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Technology's daily show (formerly the Technology Brothers Podcast). Streaming live on X and YouTube from 11 - 2 PM PST Monday - Friday. Available on X, Apple, Spotify, and YouTube.
You're watching Today is Wednesday, 08/06/2025. We are live from the TBPN UltraDome, the Temple Of Technology, the Fortress Of Finance, the capital of capital. Jordy, how are you doing? Have you been sleeping okay? You were up late partying, hanging hanging out with some of the greatest the greatest capital allocators of generation.
Speaker 1:We won't say who you were hanging out with, but give me give me the redacted read. How did it update your AGI timelines? How did it update your your world view hanging out with some of the some of the most powerful people in Silicon Valley last night?
Speaker 2:I I don't really know what I can say on this front. I feel like it was all
Speaker 1:Well, did it make you more optimistic? Did it make you more pessimistic? Did it make you feel like you're top? Like, is this a top? Is this a local bottom?
Speaker 1:Or do we have a long way to go? Is there more Are you more excited about technology? Are you more excited about capitalism?
Speaker 2:I left extremely bullish
Speaker 1:Okay.
Speaker 2:On enterprise SaaS.
Speaker 1:That's fantastic to hear.
Speaker 2:Even in the age of AGI.
Speaker 3:Okay.
Speaker 2:I also listened to a friend of mine say that he wanted to drink the blood of his his enemy.
Speaker 1:Wild guess who that is.
Speaker 2:I wonder who that is.
Speaker 4:Wild guess.
Speaker 2:But anyways, it was very it was very inspirational.
Speaker 1:That's
Speaker 2:great. And I think everybody should have a friend that gets so fired up about winning in their market
Speaker 1:Yep.
Speaker 2:That that they have sort of bloodlust.
Speaker 1:Yes. Well, you know who's fired up about winning in their market? Eric Glimon at Ramp. Go to ramp.com. Time is money saved both.
Speaker 1:Easy use corporate cards, bill payments, accounting, and a whole lot more all in one place. I wanted to highlight this post from Nikita Beer who said getting the algo just right and he shares a beautiful photo of the Vibe Aligner himself, the Tetragrammaton host.
Speaker 2:All these AI researchers talking about fine tuning.
Speaker 3:Yes. We care about fine tuning the the X algorithm.
Speaker 1:I think people I think people haven't noticed how good it's been because you only notice when it's bad. I feel like the X algo has been incredible lately. What have you been thinking? Have you been satisfied?
Speaker 2:Think it's good. I think it's good but we
Speaker 1:Oh, Tyler's got Tyler's got something to say.
Speaker 2:What about It takes I train
Speaker 1:Okay. Tyler and Jordy and then we'll go to Tyler.
Speaker 2:So for us
Speaker 3:Yeah.
Speaker 2:Yeah. We constantly are sending our favorite post to each other. Yep. And so we're just like manually training
Speaker 1:Crazy reward signal.
Speaker 2:To to show us more of what we like. And it's very good at that.
Speaker 1:I've noticed that like I really like retweeting stuff. If I just see if I see any post I like, I'll like it. But if I see any post that I think, oh, that's my friend and they're just trying to like mention something, even if I don't think it's the most incredible hilarious post, I'll repost it just to amplify it. Because just because I'm like, yeah. Yeah.
Speaker 1:Show some love. Yeah. So I've been more liberal with the like button, more liberal with the retweet button or the repost button. And I think that's also amplified the algo. So I feel like my algo's dialed but Tyler, what do you think?
Speaker 4:I feel like I'm getting like massive amounts of Normie slop.
Speaker 2:Dude. Are you engaging with Normie slop?
Speaker 1:You know that algorithms are reflections of yourself. Just you just told it yourself. Normie. Normie. Normie.
Speaker 1:What what is the example of a Normie post? Like Like Are we talking thread boy stuff? Are we talking like thread boy tier? Like here's how to start your first company or like here's
Speaker 2:the No.
Speaker 4:No. Like just like not anything that has to do with technology or business. I never engage. It's like about like some like dating thing or
Speaker 1:Well,
Speaker 4:I mean swear I don't engage. I always I I negatively engage. I say I'm not interested.
Speaker 1:You say not interested.
