmm.
Speaker 11:You could also connect it via Slack, so you can just connect our Slack bot, have it hit our m have have it hit our MCP server, and then it comes back with this, like, very rich dashboard and widgets and and text responses that's formatted that tells you all about it.
Speaker 2:Yeah. Talk about the SaaSpocalypse. Are you worried about people vibe coding their own in house version? Like, what are you seeing on the ground? What, what do you think, like, long term moats and software look like?
Speaker 2:Is anything
Speaker 1:Yeah. And I think there's there's there's like a two things, like Yeah. What what what happens to the core business? And then, how do you create net new products Yeah. Or this new kind of, like, category of company that has entirely new kind of needs around understanding how their products get used and all that kind of thing.
Speaker 2:Yeah.
Speaker 11:So first on SaaS, I think the key lesson is the software you've already built, that is no longer remote. Because to your point, whether it's someone vibe coding it or someone going after as a company, they can replicate it pretty quickly. Mhmm. And so the new key mode in my mind is it's it's a little trite, but speed of innovation. Mhmm.
Speaker 11:Have to be pushing the bleeding edge of what capabilities are, and that's what customers and if you do that and you create a company that can do that, that's what customers will buy. And so what I think the SaaS apocalypse has actually gotten right is if you look at the median SaaS company whether it's you know a few 100,000,000 ARR like us or whether it's in the billions, the median SaaS company, their innovation has actually slowed to a standstill.
Speaker 3:I don't
Speaker 11:know if you guys have ever been inside of these. Yeah. But it's it's crazy how little that they they ship in terms of net new products. You know, they'll put some nice branding on it. They'll be like, oh, introducing our new Salesforce AI agents.
Speaker 11:But then it's like, okay, this is the same thing you guys had last year. Like, why like, what are we doing here? And so I think the difference is speed of using the bleeding edge of these model capabilities is all that matters. And you're even seeing it in foundational model companies. It's right like, okay, Opus was the hottest thing, you know, a week ago, then it was Codex literally launched the same day and said, hey, we're even better and we're faster and we're on Cerberus trips and and all of this stuff.
Speaker 11:And so I think it just matters the rate of improvement. The the analogy I've heard for software that I actually like by one of my one a former Amplitude investor is it's like sushi. And so buyers are always gonna want the best thing. And so if you're keeping up with innovating the best thing, you will be able to charge a premium. And so, you know, it's fine that the gas station at the seven Eleven at the gas station now sells sushi.
Speaker 11:You know, it's not gonna put, you know, Jiro in Japan out of business. Yeah. And so for us, the lesson is, okay. There is no moat anymore from what we've built. There's only a moat if we're able to deliver the most bleeding edge capability.
Speaker 2:Yeah. How do you think about other moats that could potentially relate to what you're doing? I'm I'm just thinking about, like, we were talking about, just email delivery. Like, there is a way to get a web server to send a to send an email, but there's all this trust that's built up around email delivery rates. And so you're probably better off going with a company that has a lot of experience there, understands what Gmail likes and sets rate limits and has a history of, like, good behavior.
Speaker 2:And then you were talking about payment rails and all the bank licenses and money transfer licenses. Have you have you have you started thinking about, like, other pools of moats that might exist in in software companies as the divide grows between, okay, you have a stagnant pile of code versus a company that's actually being agile, innovating, and carving out new moats and digging existing moats deeper?
Speaker 11:Honestly, I'm at least at Amplitude, we're kind of full send on this SaaS is dead, AI is the future. And so we're just assuming Yeah. For our business that, like, it doesn't matter, you know, what we built to date and all that matters is can we deliver, you know, an AI analytics future. Yeah. And so I'm sure there's gonna be moats like you described where you get weird interfaces in the human world.
Speaker 11:But I I I actually believe in the thesis that Mhmm. I think a lot of specialized skill sets are dead. Mhmm. And if you look at I don't know
Speaker 1:if you
Speaker 11:guys have ever read the Bitter Lesson.
Speaker 4:Oh, yeah.
Speaker 2:Rich
Speaker 11:Sutton. Rich Sutton. Yeah. You know? And and Dario was actually, recently talking about that as well on on the Dwar Kesh podcast
Speaker 2:Yeah.
Speaker 11:Where the all that matters like, specialized skill sets go away. All that matters is scaling these different variables. So compute, training time, quantity of data, breadth and quality of data. Yeah. And it it doesn't really like, all these places where you could eke out a job because you have some specialized knowledge in a niche, I think are are gonna completely go away.
Speaker 11:Mhmm. And so and that goes for the companies too where, you know, a lot of them are giving lip services AI stuff, but, you know, you look at your median SaaS company again and it's like, okay. You know, we rebranded some stuff, and maybe we have some cool, you know, one little AI feature here, but that's that's kind of all they've done.
Speaker 2:Yeah. What about, just, like, just being reinvigorated? I mean, where where were you? YC 10 or 11?
Speaker 5:Win or 12?
Speaker 2:Yeah. Like, it's it's an overnight success. It's been fourteen years. But at at some point, you know, it can get exhausting. Has the AI boom sort of reinvigorated you, reinvigorated the team?
Speaker 2:And then and then what changes have been made to the the individual roles of folks on the team to actually diffuse AI into everything that you do?
Speaker 11:Yeah. I mean, we're super excited. The team has been very excited. I I think the biggest thing we're seeing is specialized skill sets are going away. Mhmm.
Speaker 11:And so if you're an engineer, you have to think about whether what you're building customers actually use and want. Mhmm. If you're a product manager or designer, you're actually shipping code. Like, we see, like, one of our best designers is is shipping code Wow. On a daily basis here, which is pretty crazy.
Speaker 11:I wouldn't even thought that were possible a year ago. And then I I think it extends beyond the the engineering and and product and design functions. I think you look at go to market, I think the same thing's gonna happen. Like, you're still gonna want salespeople because we as humans naturally respond to other people and, you know, we much like rather talking to a person than AI and and and AI. But all the kind of specialized niche skills like, oh, I know how to write an earnings call script or a blog post or file a form four or, you know, do this legal review or create an infographic.
Speaker 11:I think a lot of that is gonna go away, and instead you're just gonna be left with high agency people who just know how to use AI.
Speaker 1:Yeah. What are like, we've seen so many different products explode from zero to hundreds of thousands or millions of users really quickly. Part of that is because, you know, models are this sort of magical technology that we're still processing, right? We've seen this with, you know, back what what was it? Like two, three years ago when you had that that, image generation company that would make, you know, do like headshots.
Speaker 1:You remember this company? You have this magical technology. It can cause like really fast explosive growth. There's like this urgency from this early adopter crowd that will just try anything at least once. Like historically, if you're making a digital product and you're using Amplitude, you'd be able to see like, okay, if somebody signs up and they use the app three times in the first three days, there's an 80% chance that they'll still be using it in the sixth month.
Speaker 1:What point can you kind of see through all the noise and the chaos with some of these newer digital products that are leveraging AI and realize that you have something like sticky? Are there kind of new new indicators? Or is it or or or is there still something to be learned from the sort of like approach to retention analytics from maybe a decade ago?
Speaker 11:So the core is the same thing, which is you want users to use your product and get a ton of value over time. So you're still looking at do they retain, you know, one, two, three months down the line. But what you're looking at upstream is different. So you're gonna be looking at what sort of prompts is someone putting in. Is it getting them the result they want?
Speaker 11:Did they seem to like it? Did they reshare it? And so one of the things we're doing is actually building LLM analytics internally, and we're partnering with a number of our AI forward customers that, you know, have chatbots or, you know, are building models to see, okay. Well, does this sort of response get better engagement than this sort of response or or vice versa? And so you do need some customization to do that because you wanna look at these traces in real time.
Speaker 11:You wanna understand the sentiment. You wanna figure out how to, you know, what sort of context you can give it to give it a better response. But you're still can like, the thing that hasn't changed is you're still connecting it to long term engagement. So I know if they're still retained after three months in subscribing, that's a great outcome. So I just want behaviors, at the start that correlate with that.
Speaker 1:Yeah. That makes sense.
Speaker 2:Two somewhat unrelated questions to the core business, but, what can you tell us about how the iOS app charts work, about how they work? Because I imagine that you see analytics, and then we see the charts and, everyone has this feeling that the charts are based on momentum. How real is that? Like, what does it take to chart? How confident are you in people gaming the charts or, you know, how do you think about charting in the App Store broadly?
Speaker 11:That's so funny. I dude, this is a a blast from, blast from the past. Like, this is like a typical question we get in, like, 2014. Yeah. Charting is at least from what we've seen, charting is not the best way to get distribution anymore.
Speaker 11:You wanna get it through other channels that are whether it's viral, whether it's, like, you know, own media, whether it's, you know, just a community of influencers. It's like very, different adoption. As far as I can tell, I mean, the guys at Sensor Tower would probably be able to give you a better answer than this. It is very much how many people downloaded it in the last, you know, twenty four hours, seven days
Speaker 2:Got it.
Speaker 11:And then what's the change in that over time?
Speaker 2:Yeah. And that's why we yeah. And that's why we see, like, the the Meta Quest, charts, like, right around Christmas because everyone's getting an Oculus.
Speaker 11:Oh, yeah. It's just, like, spike up.
Speaker 2:Totally. Spike. And there's it's always fun checking the charts after Christmas because you're like, oh, here are all the toys that did well. Very, very interesting. Do you keep you you worked as a algorithmic trader at DRW Trading?
Speaker 11:DRW Trading. Go a little Don Wilson.
Speaker 2:Yeah. Do you, do you keep up with any of those folks? Do you have any ideas or predictions about how AI will impact trading firms?
Speaker 11:Don, you know, I'll just tell this quick story on Don. He is fucking next level. He was out here in Silicon Valley, and I randomly bumped him to him at a party two years ago. Really? And he was like, oh, we're trying to create models that, like, build the the the bleeding edge of what might happen in markets and incorporate all this data, whether it's geopolitical or macro or, you know, what whatever else.