Speaker 4:I say I mute this account. Okay. And they just feed me more and more stuff.
Speaker 1:Feeds you more and more.
Speaker 4:It's just because it'll be like a 100,000 likes on some random Yeah. Tweet it's like
Speaker 2:I am getting I am getting some of that.
Speaker 1:Yeah.
Speaker 2:I I try to not give it any of my attention so I try to move past quickly. I don't want the algorithm to I don't wanna send the signal that I want more of it but it's tough.
Speaker 1:Yeah. Well, I don't know. Maybe it's a skill issue. Maybe it's just Nikita Beer working his magic in the algo. But thank you for your service Nikita.
Speaker 1:We know it's a hard fight getting the algo just right and I think I I personally think you've been doing a great job. So thank you. You know who else has been doing a great job? Restream, one livestream, 30 plus destinations, multi stream and reach your audience wherever they are. Go to Restream to get started.
Speaker 2:Show wouldn't be possible without that.
Speaker 1:It truly would not be possible without without it. We talked about Genie three yesterday. I wanted to noodle on it more. So Genie three, if you're not familiar, is a new frontier world model from Google. And we played around it with a little a little bit yesterday.
Speaker 1:We saw some demo videos. We we don't have access. Right, Tyler?
Speaker 4:No. Like no one Just has like engineers.
Speaker 1:Yeah. So this is at what like this is Bard tier software. We never got access to Bard and then Gemini was the Yes. Consumer
Speaker 2:And then
Speaker 1:there was Palm Bard. Two. Palm was their big multi billion parameter large language model that Google did not release to the public but they started writing papers about. Even the transformer paper, that was just an architecture. There was no product associated with it.
Speaker 1:It wasn't until what, February or March 2023 that Google came out with their first consumer chatbot for public consumption. Correct?
Speaker 4:Yeah. I I think it's mainly there's probably a bunch of like safety stuff they gotta figure out especially Google. They're pretty safe about that kind of stuff.
Speaker 1:That's a good that's a good point. That's what I wanna debate today. So interestingly, Google creates the transformer. They create Palm. They create Bard.
Speaker 1:They have all of these incredible AI researchers, DeepMind's fantastic research lab. They they they're scaling up large language models, transformer based large language models. They are on the correct path in the tech tree, and yet they don't release the consumer product fast enough. ChatGPT releases in I believe November, May I think it was I think it was 11/30/2022, maybe December 1, so you can think about it at the December 2022, Google takes three months to respond. They respond with a product that's pretty close.
Speaker 1:And yet, consumer adoption is power law distributed, and ChatGPT has been the runaway success in consumer. And so, the lesson there is you gotta be first. If you have the technology, you got to get it out in the public even if it's messy. And I mean, maybe this is apocryphal, maybe this is like the wrong way to frame it, but like, there is a there is a story out there that people are telling in the media in books that basically says Sam Altman got fired because he launched ChatGPT. Right?
Speaker 1:They say the board, he didn't He's go to the board ready. He didn't go to the board and say, hey, we I wanna launch Chatuchi BT. He didn't tell the board he was launching Chatuchi BT.
Speaker 2:Consumer SaaS product.
Speaker 1:Yeah. I wanna make the next consumer Internet company. I wanna make something that makes a a billion dollars a month. Wanna launch an app. I wanna launch an app.
Speaker 1:Is that okay? Is that okay? That's basically that's basically Not like they fire me. Right? So, yeah.
Speaker 1:Not not a fan of the board here. But the the the interesting point is that is that that move fast break things mentality. Like, when ChatGPT launched, people forget how bad the first version was because, I mean, was amazing. It passed the touring test, but it was built on ChatGPT, or it was built on GPT 3.5002 DaVinci. Right?
Speaker 1:And so, the the model was hallucinating constantly. It would it had no access to tools. It had this crazy knowledge cut off, so you couldn't ask it anything about the last six months or the or what's going on today. It was it was like pretty useless. It was magical and it was useful for some things.
Speaker 1:But for like 99% of prompts that we hit ChatGPT with today, they would completely flop on the v one of ChatGPT.
Speaker 2:Yeah. And I remember when it launched, there had been a bunch of companies that had been building on GPT doing like text generation for different use cases. There were a number of companies that were generating text for marketing assets or emails Yep. Things like that or essays. And those companies had absolutely ripped.