Speaker 11:And I'm like, holy shit. And he was physically out here in person so much so that he had gotten a gotten a place out here in the Bay Area even though he's in Chicago. So I'm like, wow. This guy is next level.
Speaker 3:So in.
Speaker 11:I I I think it will I I think it will dramatically change
Speaker 2:Mhmm.
Speaker 11:In that. If you can create models which take in all these different data sources, and then the the lesson from deep learning is if you just get continued scale, you will all sorts of trends and underlying structure is gonna pop out that you didn't even expect was was there. So I I think the I think the high frequency trading firms that figure it out will do incredibly well, and they'll leave
Speaker 1:Yeah. Old guys just Chalet was posting yesterday or the day before saying, like, one of the first signs of, like, a, like, ASI Super intelligence. Will be a hedge fund that is just so dramatically
Speaker 2:Just printing. Outperforming. He was like, they made 10,000,000,000,000 this quarter? Would you bet on a
Speaker 11:Plus, that's why that's why they gotta have the wealth tax to redistribute it.
Speaker 2:Yeah. Yeah.
Speaker 1:Sorry. Bad joke. Would
Speaker 2:you bet on a, traditional trading finance background getting up to speed on AI or an AI lab learning finance? If you had to back Yeah.
Speaker 11:Definitely the labs are one of these engineers learning finance. I mean
Speaker 2:Really?
Speaker 11:I I I mean, when we went into high frequency, know, it used to be the finance world was filled with jocks. Right? Yeah. You know, it's like chest thumpers that, like, did, you know, hundreds of phone calls every day.
Speaker 2:Yeah. Wall Street.
Speaker 11:Yeah. Yeah. Exactly. When I went into it, you know, the nerds were just beginning to become hot. And so you wanted these people with math PhDs or, you know, physics Nobel Prize or Mhmm.
Speaker 11:Or whatever else. And it's like, yeah, they're gonna outthink you. Mhmm. And so it's it's just gonna go more in that direction. Yeah.
Speaker 11:You know, the the old days of the the finance pro is is gone. So
Speaker 2:The revenge of the nerds is upon us. Oh, yeah. Last question for me. Do you skate? Do you skateboard?
Speaker 11:Oh, absolutely. Really?
Speaker 1:That's good.
Speaker 11:That's amazing. You got it. You roller skates, not ice skates.
Speaker 2:Not not What about ice skates? My brother skates sports. The winter it's the Winter Olympics. You ever get out
Speaker 11:Oh, dude. I'd never be able to compete at that level.
Speaker 2:No. No. But, you know, it's like if it's Christmas time, you go out with the family. I don't know. You you put on some ice skates.
Speaker 2:It's a nice wintry activity I participated in.
Speaker 11:It's great great first date idea. I'll tell you that. Okay.
Speaker 1:Yeah. That's great.
Speaker 2:Well, fantastic. Thank you so
Speaker 1:much for coming. So great to finally have you on. Okay. Yeah. Hop on anytime.
Speaker 2:Yeah. We'd love that.
Speaker 11:Thanks, Jordy. Thanks, John.
Speaker 1:We'll talk to you soon. Cheers, Spencer.
Speaker 2:Have a good rest of your day. Goodbye.
Speaker 1:And Let's see. Back to the Back to timeline.
Speaker 2:Phantom cash. Fund your wallet without exchanges or middlemen and spend with the phantom card with phantom cash. Estimated ownership in anthropic of various corporations. Amazon has around 15%. Google has 13%.
Speaker 2:NVIDIA has 2%. Microsoft has 1%. Zoom has almost 1%. Salesforce has a little under half a percent. And, SPF also has a huge stake.
Speaker 2:Although I think that that's transferred at some point. I wonder where those shares actually went. I don't I have yet to get to the bottom of that.
Speaker 1:I think I think a lot of those positions got bought out at the time of bankruptcy in Yeah. Order to No. No. They they are still owned. Somebody bought them.
Speaker 1:I I remember I I believe that the cursor position traded at, near the like, that that was a situation in which kind of the vultures kind of descended. Mhmm. They were like, there's some good assets in here. Mhmm. The, you know, bankruptcy process obviously needs liquidity to pay back the people whose money was used to fund the investments.
Speaker 1:Yeah. But but, yeah, let's love to see last time Benioff was on, I think he said they had around a point, and so may have been diluted since then, but maybe more than
Speaker 2:Yeah.
Speaker 1:Maybe more than that half a percent.
Speaker 2:Well, we have some new Sonnet 4.5 is out from Anthropic.
Speaker 1:4.6.
Speaker 2:4.6. Sonnet 4.6. They say it's our most capable Sonnet model by far.
Speaker 1:It's newer. Faster.
Speaker 4:Faster. Faster.
Speaker 2:Thinner. Thinner. In many areas. Very excited for folks to try this one out says Alex Albert over in Claude, the Claude relations department at Anthropy.
Speaker 1:Will Brown says, Sonnet 4.6 is the first flagship LLM since Bloomberg GPT to be targeted primarily at the finance crowd.
Speaker 2:Bloomberg GPT 4.6. It does well on agentic financial analysis and office tasks particularly well. Yeah. Neck and neck with some other stuff but does pretty pretty well. Let's see what else is going on.
Speaker 2:We have Plaid. Plaid powers the apps you use to spend, save, borrow and invest securely connecting connecting bank accounts to move money, fight fraud and improve says
Speaker 1:Manus Manus has entered Instagram.
Speaker 2:Yes.
Speaker 1:It gives you an overview and it says you've reached a 120,000 accounts, create a content strategy with Manus based on the success of this reel. Yes. And then apparently, it just takes takes you straight to the Manus homepage.
Speaker 2:Oh, really?
Speaker 1:So not super integrated yet, but driving driving leads.
Speaker 2:There's also drama at the Olympics. Curling is in the
Speaker 10:hot seat.
Speaker 1:This is crazy. Crazy.
Speaker 2:Amanda says, I'm obsessed with the curling drama. What do you mean? The Canadians are such consistent and known cheaters that the Swedes were willing to set up a sting operation to catch them in the act, which they knew would happen because, again, they keep cheating in the same way every time. It's difficult to assign intent, but it does seem like the Canadians are cheating and in this exact way because they know that the usual cameras that cover curling matches do not cover the angle that would catch them, which is why they're mad at the Swedes for setting up the camera. And so Yeah.
Speaker 1:What was
Speaker 2:headline is the Olympics have been rocked by a cheating scandal in curling. Good pun there because I think the curling stone is called a rock. The double touch and the hog line are at the center of controversy that has Swedes tattling and Canadians cursing. The Olympics are where human beings accomplish the impossible. Skaters blaze down mountains at 90 miles per hour.
Speaker 2:Skaters spin four times in the air and land on a pair of knives. And Canadians, by reputation, the nicest folks in North America transform into something else altogether. The expletive spewing potential rule breaking rule breaking villains of the games. Canada's heel turn has come in curling of all sports. The saga began Friday during its men's match against Sweden when the Swedes accused Canadian curlers of grazing the stone with their fingertips after they'd already released it.
Speaker 2:The move is known as a double touch and is highly illegal. Canada's Mark Kennedy took the allegation sadly. So
Speaker 1:wait, Canada's still competing Well even though they were caught in four ks.
Speaker 2:Well, they were they were accused of cheating by the Swedes not by the Olympic governing
Speaker 1:body insane. So they got a passive There's a video of it. You can see him doing it.
Speaker 2:I don't know. Can you? I don't I haven't seen a video that convinced me. Innocent until proven guilty. There is
Speaker 1:You haven't seen the video?
Speaker 2:I haven't watched the video.
Speaker 1:So Who knows? It's absolutely blatant.
Speaker 2:It is? You saw the video. Yeah.
Speaker 1:It's blatant. It's completely think we have our next guest, so we won't pull it up now.
Speaker 2:Well, we will pull up public. Investing for those who take it seriously. Stocks, options, bonds, crypto, treasuries, and more with great customer service. Let's bring in from Dragonfly. We have the lightning round is starting.
Speaker 2:Thank you, Ben. The the lightning round is beginning now with Hasid Qureshi from Dragonfly. He's the managing partner and he's here.
Speaker 1:What's going on?
Speaker 2:The TVPN Ultra. How are you? Thanks so much for joining. Good. First time on the show.
Speaker 2:Please
Speaker 1:Yeah. I've been
Speaker 2:looking forward to this. An introduction.
Speaker 8:Yes. So I'm Beside, managing partner Dragonfly. We're a $4,000,000,000 crypto VC firm. Actually, today, we announced our fourth fund. Oh my god.
Speaker 8:We got overshadowed a little bit by Thrive. I think they Oh, yeah. Called MOGging.
Speaker 1:Yes. We did get MOG It is called it is called MOGging.
Speaker 2:We'll still ring the
Speaker 1:gun. How much
Speaker 2:the rest?
Speaker 1:There needs to be some organization that we're still we're still hitting the big the big the same Gong the same Gong that we hit for Josh. Yeah. There needs to be more we got three sixty five days a year. And if you're raising a fund, there's gotta be some governing body that dictates Rolls out. Yeah.
Speaker 1:If you're a $100,000,000 plus, could only
Speaker 8:think that he'd be coordinating with us, but somehow, yeah, the AI guys, they don't really care about the crypto guys anymore. They just overshadow us.
Speaker 1:Okay. Okay.
Speaker 2:How focused is the fund on crypto? Is it a 100%? What are
Speaker 8:the 100% on crypto.
Speaker 2:And are the are the lines blurring as more I mean, we we we know some folks who are, like, ostensibly doing crypto, but it's, you know, AI training, distributed compute. And so crypto is starting to touch more and more pieces of the tech economy. Where how how are you even processing
Speaker 8:the directions. Yeah. Yeah. So I I think we can see on the one hand, so we're investors in Polymarket. Polymarket now is becoming increasingly you know, a lot people don't even know that Polymarket is crypto.
Speaker 8:Yeah. The original Polymarket application was entirely on chain on Polygon. Yep. They're now launching their US app. But Okay.
Speaker 8:Before that, basically, you know, today, unless you were on the US app, you were using you were using it on chain. Yeah. If you look at increasingly a lot of the apps that are really working crypto are more fintech y, and we're seeing a lot of fintech investors coming up against us in a lot of these deals.
Speaker 1:Yep.
Speaker 8:And then, of course, like you mentioned, crypto is increasingly bleeding over with AI. Yeah. There was just this acquisition of OpenClaw. I think it was yesterday announced that OpenAI is acquiring them. Sure.
Speaker 8:The Moldbook drama, if you go on Moldbook today so I still look at Moldbook every day, and most of the highest ranked things on Moldbook are all crypto related. It's all almost all of
Speaker 1:it is that is that because people are trying to create is that because people are creating projects? Clear.
Speaker 8:There's a there's a lot of bullshit. There's a lot of bullshit going on right now in Moldbook.
Speaker 1:They're like, you don't even need users now. You just create a million users for your project.
Speaker 8:That's right. That's right. Look. It's the infinite variety of people will always find ways to try to make money from anything. And crypto, it both represents the best in humankind and the worst in humankind.
Speaker 8:And it's part of the reason why it'll never go away. No matter how unseemly or distasteful or just insane it becomes, it just never dies. So it's something that I I was just reflecting on because we're we're now eight years into Dragonfly. It's been a long time. Been a lot of cycle.
Speaker 8:We're now clearly in a trough of this cycle. Sure. Sentiment in Cryptoland is extremely low right now. Yeah. But on the other hand, like, the actual adoption, you know, stable coins Mhmm.
Speaker 8:You see all these financial institutions coming into the space. You know, multiple of your sponsors are are crypto sponsors. They're they're seeing their underlying traction go up even as prices are going in the other direction. So I feel really good. And it is bleeding into everything, like
Speaker 2:Quick quick update on Mold Book. 2,800,000 AI agents have joined. There are over 1,400,000 posts and over 12,000,000 comments now. So still still cooking on stillmaltbook.com.
Speaker 1:Still kicking. Where are you what what's the yeah. It felt like prediction markets were the product that kind of broke out fully maybe last cycle, some of these cycles blend together as different products get traction. Where are you most excited to invest the new fund that you guys haven't necessarily invested before that we're still in this kind of moment as as various laws work their way through Washington trying to figure actually get clarity on some of these things. So but what are you most excited about over the over the kind of fund life cycle for Front four?
Speaker 8:So there's the core bread and butter of crypto, which is just the financial applications. Actually, I recently got into an online debate with Chris Dixon
Speaker 2:Mhmm.
Speaker 8:Who you know, he's he was kinda coming out giving this big expose about, oh, well, you know, all the nonfinancial applications of crypto is just too early, and we still gotta give them time to bake, and maybe they're gonna come back. I sort of took the other side as I think it is largely a death knell for the nonfinancial applications of crypto. Yeah. Crypto's about money. It's about finance.
Speaker 8:Always has been. From the very beginning, whether it's Bitcoin, you know, Ethereum being programmable money, to ICOs, which are fundraising, to DeFi, which has finance in the name, almost everything that's ever worked in crypto has been financial in nature. And everybody who's tried to make nonfinancial things plug into crypto has basically failed. Now I think the the what falls under that umbrella is pretty big, and I actually do think AI does fall into that umbrella. But it's more the ways in which agents are going to be interacting with money.
Speaker 8:That very clearly I mean, you can see it right now in Motebook. You go in Motebook, and you can see that agents are trying to find ways to pay each other for things and to get each other to do things for them. It's very primitive right now. You can you but you can see where it's going. You can draw the line out about you know, if if you're an agent if I have an agent, you have an agent, you live in a different country or maybe I don't even know who you are.
Speaker 8:I don't need to know who you are if you're somebody else in notebook. It's very difficult for me to pay you with a traditional financial system. It's not really designed to have nonhuman recipients of money. We don't really know how the laws are gonna work, how taxes are gonna work, how money laundering is gonna work, whereas crypto doesn't ask any of those questions. Crypto was really designed for machines more than it was designed for humans.
Speaker 8:Mhmm. And so I think we're gonna see this become an increasing part of the story of how AI agents are going to become more and more autonomous and, you know, self driving financially is by giving them crypto and allowing them to just interact with other agents and other systems using using crypto rails. So I'm I'm very intrigued by that. Yeah. But the core trend of crypto is just more and more of the same.
Speaker 2:Interesting.
Speaker 1:How do you how do you invest in, like stablecoins as a category going forward, giving you have I put
Speaker 2:a ton of money on stablecoins. I've lost anything. I mean, I haven't made a lot,
Speaker 8:but They've done really well compared to Bitcoin.
Speaker 2:Well compared to Bitcoin.
Speaker 1:Outperformed. But you have a bunch of startup players, you have big institutions, like it feels like I'm wondering where there's white space, where where you think there's still there still could be white space given that we know there's so much growth that's gonna happen. That that part feels inevitable, but where does the value actually flow and what where what are the opportunities for start ups?
Speaker 8:So I think everybody at this point is bullish on stablecoins. Right?
Speaker 1:So Yeah.
Speaker 8:Secretary Besson has said he expects stablecoins to hit 3,000,000,000,000 by the end of the decade. Right now, they're about 300,000,000,000. So that's like a 10 x in the span of, you know, call it four to five years. Now I I think that's pretty optimistic. I don't know that we're gonna hit that kind of growth rate, but the the numbers are clearly growing, and they're growing every single year, like, sixty, seventy percent year over year.
Speaker 8:Now how do you make money on that? So one way is to own a stablecoin issuer. I think that's pretty tough at this point. Right? You can see it's basically a duopoly between Circle and Tether.
Speaker 8:Circle's already public. Tether is private, but they're, you know, supposedly raising around at 500,000,000,000. It's there's not there's not a lot of meat on the bone if you're investing at 500,000,000,000 into a stablecoin issuer. And the the economics are really good at being a stablecoin issuer, but it's basically being a bank. Right?
Speaker 8:And it's it's it's it's the modern financial institution, except they have a 100% net interest margin, which is which is great. Is are there gonna be new stablecoin issuers who show up now? If there are, they're probably gonna be GSIPS. Right? They're not gonna be some new startup that comes up with a new way to launch the same product, which is effectively just, you know, a narrow bank.
Speaker 8:I think the place where you want to be investing as a VC is more in the interstitial layers, which is how is this stuff going to move around the world and get into the hands of a user wherever they are? So one of the investments that we've made recently is a company called RAIN, which basically Oh, yeah. They do these Stablecoin cards. Right? And and they allow you let's say you're in some country where you you're using some fintech app that's allowing you to get access to Stablecoins.
Speaker 8:Let's say you're in Argentina. You're in, you know, you're in Nigeria. You're somewhere where you really want stablecoins or you want dollars. You don't even know that they're stablecoins. A lot these apps, the users don't even know that there's crypto underneath the rails.
Speaker 8:They just know that, you know, they send the naira, they get USD, and they can send their USD overseas to somebody else. The problem with all these apps is you can't pay anybody who's not in the app. You can't pay anybody who doesn't directly take crypto or they're not sitting on the same fintech as you. And so these cards, you can basically issue cards against your stablecoin balance. And the moment you swipe your card, whether you enter it into an app or you tap to pay or whatever, it debits stablecoins and settles directly on VisaNet using stablecoins.
Speaker 8:Visa has now seen these as one of the fastest growing use cases for Visa around the world, and they're just growing like gangbusters. You know? It's, 20% month over month growth. This, I think, is going to be the way in which you see stable points go global is that they just get more and more integrated into the normal payments workflows for people.
Speaker 1:So How what what do you do you look at do you do you see much geo broad geopolitical risk to stablecoins if I'm a country and I have a currency and suddenly all my
Speaker 2:A lot
Speaker 1:of dollarized. All my citizens say well, actually, we like USCC At or what point does that become, you know, such a such a threat to the country's own monetary system that they need to, you know, pass new regulations and that kind of thing?
Speaker 8:It already is. So a lot of the countries that have a lot of stablecoin adoption, stablecoins are per se illegal. You know? If if if you go to Venezuela, you go to China, you know, buying things with dollars is is illegal in size. Right?
Speaker 8:And that's why these are black markets. Most of these places, like, you know, Venezuela very famously, there's a very different price for the Bolivar in the, quote, unquote, you know, lit market as opposed to on the black market where people are actually transacting with dollars. Any of these places where you have very high inflation, you see this. Now in the past, especially pre COVID, the way that this was done was you imported little green piece of paper, and that's how these countries dollarized. That's not happening anymore.
Speaker 8:Increasingly, the way in which these countries are dollarizing is they're dollarizing digitally. They're dollarizing from the ground up. And that's much harder to police. Right? Because the reality is that all you need is a mobile phone and an Internet connection, and now you can get stablecoins no matter where you are anywhere in the world.
Speaker 8:All you need is somebody who's willing to trade you the local currency for that stablecoin. So I I I think the the right way to think about this is not, okay, when are governments gonna push back? They've they're already pushing back, especially if you're in a country that has very high inflation. Why do they have very high inflation? The answer is because the governments are printing a ton of money to bake up for the fact that they're spending like drunken sailors.
Speaker 8:Right? It's a it's a way to tax your citizenship when you cannot actually extract that through taxation. So in in every technology renegotiates the balance of power between individuals and governments. The Internet did the exact same thing. Information technology did that with respect to the dissemination of of information.
Speaker 8:Yep. I think what you'll see is that crypto does that with money. Is the presumption was always that this narrow waste of the banking system was always controlled by the government. And it's easy to control because it's very centralized, and banks everywhere in the world are basically nationalized. You know, even even when they're, quote unquote, private companies, they're essentially controlled by the government.
Speaker 8:When that's no longer true, when basically you can exit by going on chain, by going to the blockchain, by going to a stable coin, then now that is a check against every government and every form of profiligate spending everywhere in the world. I think that's ultimately good. Competition is almost always good. Yeah. Now it's it's disruptive to a lot of countries that will say, hey.