Speaker 2:They had insane revenue ramps and when ChatGPT launched, there were still some people that thought, oh, you're still gonna be able to build a business here around just like generating generating text for like niche use cases. Yep. And then like a month or two and it was very clear that like all those companies had gone ramped and then like basically, you know, right back to where they started.
Speaker 1:Totally. I mean, I I talked to a YouTuber at the time, someone with like, I think many millions of followers in the in the true crime horror genre. And his whole his whole channel was to to to to like, designed around finding an interesting case or, you know, crime and then telling the story.
Speaker 2:An interesting crime.
Speaker 1:Yeah. I mean, it's a true crime podcast. We saw Odd Lots. Like, true crime podcasts are the number one and the number two biggest podcast in the world right now above Joe Rogan, at least
Speaker 3:in the
Speaker 1:charts. And so, the like, true crime, it's all about storytelling. It's all about just writing, getting the facts together, assembling them into a script that makes sense on YouTube. This guy, he's not he's not like the the most insane writer. He's just like somebody who figured out how to write for YouTube and do the video production he has a good voice for it.
Speaker 1:He's a great voice for it, actually. And he has good lighting and he does all this all this great stuff to make the stuff work really well. He's good with thumbnails and and and titles. And so, he'd grown to the point where he could just put up a million view video like every And he was like, I'm gonna use ChaGePete to write all my scripts. And he did that for like a week and then he just completely quit doing YouTube videos entirely and switched to a switched to an interview show.
Speaker 1:This is the guy who interviewed Andrew Tate. He interviewed a bunch of people but there's one there's a couple like super viral like clips of like hustlepreneurs that he's the other guy interviewing them. He's the reason that he that like this clip exists on the internet. Yeah. He's a really nice guy.
Speaker 1:But it was just funny because he went like so hard into this and the product wasn't there yet. And now, maybe it is, but still people people still can tell the flavor of of text written from GPT 4.5 even. And but at the same time, the actual use case was information retrieval, transformation of information, translation, all the things that we use ChatGPT for for thirty minutes a day. I'm not telling it, write me a novel. I want to read a great novel.
Speaker 1:But I am saying, you know, give me pull all this data from the Internet and from all your resources and put it together in a table. Teach me this thing. It it it's super helpful for knowledge retrieval. And when you look at Fiji Simo's five things that ChatGPT is gonna focus on, like writing new books was not one of them. And I think that's by design because that's not where the models excel.
Speaker 1:We're in this age of spiky intelligence. And so you wanna do you wanna let the models cook on what they're good at. And they're good at knowledge retrieval and they're good at, hey, my knee hurts. Here's some symptoms. Let's go look up.
Speaker 1:It's another knowledge retrieval task. And they're also good at just chatting back and forth having a conversation and that's a therapy angle.
Speaker 2:Yep.
Speaker 1:But, my question is, Genie three, Google is clearly at the very front of this from a research perspective.
Speaker 2:Yep.
Speaker 1:And so, it's super high fidelity. It looks HD. It's rendering at 20 to 24 frames per second. You can prompt it. It seems super fun.
Speaker 1:There's this world memory. They've clearly gotten a number of fundamental improvements. Like, you know, you you you watch what has happened in the LLM world with adding reinforcement learning, adding memory, adding tool use, and and a web browser and a Python REPL and a bunch of other tools that have made it great. Clearly, in this Genie three model, there's a bunch of those tools. Like, you know, they figured out how to do memory.
Speaker 1:It's probably not just one simple algorithm. It's a bunch of things working together. They're they're crushing it. DeepMind is doing what they do best. They've done the research and created something awesome.
Speaker 1:The question is
Speaker 2:What are they gonna do it?
Speaker 1:They can't get in the chat GBT world again. They can't let another lab
Speaker 3:Yeah.
Speaker 1:Do the same research and then productize it first and then be playing catch up. So three months is is enough to lose the race in the chat world.
Speaker 2:Yeah. I think one one question I have
Speaker 1:You gotta get this out.
Speaker 2:Is this the kind of tool that's that's sort of like a Google Earth that I remember as a kid discovering Google Earth realizing that you could just explore the real world from your computer and it was magical experience. And I definitely spent a bunch of time just like going around, bopping around different places being like, I'm gonna drop into this continent. I'm gonna drop into this city. And that was really cool. I think the question with Genie three is like, is this something that people are just gonna be you know, prompting themselves, generating worlds?
Speaker 2:Is this the kind of thing that video games will adapt and build on top of? Is it more of a developer focused product? Yep. Unclear so far. We should probably have Logan on the show to break it down because I think there's a lot of people, game developers specifically that would look at this and realize just the incredible potential of this.
Speaker 2:If you can you can integrate some type of game engine into this and Yeah. And rules.
Speaker 1:It's totally a while. Be doing design wins.
Speaker 2:Mean, it's an interesting thing. When you think of like first person shooter games, when I think of my memories playing those games, there's like a few key maps and a few key games that were just iconic. Yep. And like people loved playing in those maps. And I think the interesting thing is when you have infinite optionality, you can imagine a world in the future where Call of Duty lets you just prompt battlefields, prompt, you know, different kind of arena settings for for different gameplay.
Speaker 2:But it'll be interesting if people still gravitate towards certain maps just because it's fun to have consistency with certain games.
Speaker 1:Completely agree. There will definitely be a power law. And the only way to actually realize that power law and find out what's at the long tail of that power law is to get it in the hands of millions of people. Yeah. And that's the same thing that happened with ChatGPT.
Speaker 1:And so beautiful website, by the way. I wonder if they designed it in Figma. Think build bigger build faster. Figma helps design and development teams build great products together, get started for free. So my my point is is that I I agree with everything you're saying.
Speaker 1:Is this going to be just like this meditative hangout space? Will it be something that people put on in the background and then they're studying or will they be, you know, maybe people will be using this as a development tool to then go and hard code a new video game or they'll use as an exploration canvas in the same way that people use, you know, a lot of people use generative imagery as I was listening to a One. A talk about this where someone was like like, if you're an artist, you probably can't just just turn in a final turn in a prompt as your final work. But you're going to be on Behance and you're gonna be on there's a bunch of these services that like Majority now. Yeah.
Speaker 1:You're gonna be on before, you would like scroll Instagram for references. Yeah. And you'd put that into a mood board and you'd be like, okay, this is the brand that we're going for. Now, we're gonna create our own and it's not gonna be derivative of any one thing. We give you a look at like, I don't know if we I don't know if we ever actually did a mood board for TBPN, but you could imagine there's like, you know, there's the there's the hardwood aesthetic, the mahogany, the official wood of business.
Speaker 1:Yep. Then there's some racing livery. There's the green that you really liked that you were like, let's do green and that was great. And And then there's, you know, a little bit of sci fi. There's Gong for some reason.
Speaker 1:You mix all these up and all of a sudden, it's not just we're not just doing racing team shtick. It's like racing team plus Gong plus hardwood Yeah. Plus all these different things, suits. And you add all that up and you get something new. And people used to do that just by pulling imagery on on Pinterest and Instagram and Behance, and Arena was one of them, I think.
Speaker 1:And and now, people use generative art to do that. And you can see that happening there. But the main thing is that like, there's zero chance that we figure that out in the lab. I think you can only figure it out by actually getting into the consumer's hands
Speaker 5:Yeah.
Speaker 1:And being very responsive to it. But, yes, there are safety concerns. But this is a game where the the the most risk taking person, the most founder mode company wins. Yeah. And that's exactly what happened in Czech.
Speaker 1:Yeah. There were huge that
Speaker 2:I'm interested like I would be interested in playing around with. One is like a voice prompting functionality where you can just be sitting with the screen
Speaker 1:Yeah.
Speaker 2:And just be live prompting.
Speaker 1:Like no hands
Speaker 2:on the keyboard. Hands on the keyboard. That's thing.
Speaker 1:And you're
Speaker 2:saying a dolphin just skateboarded by. It's Yeah. Gonna skateboard by. Right? Then you're like, oh, it's like and there's a LaFerrari
Speaker 1:Yeah.
Speaker 2:That has wings. Yep. And it's like taking off into the sky. Right? So you're just like giving people the ability to like have this almost like lucid dream Yep.
Speaker 2:Effectively.
Speaker 1:Yep.