Speaker 8:This is terrible. You know, The US is attacking us or, you know, blah blah. There's there's gonna be all sorts of ratcheting up of geopolitical tensions. You saw this, by the way, in Nigeria. I believe it was Nigeria where there were Binance executives who got detained by the Nigerian government under the claim that Binance was assisting in, you know, tax evasion and all this other stuff, which is basically another way to say that they were allowing the the the sale of stable points in the country.
Speaker 8:And it was a huge political flashpoint, and they ended up having to get the secretary of state to negotiate with them to get those to get those executives out. But I think that's only the beginning. You're gonna see more and more of this. And I think this is very intentional by the US government. Right?
Speaker 8:Like, Besant has said very clearly, a big part of the reason why stablecoins are good for America is that they increase the demand for treasuries. They increase the demand for dollars and they increase the demand for treasuries. Yeah. Where is the demand coming from? Obviously, coming from people who don't want their citizens to be holding our treasuries.
Speaker 2:Sure. Yeah. That makes a ton of sense. Thank you so much for coming on the show. Congrats on the massive fundraise.
Speaker 1:And I'm sure we'll have a bunch of of your companies on.
Speaker 2:Yeah. We're looking forward to it. Yeah. Have a good rest of your day.
Speaker 1:Finally meet.
Speaker 2:Michael. We'll talk to you soon.
Speaker 1:Congrats to the team.
Speaker 2: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. We will continue our lightning round with Celine, hallelujah, from Loyal. Celine, how are you doing? Good to see
Speaker 1:you, guys.
Speaker 12:Good to be back.
Speaker 2:You got some big news for us. What happened?
Speaker 12:Raise a hundo milli.
Speaker 1:Woah. Big day for our Gong. Big day for the Gong. Everyone
Speaker 2:took yesterday off and was like, I'm dropping a big number on Tuesday. What's the what does this unlock? Like, what's the next step in the company's mission?
Speaker 12:Get this goddamn drug to market and launch the first FDA approved longevity drug.
Speaker 8:Mhmm.
Speaker 12:Just just do that.
Speaker 1:Just that. Yeah.
Speaker 12:Yeah. And build our pipeline and all that shit too. But, like, honestly, man, I'm just, like, locked in on getting that first FDA approval. It's been six years of work.
Speaker 2:So what does that mean? Hiring more lobbyists, lawyers, doctors, scientists? No. Who are you bringing on with this new money?
Speaker 12:It's actually spectacularly boring. Mhmm. It's literally just time. Like, so much of developing a drug is, like, you put the drug on a shelf. You wait for it to age.
Speaker 12:You quantify how it ages. That tells you its shelf life. You send something to FDA. They reply six months later. Mhmm.
Speaker 12:So there's obviously, like, we're spending on things like product expansion and commercialization. We're, you know, doing an owned commercial strategy. But Mhmm. Honestly, our biggest burn driver is just time.
Speaker 2:Okay. Unpack the owned commercial strategy. What does that mean?
Speaker 12:So when I started loyal five years ago week, I kinda had this thesis of building a
Speaker 5:pharma brand
Speaker 12:that people love.
Speaker 2:Mhmm.
Speaker 12:Right? This idea of building a consumer brand around a pharmaceutical product, which five years later is like super normalized with Ozempic and GLP-1s. Like, everybody's like going to peptide parties in Silicon Valley. Like, everyone knows Ozempic and Mounjaro and all that stuff, right? But before that, really the only consumer marketed drugs were like Botox.
Speaker 2:Oh, yeah.
Speaker 12:So we could sell out. That's like what most pharm biotech companies would do right now. Can like go buy a small, maybe medium sized island. Mhmm. But I think it's much more exciting to commercialize it and build a consumer brand around this pharmaceutical
Speaker 2:Mhmm. What what's the impact of the GLP one boom on your business? Is that these they feel like almost longevity They're definitely life extending for a lot of people. Yeah. But is that gonna actually change anything in the market or at the FDA?
Speaker 12:I think it has really changed how people think about the biology of aging. Right? It was so difficult to explain these drugs before. Like, oh, it's this one drug. It has this one mechanism.
Speaker 12:Mhmm. But it'll help this aging phenotype and that aging phenotype and this bad thing that happens and that bad thing that happens. People are like, But how can that happen? It's a drug. It's only hitting one thing.
Speaker 12:And now they're like, Oh my god, GLP-1s. They like, you know, make you lose weight and your metabolic fitness is better. My god, you're not addicted to things anymore, and there's just 10 other magical benefits that see that happen. And it actually makes total sense, right? Improving metabolic fitness improves basically everything downstream of that, but the general public had not been exposed to that writ large until GLP-1s.
Speaker 12:So I think people really understand an aging drug a lot better now, and it sounds a lot more real now than it did, you know, before a year or two ago.
Speaker 1:Are people giving GLP ones or peptides generally to their dogs legally?
Speaker 12:No. Have you
Speaker 1:heard about have you heard about it?
Speaker 12:No. There there's a couple people trying to do GLP ones for dogs, and cats. I think it, like, could maybe make sense for cats. I have a really fat cat that, like, maybe could benefit. But, people don't want their dogs to not have appetite, motivation, and drive.
Speaker 12:This is like a whole thing. You know? Like, my dog is, you know, sleeping at my feet right now. I would love to think it's because she loves me, but it's also probably because she wants treats.
Speaker 2:Yeah. Food motivated.
Speaker 1:Yeah. Parents know this. There's nothing there's nothing better than when your child is just, like, wants to eat a lot of food. And if they're not incredibly hungry, you're, like, trying to Yeah. I mean, it's literally one
Speaker 12:of the two major levers we have to negotiate with them. It's Yeah. Reward via food
Speaker 1:Yeah.
Speaker 12:And then negative reinforcement, which, you know, you don't wanna do a ton of.
Speaker 1:Yeah.
Speaker 2:Yeah.
Speaker 12:So we're we don't wanna take that lever away from people.
Speaker 2:Yeah. How are you thinking about branding? Like, GLP ones are interesting because I feel like they're not just consumer marketed as people know the name Wegoovy or Wegovy or Ozempic. They also know peptide. And peptide has become a new category that people, I think, largely feel more comfortable about than magical weight loss pill or like injectable drug.
Speaker 2:It's like, what were you injecting? There were a lot of injectables that people were not cool with and now everyone's like, well, it's a peptide, then okay. Do you think It's about natural. Yeah. How do you think about creating like educating folks about your category and how you fit into the overall hierarchy of things that you put in your body potentially?
Speaker 12:Yeah. So, you know, this this drug that we're hopefully bringing to market first, Loy2, is for a senior dog lifespan extension. It works by metabolic fitness improvement, is one of the predominant mechanisms of GLP-one. Mhmm. But actually our first drug, and hopefully a drug we'll bring to market after this, it's a bit slower in the manufacturing side, is for big dog short lifespan.
Speaker 2:Yeah.
Speaker 12:And this idea that, you know, large and giant breed dogs live, you know, half as long as small breed dogs, And introducing there was, like, such a nice, like, Trojan horse or Trojan dog or whatever to introduce the ethos, both at a general thank you. Thank you. I'm here all day. Yes. Introduce people to the thesis of the aging field and also introduce regulators.
Speaker 12:Yeah. Right? Because we're like, oh, like, here's this thing that you take as inherent, as natural. You know, Roddy's dying at age 10. Yeah.
Speaker 12:It's actually not natural. Here's, like, the mechanism, and here's the drug, and here's how it's gonna work. And, by the way, the way it works is by just slowing the rate of just slowing the rate of aging of these big dogs.
Speaker 2:Yeah.
Speaker 12:And so I think it's the same thing. Right? You you give something where somebody only has to make one leap or two leaps. Yeah. Right?
Speaker 12:It needs to be accessible but still technically rigorous, which is always a challenge with bio, And then you can push it further and further and further from there. Like peptides. Right? Like, don't think peptide is going to become a thing if it wasn't a weight loss drug.
Speaker 2:Yeah. So what's
Speaker 12:the That's a great intro.
Speaker 2:What's the current phrasing? Because you have, like, drugs, then peptides, then Ozempic, and you have drugs Yeah. And then blank and then loyal.
Speaker 12:Oh, small molecule mostly.
Speaker 4:Small molecule. Okay.
Speaker 2:People people are loosely familiar with that, but maybe it needs a buzzword. I don't see small molecule parties happening even though people are obviously doing that.
Speaker 1:Is there any
Speaker 2:different thing.
Speaker 12:I don't recommend small molecule. I mean, that's just like drug parties. That's like college.
Speaker 2:That's what I mean. That's what I mean. Is
Speaker 1:there is there anything to learn from fringe Internet communities in relation to dog health? Like in the
Speaker 2:The Brian Johnson of dogs. Is that
Speaker 1:there somewhere? That kind of thing, you know, some owners going crazy, but I think about like there's so much that like bodybuilders were doing ten years ago that's now becoming mainstream.
Speaker 2:Future here is just not evenly distributed. Yeah.
Speaker 12:I think it's all the raw food stuff.
Speaker 3:Oh, really?
Speaker 12:And all the cooking at home food stuff. Yeah. The nutritionally complete I mean, there's a lot of there's a lot of scandal here, and we like we've like pretty purposely stayed away from the dog food wars as I like to call them. But that is definitely where people started. They people don't really do drug hacking as much.
Speaker 12:Well, because also a lot of the drug hacking for, like, weight lifters. I mean, yeah, it's, like, for fitness, but it's really for, like, aesthetics. You're not gonna, like, hack your dog for aesthetics. That's kind of unethical.
Speaker 1:There's gotta be looks maxing.
Speaker 2:Looks maxing. I mean, that's all dogs.
Speaker 12:Fuck times. Shoot smaxing.
Speaker 2:Cute's maxing. That's the story of dog breeding.
Speaker 12:That. Yeah. I mean, not gonna lie. Like, there's some genetics, in, like, golden retrievers that we, like, inadvertently gave them to be, like, extra cute and extra lovey. You could totally give that to any dog.
Speaker 10:Let's go.
Speaker 8:We should.
Speaker 12:We should. Will. Tempting. We are not doing dog gene editing, but, like, someone totally will, and they totally will do that. And Well it'll
Speaker 8:be interesting.
Speaker 2:Well, you'll be the first person we call when it happens. Thank you so
Speaker 1:much, Cameron.
Speaker 2:On the show. Congratulations. You feel
Speaker 1:like, yeah. The the energy is real. It's coming through this, the screen. You're swearing like a sailor.
Speaker 12:That's always Damn. I I'm so sorry.
Speaker 1:My No. I mean
Speaker 12:The my
Speaker 2:The energy is palpable.
Speaker 1:The team's fired up. Team's fired up.
Speaker 12:A lot of drama for it, but, you know, you can.
Speaker 1:You gotta be yourself.
Speaker 12:Be yourself.
Speaker 2:We'll talk to you soon.
Speaker 1:Have a good rest of your day. Congrats on the progress.
Speaker 2:Goodbye. Let me tell you about Sentry. Sentry shows developers what's broken and helps them fix it fast. That's why a 150,000 organizations use it to keep their apps working. Let's have Ankur from
Speaker 1:Up next.
Speaker 2:Brain Trust. He's in the restreaming.
Speaker 1:Let's bring
Speaker 2:him in. Chatting with him earlier. How are you doing?
Speaker 1:What's happening?
Speaker 2:What's up, guys? Not too much. First time on the show, quick introduction. I wanna hear the news, and then I wanna talk about the economics of AI labs. But, I wanna talk about your news first, so please introduce yourself.
Speaker 5:Awesome. Yeah. Thanks so much for having me. Ankur, founder and CEO of Brain Trust. We build observability for AI products.
Speaker 5:So companies like, you know, our or over or overlord here, Ramp, Notion, Instacart, Dropbox, etcetera, that are building really great AI products. They all use BrainTrust to help with that.
Speaker 2:Okay.
Speaker 5:We're announcing our series b today. We just raised $80,000,000 and,
Speaker 1:you know, helps us build Sorry
Speaker 2:to interrupt. Congratulations. We're very excited.
Speaker 1:You said that
Speaker 2:helps interruption.
Speaker 1:That that you said that helps you build
Speaker 5:Yeah. It helps us ship more stuff and hire more people.
Speaker 2:Yeah. Very simple. So, yeah, walk me through why, someone's someone's picking you, how they're integrating you, what the business model looks like, and what, like, the best case scenario of AI observability looks like.
Speaker 5:Yeah. I think what's interesting about AI is when you build a product, you actually have no idea what's gonna happen when you ship it. So if you're, you know, you're building a traditional UI, you can pretend to be Steve Jobs. Look at the UI, play with it, form an opinion, and then you can kind of guess what's gonna happen when people actually use it. With AI, you have literally no idea what's gonna happen.
Speaker 5:Mhmm. And so being able to look at how people actually use your product and then capture the cases where it works well and the cases where it doesn't and test them is critically important. And that's basically the data flywheel that we power for all these companies.
Speaker 1:And then you have yeah. Digging in a little bit deeper, you have, like, same application, different models integrating as well that I imagine you're also comparing. So, like, what is what is best in class look like if you're a software company that's integrating LLMs? Like, what is best in class testing look like? Who who who's, like, doing this at the highest level, that you can Yeah.
Speaker 5:I mean, I honestly, I think Ramd is a great example of a company that does this very well. Use a bunch of different models for different use cases. And I think there's two things you shouldn't do. One is just use the same model and be very afraid to change it. There's some companies we meet that are still using GPT 3.5
Speaker 1:on
Speaker 5:Azure.
Speaker 1:Oh, no way. I was debating.
Speaker 2:Are they making any money from 3.5?
Speaker 4:And I
Speaker 2:was like, it might be actually zero.
Speaker 1:You kinda set set one of these things on a on on some feature Okay.
Speaker 2:Or or something. Schedule in that case because those GPUs are gonna be burning into the 20 forties running 3.5. I love it. Okay.
Speaker 1:I'm sorry.
Speaker 5:And and there's there's some companies that are just changing the model every day, and I think Sure. I that's not a good way to build a good product. You need to really understand the nuances of the technology that you're using. So I think best in class is actually being able to change the model every four to six weeks. And if a new model comes out like Sonnet 4.6 came out today, the best companies are gonna have that integrated into their product in the next twenty four hours if it makes an improvement for what they're doing.
Speaker 2:Okay. Any more questions? I wanna talk about AI lab economics. Let's
Speaker 1:do it.
Speaker 2:Are we in the the Cournot equilibrium? Do you agree with that characterization? How long does that last? Walk me through how you think the AI lab economics might change over the next few years.
Speaker 5:I think it's it's really simple. So, basically, when new models are coming out, people forget about open source and they forget about economics. And that's because it changes fundamentally what you can do with a model in the first place. Like, the you know, programming is a good example. The workflow today is completely different than it was a year ago.
Speaker 5:And if you tried to use the models from a year ago today, you wouldn't be able to do crazy stuff Yeah. Like, you know, Claude Bot or whatever that people are building Yeah. Nowadays. And when models don't change at that speed, then what happens is people optimize the performance on the use cases that they have. Mhmm.
Speaker 5:And so in between major model releases and I think we're in one of these periods right now. There are new models coming out, but they're not fundamentally changing what's possible or not possible. You see a lot of interest in open source models, and, I think that's very exciting right now. Like, although there are not that many companies using open source models, if you look at usage, on our platform, almost half the usage, like token usage, is coming from open source models Mhmm. From a very small number of companies that have figured out how to optimize use cases really well.
Speaker 5:And so I think it's gonna be really interesting.
Speaker 2:Okay. So, I feel like we've been playing this cat and mouse game with the value accrues to the foundation model layer, value accrues to the to the application layer.
Speaker 1:Value is very clearly
Speaker 2:Ship brain trust. Yeah. But but I agree. How does that how does that flip, and and what do the big AI labs look like in the like, after the final models? Do they look like hyperscaler clouds?
Speaker 2:Do they look like Azure, GCP, AWS? Is is that the right formulation, or are they more like infrastructure providers? How do you think about that?
Speaker 5:Well, first of it's not clear to me when, if, whatever the party's ever gonna end. But let's say let's say the party sort of slows down at some point. I think one thing that happens is there are some use cases that actually aren't changing that much. So customer service for a consumer software app at the very, very highest scale. If you think about, like, deflecting incoming tickets that come in Yep.
Speaker 5:For example, can I get a refund? Yep. That use case doesn't really change at the speed that new LLMs are coming out. Sure. And so we actually have a lot of customers that have built solutions, in in many cases using open source models like one or two years ago that they're still using and optimizing, and they're getting both better performance and better economics each coming month by taking advantage of the downstream optimizations that are happening from from the frontier.
Speaker 5:So I think a lot of use cases are just gonna get cheaper and higher margin, especially the use cases that aren't changing that much. Yeah. In terms of what we see with the models, I think probably the most interesting trend is that they're verticalizing and building products. Like, again, I think Clodbod is a really interesting example of this. So is Clod for Sheets and and, obviously, Clod Code.
Speaker 5:Yeah. So, I mean, I think if the party stops, there's a whole another layer of low hanging fruit tightly integrating models into these canonical applications. And I think there's still a lot of room to make that really good.
Speaker 2:Do you think that that will do you how long do you think we'll stay in this regime of building Centaur like projects instead of you know? Yeah. It's like, you know, Big AI Lab launches a product for legal. They haven't launched a law firm yet. Is that common?
Speaker 5:Yeah. I mean, I have been working in AI now for, like, ten years. And prior to that, I'm a, you know, crusty suits. Yeah. Crusty, jaded, pessimistic, engineer type person.
Speaker 2:Okay.
Speaker 5:And so when I first started working in AI, I thought, wow. Things are changing really quickly. Mhmm. It's not gonna be like this forever, and next year, it's gonna be totally different. But this is, like, 2017, 2018.
Speaker 5:Right? And and so I I've had to totally unwind that part of my brain and just assume that I I I think there's a reasonable chance we will be in this state, and and then the normal is gonna change, for for a very long period of time.
Speaker 2:Just progress will continue for a very long time, and we'll see more
Speaker 5:and more progress. And I I I mean, I think that's just generally true, but, you know, the baseline for progress is gonna feel different a few years from now once we get used to this than it it did, like, ten or twenty years ago.
Speaker 2:Yeah. How how have you reacted to that line from Dorkash that, like, diffusion is cope? And then the models aren't actually that good, and so if they were better, they would they would diffuse much more fast, much more
Speaker 5:Totally. I mean, I was actually talking to Martine last night about this, but I think we are now programming at the maximum speed that we can program.
Speaker 2:Okay.
Speaker 5:In fact, there are so many people who make so many mistakes and walk them back or we we ship crappy products and then walk them back, or we ship buggy products and then fix them, or the speed at which we're able to respond to user feature requests and bugs is we're totally tapped out. Right? And so I I I I think that we're in this really weird equilibrium state with how productive we can be in some of these use cases. And it's not super clear, at least to me, that a model that's 5% smarter at writing c plus plus code is gonna dramatically change the amount of productivity we're able to create.
Speaker 2:Bull case for FDEs, basically. Is that right?
Speaker 1:Yeah. Yeah. It's interesting. It's like you can do so much more, but there's still value and focus. Right?
Speaker 1:Yeah. It's like, you know, a company that raises like, Brain Trust raises a big round. You've got a lot of resources available. That doesn't mean, okay. We should launch 10 products at once.
Speaker 1:It's like, okay. You still have to,
Speaker 2:like Yeah.
Speaker 1:You know, focus that energy in.
Speaker 5:And and, you know, weirdly enough, we actually raised a smaller round than we could have. I think we we are trying to be very careful about not
Speaker 1:getting Just kidding. Yeah.
Speaker 4:I know. I'm sorry.