Speaker 2:And then what what was the other thing I was thinking? Blanking. Tyler, did did you have a thought?
Speaker 4:Yeah. I mean, I I think obviously it's like super cool as a consumer use case. Like I wanna play with it. But I mean, I think you could definitely make the case that the main value of this is it being used as training data for, like, robotics. Mhmm.
Speaker 4:Like, if you train a humanoid robot off this, that's like everyone says, like, the main issue, like, why don't we have humanoids yet? Because we it's a data problem. We don't have, like, insane videos of first person like doing every single task. Right?
Speaker 1:I wonder Yeah. I mean, I I don't know enough about it. But you'd think that you'd be able to generate endless procedural worlds with just traditional game development pipelines. Unreal Engine, Houdini, you can define you know, endless corridors. Like there's that game No Man's Sky.
Speaker 1:Have you heard of that? It's like Yeah. Every single planet you go to is procedurally generated. There's an unlimited canvas. So And you'd think you'd be able to walk around with that and then just do some style transfer on top of it to get to something that is trainable.
Speaker 1:But maybe this is better. I don't know. We need to talk to some some robotics people to see if this is actually like
Speaker 2:a Yeah. Well, we talked to
Speaker 1:But I we
Speaker 2:talked we we talked with the team from physical intelligence and they said they have effectively, they're like generating a bunch of live real world data. The question is how valuable is this
Speaker 1:synthetic mean, Waymo, Tesla and Cruise all had very serious simulation teams that were developing. They would they would go and map the world, take all the pictures, reconstitute that into essentially a video game and then the cars could virtually drive around. And then they they did have the trouble of like, they kind of needed hallucinations because the first time that like, it wasn't just like a dog running out and and thing, but like what what happens how much train data is there on like a cow going in the middle of the road? Like, that happens like one in a 100,000,000,000 vehicle miles traveled. So you could have like petabytes of of data of cars mapping the road and maybe the big Tesla data set has like one image of it and so you can train on it.
Speaker 1:But in a simulation, you're gonna get a lot more crazy hallucinations and then that might be valuable. Yeah. I guess my point Tyler is that like you're describing like the b to b use case and and I think that there might be a consumer use case.
Speaker 2:Here's the consumer use case.
Speaker 1:And the consumer use case will be more monopolistic. So so yes, like OpenAI and Anthropic are duking it out in b to b. Right? And and it looks like that will be a lot less lot less winner take all than chat. Like consumer chat, like the the the interface, the the new consumer company with all the aggregation that ChatGPT has is gonna be incredibly valuable.
Speaker 1:And then all the hyperscalers will have a frontier model that they can sell at, you know, somewhat competitive rates and they'll make a lot of money and they'll do great and it's a big new market. So that could that that could happen here. The thing is that if they if they if they start selling this to robotics training companies, what's stopping someone else from training a similar model and then selling it to another robotics company? It becomes more oligopolistic, I would think.
Speaker 4:Yeah. It will isn't it like, okay, if you're super AGI pilled then
Speaker 1:As you are.
Speaker 4:Then like consumer doesn't matter as much cause they're not doing as, like, economically valuable things as a like, as b to b would. Right? Okay. In that case then, b to b is, like, way more important even if it's not, like, as monopolistic.
Speaker 2:Tyler, so much of the economy is raw consumption. It's the will of the American. Here's here's the other use case I was thinking. Yeah. I think it'd be cool if you could upload some images and some video and like recreate a scene
Speaker 1:Yeah.
Speaker 2:That you're in. So think about like your oldest like first birthday.
Speaker 1:If you
Speaker 2:could take like three images Yeah. From from that like you know celebration like cutting the cake or whatever and just like drop it into genie and just like recreate the scene and be able to just like witness it again
Speaker 1:Yep.
Speaker 2:In in like virtual reality, that would be an absolutely wild experience. And I think a lot of people would would do that when you know you know just reminiscing
Speaker 1:on And that feels entertaining and important whether or not I have a job. Like if the robots take all the jobs in this ASI future, I still want something to do with my time, right? So like why not go hang out in Genie three? Tyler?
Speaker 4:That's like pretty black pilling, right?
Speaker 1:Why?
Speaker 4:It's like wire heading all the time. If everyone lives in the simulation?