Speaker 1:Yeah. Right? Trying to
Speaker 5:be careful about not getting caught up in in the craziness. Like, we know exactly how much money we need to hit our revenue target for the next two years, and we raised that much money.
Speaker 2:No. Very, very smart. We're messing
Speaker 1:with Now you're giving us time to get a bigger gong.
Speaker 2:Yeah. Yeah. Get it. You're like
Speaker 1:This one's not big enough. Well
Speaker 5:Oh, we'll be we'll be ready. Keep
Speaker 2:it warm. Well, thank you so much for coming on.
Speaker 1:Yeah. Great. Great to finally have you on and and come back on anytime you have thoughts.
Speaker 2:Yeah. We'd love to talk to
Speaker 5:Thanks for having me.
Speaker 2:Yeah.
Speaker 1:Have a great rest of your day. Cheers.
Speaker 2:We'll talk to you soon. Let me tell you about Eleven Labs. Build intelligent real time conversational agents and reimagine human technology interaction with Eleven Labs. And we have our next guest almost here in the Restream waiting room. We have Reed from Knight.
Speaker 2:He's the founding CEO. He's been on the show before, but he has some big news for us. So Reid, how you doing?
Speaker 1:He's back.
Speaker 10:I'm just trying to get on this show as
Speaker 1:much as Delian at this point. Gotta get your numbers up.
Speaker 2:Number two. Well, you're welcome anytime. We can always talk, creator economy, what's
Speaker 1:going on. This is cool. I feel like you're this is like your your streaming setup.
Speaker 2:This is
Speaker 1:It was fun having you here.
Speaker 2:That's the big play button. Is that 10 mil?
Speaker 10:It's a 100.
Speaker 2:A 100? Wow. There we go. Let's hit the golf course.
Speaker 10:Subs. You'll get there.
Speaker 1:Either way. Either way.
Speaker 2:Anyway, give us the real news.
Speaker 1:What happened today?
Speaker 10:Yeah. We finally announced our capital raise. Stepstone led it. Founders Fund also involved. K five, House Capital.
Speaker 10:Kinda kinda felt like it was time to to get that out there. And so, yeah, we officially announced that Bloomberg today and I'm kinda just bouncing around. Amazing.
Speaker 2:How much did you raise?
Speaker 10:70.
Speaker 1:Oh, he's going back. He's going back. Yeah. Alright. What, yeah.
Speaker 1:Let's you've been on the show before. We'll assume people generally understand Knight. Like, what does this capital allow you to do because you guys are in a business that, unlike some of our other guests makes, you know, has been making real real money for for some amount of time. And so why raise why raise?
Speaker 10:Yeah. We're probably a little bit different. Like, we're we've been profitable for ten straight years. So it's a it's a different church We're great success.
Speaker 2:For that sake.
Speaker 10:And so, you know, I I think for us, you know, kinda said this last time I
Speaker 1:was You're on of profitability. You're like, I've done that. I've done that for ten years. I gotta switch it up. I've listened to the show too much and, like, all these companies do so damn lose so
Speaker 10:much damn money. It kinda felt like the time for us to not be profitable anymore.
Speaker 2:Let's go. Let's go. But seriously, yeah. What what, what, like, can you acquire assets? Can you hire a bunch of people?
Speaker 2:Are you gonna build technology? Like like, what what's on the menu? There's so much that you could do.
Speaker 10:Yeah. The the focus has always been talent, talent management. I think we launched the venture studio five years ago. We did Feastables and Tone, Outtake, a lot of stuff has come out of that. The venture studio is going to be a big focus of ours.
Speaker 10:And then we're also like, we think music is interesting. We think sports is interesting. We wanna push deeper into live events. I think it just kinda opens the aperture a little bit wider for us. The the core idea is just continue to be the Internet's media company.
Speaker 1:Mhmm.
Speaker 10:Like, bias assets that are transcended by the Internet over the next decade. Hopefully, I'm doing this for a long time. Hopefully, we're profitable for a long time. Yeah. And so, yeah, it's it's, like, an exciting next step.
Speaker 10:And, you know, I'm glad Stepstone and and honestly, like, Founders Fund and some of these other ones are involved. Like, I I don't think FF has ever done another media deal. I think this is kinda like the first one for them. And, yes, we have a venture studio.
Speaker 2:Yes, media company called Facebook back in the day.
Speaker 10:That was one. Yeah.
Speaker 2:That was one.
Speaker 1:We don't hear about Facebook much anymore.
Speaker 2:Well, do metaverse now. Yeah. They're they're kinda out of the media game. No. But truly, like, yeah, what you do is is very, very unique for for venture broadly, but also for Founders Fund.
Speaker 2:Give us a give us a song review of RIP, my granny, she got hit with a bazooka.
Speaker 10:Wait. What happened?
Speaker 1:What did I miss?
Speaker 2:Have you not heard that song bazooka?
Speaker 1:No. What?
Speaker 10:Like, did this just happen today?
Speaker 2:Like Oh, it's just this viral song.
Speaker 1:So we'll send you we'll send
Speaker 2:you some
Speaker 1:we'll send you some video.
Speaker 2:This is stupid meme song.
Speaker 1:But
Speaker 2:but but unpack unpack, bullishness around music. Obviously, a lot of people are doom and gloom. AI is gonna do it all. Where are you seeing opportunities? What are the smart musicians doing today?
Speaker 10:I'm still waiting for AI to create content, to be honest. Like, I like, had didn't figure it out. Like, I yes. Like, mid journey and v o three, there's some cool shit. Yeah.
Speaker 10:And some fake animations. Mhmm. Okay. It's okay. Like, I I'm so not bullish on the future of AI transcending content, at least not in the next two to three years.
Speaker 2:Yeah.
Speaker 10:So I I am not as much doom and gloom as people are in the music industry, in the content industry. Like, I I get it. Like, I get why people are scared. It just feels like adoption takes so long and the products aren't even close.
Speaker 1:Yeah.
Speaker 10:So that that's, like, my take, and I I know you guys
Speaker 2:have Yeah. It feels just so much like a tool. Like, okay. You don't have the money for the drone. You take a photo with your iPhone and then go to Google Maps, and you say interpolate these two with v o three, and it does the cool drone shot for you, and your viewers don't really notice.
Speaker 2:And all of a sudden, you have higher production value with lower overhead. But one shotting a truly viral video, it just requires so much you know, you have to be one with the algorithm.
Speaker 1:Are you are you getting are you getting pitches from people that are saying, like, I'm gonna be a creator, but I'm gonna be faceless, this sort of, like, Lil Kayla thing. Obviously, they were earliest to this trend and and kind of ran
Speaker 10:the Two sides of this conversation. There's one like being a faceless creator
Speaker 2:Yeah.
Speaker 10:Which Iron Mouse, I think, is one of the biggest ones in America. She's considered a VTuber. And so I I get why that's popular. It's a it's a faceless animated character with a real person doing the voice over. I get that.
Speaker 10:It's popular in Japan. It's becoming popular in America. In terms of AI, more generative AI channels or a 100% generative AI channels, I I don't think we're even close. I I see the news channels on YouTube. I I see a lot of this stuff.
Speaker 10:Nobody's watching it. I think you guys gain have gained momentum for a reason.
Speaker 1:I just don't think that some AI news channel is going to do anything in the next, like, I don't know, five years, to be honest.
Speaker 2:I mean, maybe competitor to if your news if the news channel you're competing with is just straight up reading you headlines, but if there's commentary and back and forth and stuff, that that that's much harder to capture.
Speaker 1:How are you thinking about, like, timelines around deploying capital?
Speaker 2:Mhmm.
Speaker 1:This is not you know, because you guys have just been operating real business for so long, I would assume you're not like, we wanna burn through we're gonna burn through this over the next eighteen months and then try to raise another round. It's more like strategic capital that can allow you to kind of strike when you have an amazing opportunity or own more of a business that's kind of, you know, being created with some of your existing talent. How do you think about it?
Speaker 10:Yeah. I I think that was well said. I, you know, I take a pretty long term outlook on this company. I I hope to do this for a long period of time, and so I'm not in a hurry. Like, I like to have long term out outcomes, and I I think long term when it comes to acquisitions as well.
Speaker 10:So I I think about what's gonna be popular five to ten years from now because, hopefully, I'll be running this company five to ten years from now. So it's not necessarily let's go do something tomorrow. We're gonna look at a lot of different things and, you know, we're having a lot of conversations, but I'm not in a hurry to just
Speaker 1:go spend rapidly and lose a ton of money. What when's the right moment to meet a creator? Like, do they need to have, proven that they have some element of star power, like, some some, like, base fan base? Like, when do you know when do you look at somebody's, like, content? It could be a standalone Instagram account or a YouTube channel or a TikTok or a Twitch account and say, I can I can 100 x this individual?
Speaker 10:Man, it's changed a lot over the years. I've you know, five years ago, we were very, very, very selective and we were mostly just working with the top people in the world. But then people have come around that have changed how I think about content, and also the careers get big so quick. I mean, think like let's just take the Rizzler. I think
Speaker 8:I have the
Speaker 10:iced tea back there. Let's just take the Rizzler as example. Like, we found him very early, and I think five years ago, Knight would have not signed the Rizzler. And we took we took a little bit of a risk and it paid off and now he's this just like global superstar of a nine year old. And so we we take a lot more risks.
Speaker 1:He's nine? He's nine. That's crazy. I always assumed that he was at least
Speaker 2:Me too.
Speaker 1:At least a teenager.
Speaker 2:Well in my mind here.
Speaker 10:I know. And so we'll we'll take risks a lot earlier if we have high conviction in somebody. We'll take risks earlier on Twitch, YouTube, TikTok. And I I know also it's more competitive. When I first started the company ten years ago, there wasn't a lot of representation companies that gave a shit.
Speaker 10:Can I swear on this?
Speaker 2:We don't, but you can.
Speaker 1:That okay.
Speaker 10:I can't swear. That that cared about digital. Now, it's the big agencies, the big management companies, the traditional management companies, they all look at people pretty early. And so discoverability of new talent only happens on the Internet. In comedy, podcasting.