Speaker 1:You don't need to be wire heading. You can just you can just watch a movie. Like is that wire heading? You know? You have you have more free time.
Speaker 1:You can you can can watch Dunkirk. Jordy's gonna have the best time in the singularity. He's gonna be like, I've never seen a single movie.
Speaker 2:I've so many movies
Speaker 1:I'm gonna be like, I need a generative slop. I've seen everything. And Jordy's gonna
Speaker 2:be just been building up an incredible backlog. Incredible backlog. Almost a thirty year backlog.
Speaker 1:It's gonna be amazing. You have you have a decade worth of films to watch and enjoy and discuss. It's gonna be a fantastic post singularity life for Geordie. Well, until we hit the singularity, you're gonna need to stay compliant. You're gonna need to get on Banta, automate compliance, manage risk, prove trust continuously.
Speaker 1:Vanta's trust management platform takes the manual work out of your security and compliance process and replaces it with continuous automation whether you're pursuing your first framework or managing a complex program. So speaking of robotics, Tyler, I wanna talk about the the five levels of robotic autonomy from semi analysis. This article dropped when we were in New York last week. We didn't get a chance to cover it, but I thought it was pretty interesting because just like with autonomous cars, they're like we had the five levels of autonomous cars like level zero is basically no autonomy to your Carrera GT, fully full driver engagement, no no
Speaker 2:What is it?
Speaker 1:No traction control. Is that is that level level one autonomy? No. Level one was like cruise control, basically lane keep assist, the basic stuff. Level two was it it does lane centering and adaptive cruise control.
Speaker 1:So it will it will it'll brake if a car is slowing down in front of you. It'll speed up. But you have to be very engaged and you have to be prepared to take over at any time. Yeah. Level three is is the car is basically driving itself fully stops at stoplights, does everything but it can tell you, hey, you gotta get back in the driver's seat.
Speaker 1:Yeah. And then level four is is the the human doesn't need to be involved at all and level five I think like no steering wheel something along those lines. But there's always this question, know, the the humanoid robotics discussion has become really really focused on like level five, the most insane where we're AGI pill that's gonna be humanoids that can do everything. They can do plumbing. They can move perfectly.
Speaker 1:But clearly, there's gonna be a rollout here. And so Semi Analysis did a great job of kind of breaking down, like, where we are because there's actually a a continuum of robotic capabilities and you'll see some of the the those in that image. So level zero is scripted motion. This is high accuracy, high repeatability, but this this unlocks twenty four seven automation and high throughput. So this is when you see the car factory with the robotic arm that just moves the windshield, picks it up, puts it on the car, moves the windshield, puts it back.
Speaker 1:Like, that is perfectly scripted in a computer simulation, like like the key framed animation essentially. It does the same thing every time. There are no cameras on that robot whatsoever. And so, if you are next to it and it decides to go like this, it will hit you and it might kill you. So you have to be very careful.
Speaker 1:So there's so there's typically like fencing around these and they have these Have you ever been to Hadrian and seen the the light curtain? Have you seen this thing? No. So the light curtain is a a bunch of lasers and and if you break the beam, it will immediately trigger stop everything on the So it's it just knows Don't if you
Speaker 2:kill the humans.
Speaker 1:Exactly. Exactly. But there's no there's no cameras involved. There's no machine learning. It's purely just a big powerful, you know, arm that is scripted to do exactly what it what it can.
Speaker 1:But that's extremely useful and we use tons of these and these these robots have been around for, you know, decades at this point and they are definitely out there. They're expensive and you need constant oversight. And and interestingly, even though they do, in theory, enable twenty four seven automation, they often don't run twenty four seven because they need a person managing them all all the time. And so, like, they like, there are tons and tons of facilities that actually just straight up shut down the robots when they go to lunch, which is kinda crazy but that's just the nature of these things. They're so precise.
Speaker 1:And then we've talked to other folks about like, you gotta change out the motors, change out the grease, you gotta
Speaker 2:Yep.
Speaker 1:You gotta put the oil can in the in the joints basically.
Speaker 2:Yeah. And the big, you know, we we've talked to a few people around trying to get a sense for where humanoids will be valuable and people that run factories with traditional robots.