Speaker 10:And and so it's just more competitive now, and so we've taken earlier swings on people.
Speaker 2:What can you tell me or explain what's going on on Kik, Luxmaxing, clavicular is in the New York Times now? Like, it feels like there's some machinery there behind the scenes. There's clipping. We do a little bit of this.
Speaker 1:But funded in this case by Kik, my understanding. Like, they're putting up budget and saying Yeah.
Speaker 2:We're gonna
Speaker 1:pay pay out views. Like, it it
Speaker 2:Maybe just give me, like, a IRL streamer one zero one. Like, what's going on here?
Speaker 10:The it's it's not new. I think you guys are just now hearing about it, and people are hearing about it for the first time on Twitter. But this was very much like how Aiden Ross became popular is he was paying a lot of of clippers to clip his content out. Mhmm. And you can livestream on Kik or Twitch and you can get 5,000 CCBs, but those 5,000 people are the only people that see it.
Speaker 10:Yeah. So a lot of the discoverability and the amplification of those views comes from clipping on the Internet. Creators figured that out two to three years ago. It's just now becoming a lot more mainstream and people are realizing that that's the growth metric. And so clavicular, neon, there's so many now that are spending $10.20, up to upwards of a $100,000 a month Wow.
Speaker 10:Right now just clipping content.
Speaker 2:Interesting. And so, yeah, that's why it's breaking through broadly.
Speaker 10:His too, the Luxmaxing thing, like, it it's that kind of like a wave. Totally. And, you know, it's like,
Speaker 4:I have
Speaker 10:a lot of people texting me about it with about my thoughts on just him more generally.
Speaker 2:Totally.
Speaker 10:But he
Speaker 1:does This is great. Now now you you all your investors, anytime there's a new Internet star, they just get to text you a clip and they're like, are we in this one? Like, am I making am I making money on this indirectly? And you're I'm sure a lot of the time you're like, yeah, we're we're we're partnered and then and then you got it. Yeah.
Speaker 10:They did ask about clavicular.
Speaker 2:So I'm sure.
Speaker 10:I have had that text. So his his clips are breaking through to a lot of people, not just kids.
Speaker 2:Yeah. Yeah. It feels like there's also a little bit of, like, creative writing going on. I mean, the whole vernacular and the way they structure it, like it's like it's TMZ based celebrity news, but it has all this lingo and it you have to peel back this onion to understand what's actually happening in the clip. That has created this sort of, like it nerd snipes a lot of people.
Speaker 2:They're like, I wanna learn what frame mugging means today. And then they go and dig in there. Oh, they're engaged.
Speaker 1:Do you think do you think we'll get, one person movie studios Mhmm. In the next few years? Is that is that something that you're kinda waiting for? You said earlier, like, AI is not really making content, but you can imagine the archetype of somebody who's like a writer who can, like, write out a, you know, a, you know, effectively an entire script Yeah. And then piece by piece prompt to get to something that is a cohesive project and seeing like C Dance from last week and seeing Saag's reaction to it, you can immediately see like it will be possible to piece together with character consistency, maybe even using traditional stars and get to the point where somebody can put out ninety minutes of content and do that every month, maybe every two months.
Speaker 1:It's not gonna be like one shotted Yeah. To make something great.
Speaker 10:Yeah. I I agree. I think the you know, I've been seeing rumblings of people now gonna go back on strike. Think I that the big to your question, yes. I do think it's gonna happen.
Speaker 10:How are the guilds gonna handle this? Because that will undoubtedly be, like, nonunion work. And so I think they're gonna have to come to terms with, are we gonna allow this to happen within the guild, or are we gonna allow these things to get billed outside of the guild? And then does nonunion work actually become more powerful and the streaming services start buying that stuff? And so I I think a lot of that's gonna have to unravel over the next, like, three to four years.
Speaker 10:And, yeah, I I do agree that we will have, like, a one person studio that uses prompts to create a script to then create content. And we just saw, like, Markiplier did this all just by himself, wrote Iron Lung, directed and and acted in the film, distributed independently to movie theaters. I think it ended up doing, like, 25,000,000 box office on a $6,000,000 budget. And so we're seeing it happen, and we're seeing the model to go direct to theatrical. Will that happen through generative AI?
Speaker 10:Like, undoubtedly, yes. I just think we're further away than people realize.
Speaker 1:Yeah. How how badly do you want to help create a new platform, the likes of a Twitch or a Snapchat or or ideally an Instagram or YouTube. Because like eventually, like the the nature of these platforms is is you wanna have the breakout stars, the superstars creating content on your platform, but you also wanna keep them down. Right? You don't wanna let them get, too powerful to have any type of leverage over the platform.
Speaker 1:You can imagine at some point, you know, some amount of creators rising up and then using clipping on all these different platforms to, try to seed kind of a a new platform with users. And and given that you're in the business of being effectively at the mercy, like, creator is at the mercy of these platforms and you can, you know, sometimes you're you're on a on a hot streak and then other times you're kind of on the receiving end of of different changes. But how do you think about new new platform opportunities?
Speaker 10:I I don't think I'll be the one or we as a company will be the one that creates the next platform. It's it's not something we're thinking about internally. I hope that a new platform pops up in the next twelve to eighteen months. It feels like we're due for something. I have no idea what that's gonna be because the meta still feels very much like short form content dominates attention.
Speaker 10:So I I don't know what else is gonna come through the system, but it it is an interesting trend we're seeing right now where every platform is adopting video podcasts. Netflix kind of to start. Just saw the Apple announcement this morning that they're gonna start doing video podcasts. Amazon's gonna follow. Everyone's gonna follow.
Speaker 10:And then there's gonna be this long form podcast feed. Maybe that scene is a new type of mechanism Apple's
Speaker 1:timing with that. I'm very I'm I'm super happy they're finally doing video. We still get way more views on on like Apple Podcasts than than YouTube and Spotify, which we laugh at because we feel like it's such a such a video heavy show. Like, it's insane to be like, I'm gonna watch TBVN. Hey.
Speaker 1:Some people are gonna
Speaker 2:for anyone who's just Total
Speaker 1:total respect. There's there's somebody listening to this. There'll be someone listening to this. Many people over the next twenty four hours from Apple Podcast. But
Speaker 10:But is that because your audience is older and the boomers listen to it on Apple Podcasts? Woah.
Speaker 2:Woah. Woah. Woah. They're let's not call them names here. They're lovely members of our community up stand
Speaker 1:I think I think it's just habit forming. I I I listened to probably thousand thousands of hours Yeah. Podcast back Yeah. Yeah. On Apple Podcast back in in college.
Speaker 2:Yeah. For sure. Help me get up to speed on video games. There's this weird boom and bust that I sort of perceived that I want a reality check. So we we had boom in in Twitch streaming for for video games.
Speaker 2:People were watching a of video game content. That seems to be continuing to go. But the the esports IRL competitions felt like they reached a zenith and sort of have been either status quo or declining. At the same time, you have something like Kaisenot's Bloodborne stream that looked like it had the budget of an ESL event. Like so it feels like there's more there's there's exciting things happening in in video game streaming and content related to video games, but I can't quite put my finger on it.
Speaker 2:Like, where what it where is where where is video game content today, and where is it going?
Speaker 10:It's still struggling. And I think we've had a lot of games come out and have moments, like a month at max, like a moment, and then just kind of fade into the darkness. We haven't had a game that has come out that has been a Minecraft Fortnite Grand Theft Auto that's sustained.
Speaker 2:Okay.
Speaker 10:Hopefully, we get Grand Theft Auto the end of this year. I'm probably not as confident that they finally put that out. But even in the esports genre, we had everything. We had Rocket League. We had like, we had every single esport Yeah.
Speaker 10:Out there. And it feels like we've fully retreated just back to League of Legends and Counter Strike. Interesting. And I I don't know if that changes. Like, it feels like the the esports thing had its moment.
Speaker 10:Most of the teams are no longer here. Yeah. And the two esports that were dominating, that were the the biggest in the pack while this trend was happening, Counter Strike and League, are still very much the two most popular. We just we need to get back to making games. Like, it but it's hard.
Speaker 10:Like, Roblox. Kids are putting out Roblox games every single day, and so you just have a new influx of games. Like, you have YouTube videos every single minute. And so it's hard, I think, for a triple a studio like an Activision or a Ubisoft to put out a game and that game to have some sustainability over the one month period that people play it. You know?
Speaker 10:So I I don't know. I've I've been pretty upset by, like, the last two and a half to three years of the video game industry. Maybe some of it was COVID induced. But we just have had big titles,
Speaker 1:unfortunately. Good news is that AI will totally help this this year. No. It's gonna make it it's gonna make it way worse because you can imagine my my theory is that the the platforms of existing networks like Roblox make Mhmm. Use integrate a bunch of AI to make it even easier to make all these games, and then you get more fragmentation, and it becomes even harder to have a truly breakout, durable hit.
Speaker 2:Yeah. It is odd that we have, like, the Call of Duty annual release cadence, which I think a lot of people have not been happy with because there's just too much incrementality, not much changing. But then you have Rockstar in the exact opposite spectrum. It's been, what, like, almost twenty years since the last Grand Theft Auto came out, and everyone's like, okay. We'd love a little bit more cadence from you, but less cadence from you, Call of Duty.
Speaker 2:Slow down Call of Duty. Speed up Grand Theft Auto. But, yeah, greatness takes time, so I don't know. Maybe it'll happen.
Speaker 10:I I Call of Duty will retreat and not do every year rollouts.
Speaker 4:Yeah.
Speaker 10:I I do that is what what ends up happening. And then the resurgence of sports games has has been good for the the the at least the video game ecosystem. The content creation of those sports games has not increased as those games have come out. But call NCAA football was one of the biggest releases we've had in a long time, and it took a long hiatus. And so we we are seeing a resurgence in sports games.
Speaker 10:I just think from a casual fan, they're playing the games. They're not just watching streamers play the games.
Speaker 2:Yeah. What how are the economics or key strategies of a video game launch different today than maybe a a decade ago? I I I I watched some video game reviews, and I'll see, you know, oh, thanks to Activision for sending me the free review copy. Or, hey. This was actually promoted by this is a promoted video by Ubisoft for the latest Assassin's Creed.
Speaker 2:I probably wouldn't have made a video review of it, but I am because they're paying me all the way to, you could imagine, a Kaisenade stream where they pay for the production value. And, you know, when GTA six comes out, they're putting, you know, props behind him, all sorts of crazy integrations. What does the rollout of of a successful video game look like and partnering with, like, your team?
Speaker 10:Yeah. Used to be a lot of linear TV ads. That's transition obviously to like, let's pay creators. Let's do interesting things with creators. Mhmm.
Speaker 10:But I I don't think people remember when Fortnite first came out, it was called Save the World. Yeah. And they beat a lot of creators. Like, their strategy when they came out with the game was to pay every single creator. And then when Battle Royale came out, they paid every single creator again to play Battle Royale.
Speaker 10:So it's been going on for a
Speaker 1:long time. This isn't a new thing.
Speaker 10:Yeah. Individuals discover video games on YouTube or Twitch from their favorite people making those games. And so the advertising has had to change with that.
Speaker 3:Yeah. But I
Speaker 10:still feel like Activision, Ubisoft, they still have traditional spend. I still see the commercials. Yeah. They're just like the budget allocation is very different. It's like, let's we spend on creators and Google and and meta ads and some of the linear stuff.
Speaker 10:Maybe we'll play that at NBA All Star game during the commercial break, whatever that is. But, yeah, it's it's changed rapidly and will continue to change.
Speaker 2:How much of it is, like, top down versus bottom up? Like, you could pay a ton of small creators to to play a game, or you could say, like, we're having Shroud and Ninja on day one. And just the fact that you could queue with them or you could watch their streams, maybe they get paired. Like, you create this, like, snowball effect. You just jump straight to the top of, the Twitch viewership numbers.
Speaker 10:Man, it's so dependent on the game. I think if you're raiders, you probably get more out of paying Shroud and Burnt Peanut, whoever that is, play your game than you will after go or than you will from just doing a wide micro influencer strategy Mhmm. Which is gonna be 10 times more work to get all that paperwork done, and then you're gonna have to manage hundreds of creators Sure. Or just that shroud who's known so deeply in the community to be one of the best FPS
Speaker 1:Yeah.
Speaker 10:Gamers of all time. I think it's a it's such a balance depending on the game, to be honest, and each studio is trying to figure that out right now. And it but I I've seen the the disco more micro in the past, like, now over the last few years. Let's widen out the budget. Let's not necessarily just give it all to mister beast Okay.
Speaker 10:Or some other macro creator.
Speaker 2:Last question for me. We'll let you get back to your busy day. Give us a Burnt Peanut one zero one. The chat's going crazy for Burnt Peanut. Like, what is that?
Speaker 2:How does it work? What are the keys to success? Why are we talking about Burnt Peanut, not someone else?
Speaker 10:Yeah. It's been it's been crazy watching him kinda just come on. And I'm quite confident he doesn't pay clippers. I think a lot of this is just organic. Like, all the clips that you see on TikTok
Speaker 2:Yeah.
Speaker 10:Are just fans making clips because he is hilarious.
Speaker 2:Yeah.
Speaker 10:But it is essentially a v tuber Mhmm. Real person behind a peanut. And I've I my theory is that peanut is a Snapchat filter of some sorts or some Mhmm. Own filter Yeah. And they overlay it over him.
Speaker 2:Okay.
Speaker 10:And, yeah, it's it's worked. And now I'm seeing like burnt broccoli and like all kinds of different melons and fruit characters on
Speaker 1:Twitch right now. It's a whole
Speaker 10:So he's Synap universe. Gonna found something. Yeah. Yeah. The synap universe of like fruit and like vegetables streaming on YouTube is is a real thing.
Speaker 2:Yeah. One of my friends started sending me burnt peanut videos and was just like, these are hilarious. And I was like, oh, I I think I understand what's going on here, but thanks for breaking it down.
Speaker 10:Are we are we like, I'm seeing this on Twitter. So we're charging a million bucks per email right now? Are are we ripping over here?
Speaker 1:That was that was not Not a I don't know where they got that information. Yeah. But the the they certainly ran with it. Yeah. But we're having a good time.
Speaker 2:Yeah. We're running ads.
Speaker 10:You guys have been killing it. It's been fun. I have it on the TV every day, so it's fun to watch.
Speaker 1:Appreciate that. Come back on soon. Bring bring your next when next time you sign a client that you think is interesting or relevant to our world, come bring him by the Ultradome and we'll all hang out in person. We always love these conversations.
Speaker 2:We'll talk to you soon, Reid.
Speaker 1:Please. Have a good Congrats.
Speaker 2:Let me tell you about Gusto, the unified platform for payroll benefits and HR, built to evolve with modern small and medium sized businesses.
Speaker 1:Very funny. What? Because every every time a creator is doing anything, people are talking like, oh, are they are they PT backed? Is p is is PT involved? Like, is PT back in clavicular?
Speaker 8:Mhmm.
Speaker 1:And now the schizos with the red The schizo's gonna
Speaker 2:go crazy.
Speaker 1:So PT backed Knight. Yeah. And then Knight backed And so Bernie yeah. The Rizzler. Red bull market in red string.
Speaker 1:Rid the Rizzler's PT.
Speaker 2:You gotta go long red string right
Speaker 1:now. There's lot
Speaker 2:of stuff. Anyway, we have the video from
Speaker 1:Yeah. We're gonna pull up
Speaker 2:Ian Curler's double touch cheating allegations. Apparently, it's dead to rights. We'll see. I haven't seen the video, but we're gonna pull it up and we will decide whether or not they
Speaker 1:broke for you to see this. So here they're getting called out and he's freaking out like, give me a break. Give me a break.
Speaker 2:Yeah. And that's the Canadian who was accused Alright.
Speaker 1:Let's get some sound on. He was accused of Curling Canada?
Speaker 2:So the Canadian was accused of cheating by the Swedes. And here's the clip of them at the Olympics. I don't know if we can play the audio because of the, the Olympics is very, very tight about, not repurposing.
Speaker 1:Can we find the actual video, though?
Speaker 2:Wait. They said that there's a clear double touch at, fifty eight seconds. Yeah. See see, the the the copyright strike could could end us.
Speaker 1:Throws the stone.
Speaker 2:Let's be careful. Let's keep talking over it the whole time so we don't get destroyed.
Speaker 1:Once it
Speaker 2:crosses the line This is
Speaker 1:touches it, even for a late release, that's considered a double touch violation.
Speaker 2:Double touch violation.
Speaker 1:The result of that, the stone gets removed from the game.
Speaker 2:Okay.
Speaker 1:On Saturday, Canada's Rachel Bowman had a rock removed after I don't see anything there.
Speaker 2:That looks fine.
Speaker 1:Look at this. Look at this. There it is. Oh, He pushed it. He he Why would you touch it
Speaker 2:like that? That doesn't that
Speaker 1:doesn't do anything. What do you mean? Obviously, he something. He's he's he's watching Okay. Watching the thing.
Speaker 1:I don't know what it's called. The rock. And he's kind of, like, directing it a little bit. That's all you need. A little microbe You've
Speaker 2:had your whole hand on it. Like, let the hand do enough. Like, look. You're releasing it. You don't need one extra touch.
Speaker 2:That doesn't do anything.
Speaker 1:Yeah. You're I I agree they should not cheat in the game.
Speaker 2:But I I just I don't even think the the cheating has that much of an impact on the actual result. I I I think that one extra touch, it's an accident. It might not be an accident, but it just doesn't seem like it really changed the trajectory of
Speaker 1:That's blatant.
Speaker 2:But isn't he already touching it? So he took his hand off and then
Speaker 1:off and he put it back on. He's Why would even do that?
Speaker 3:He's so dialed on the release.
Speaker 1:He can tell if he messed up.
Speaker 2:He can tell if he messed up and make a slight release.
Speaker 3:Released it, I think. And then He's like, oh, chop.
Speaker 2:Okay. Okay. Interesting. This is the equivalent of taking steroids.
Speaker 1:Cooper says it's the equivalent of taking steroids and curling.
Speaker 2:I really hope we can get that curling, that curling guy on the show. I I know we we talked about him earlier. One of
Speaker 1:the Yeah. So guys. Yeah. His name is Rich Rahonan. Rahonan.
Speaker 1:Yeah. Yeah. Year old personal injury attorney.
Speaker 6:We'd love to
Speaker 2:have him.
Speaker 1:We talked about him on the show last week. He followed me on Instagram. I messaged him. He says after the Olympics are wrapped up Yeah. I'll consider it.
Speaker 2:Yeah. We will see. Well, anything else to talk about? We did not get to the Neo Lab. Tomorrow.
Speaker 2:Tomorrow.
Speaker 1:We're gonna be doing a breakdown.
Speaker 2:Deep dive on Neo Labs. I posted some fake news on X. I said, I'm gonna do it with Tyler, and we didn't get to it. We had plenty of time. I just like we need to put it in the timeline.
Speaker 2:That's what we gotta do so that I know when we're hitting it. Anyway, thank you for watching. Is it time to plant the bomb?
Speaker 1:Plant the bazooka.
Speaker 2:Tell folks the bazooka has been planted. The bazooka has been planted. Leave us five stars on Apple Podcasts. If you're listening, it's fine that there's no video. We don't mind.
Speaker 1:But there's gonna be videos soon. I can't I'm so excited. Oh, yeah. There's video on Podcasts.
Speaker 2:We might be on Apple soon. Who knows? Leave us five stars on Spotify. Sign
Speaker 1:up for
Speaker 2:our newsletter at tbpn.com. Can't wait to tomorrow at 11AM sharp Pacific. Nice
Speaker 3:work, brothers. I'll see you on the next one.