Speaker 6:You
Speaker 2:know, these sort of the the arms that that you're describing Talk about just how often they're having to replace parts and motors and when you have a humanoid, you're like adding a You're basically like multiplying the number of motors that need to be functioning properly in order for the robot to be like online and productive. And that's just gonna be one of the challenges that anybody building humanoids is gonna have to deal with.
Speaker 1:Techno chief 2,000 in the chat says, good morning, brothers. Good morning, Techno chief. I hope you're on Graphite code review for the age of AI. Graphite helps teams on GitHub ship higher quality software faster. Now, back to the semi analysis breakdown.
Speaker 1:That's a new transition. Level one is intelligent pick and place. And this is important because this is also something that we've had. So you put you put motors on a gantry x and y axis then and you put a little grabber. It can be anything from like a suction cup to a little like actuator.
Speaker 1:And all of a sudden, if you just say, there is the diet coke, move this over, pick it up. It's like the the claw game, you know, the claw game at the carnival. So you put a camera, some object detection and then you map that. And this is like very basic open CV computer vision, very I mean, it's amazing. Miracle.
Speaker 1:But it's still like, it's very doable at this point. There's plenty of, like, open source packages. There's a bunch of companies that have done this. And it's important to to define this as, like, this counts as level one autonomy. There is machine learning in the process.
Speaker 1:There is computer vision at work. And because of that, this is a tool that can be used and has benefits and costs.
Speaker 2:But, is it end to end?
Speaker 1:I mean, it doesn't matter. But, sometimes it can be, sometimes it isn't. But, the I think the more important thing you're getting to is that there are a lot of people out there who are showing humanoid robotic demos doing things and they're saying, hey, we have a level four fully autonomous humanoid robot. It can do anything. And they show it doing a level one task.
Speaker 1:And it's like like I remember seeing some some demo of a humanoid robot just taking parts from one place and putting them to the other side. And it's like, well for that, you just need a robotic arm with scripted motion. You need level zero autonomy actually. You haven't, like you're not demoing it in the way that that would actually necessitate And so even if you did it and even if you are successful, it's a waste of money because you'd be better off using a simpler robot for that. Yeah.
Speaker 1:And the analogy here is that like LLMs are clearly incredible to the point where I believe the OpenAI IMO model was purely text based. Like, it didn't have access to Python. It didn't have tools. Right? And so but at the same time, no one cares.
Speaker 1:Like, like, why not give an LLM tools? Like, obviously, ChatGPT is better when it has a browser, when it has a Python REPL, when it has, you know, access to a database, when it has just things that it can actually look up a calculator. Like, it should there's no reason to artificially constrain it just because like, oh, that's that's more impressive from an AI research perspective. And so in the same way, a humanoid robot should also have access to a standard robotic arm if it needs to. And the right and like you should if you're running a factory you should say, hey, for this task we don't wanna use the humanoid robot.
Speaker 2:In the near term, John. We wanna use the conveyor. Job opportunity for humanoid robots to just turn the the regular robot arm on and off. Just be the guy that presses the button?
Speaker 1:You're joking, but it's real. It's 100% real. Just like just like, you know, the LLM could try and memorize everything on the web. That was the first version of ChatGPT. It didn't have access to a web browser.
Speaker 2:Yep.
Speaker 1:Now, if I ask it you know how many how many you know how many how much sodium in a can of diet coke, it probably has that memorized. But also it can just Google it and look at the results. Well maybe not Google it. Maybe Google it. We don't know.
Speaker 1:We don't know how to use
Speaker 2:We don't know.
Speaker 1:I don't think they're Googling it. I think Google does not allow other people to use like Google search as an API but who knows? Big question.
Speaker 2:I never know.
Speaker 1:I can use Google. I can use chat GPT. Why can't I tell chat GPT agent? Open up google.com chat GPT. Chat GPT agent.
Speaker 1:Go to google.com. Download. Hit query Gemini for me.
Speaker 2:Search this for me.
Speaker 1:And so, there are there are other levels and I think these other levels from two to four are gonna become increasingly more important because these are the ones that are more on the frontier and they're more and they require more and more AI, more and more, you know, end to end machine learning. So level two is autonomous mobility, scene understanding, higher order planning, long horizon reasoning, agile movement capabilities or open world navigation and traversal. So these are like the Boston Dynamics robots. When you have that like Boston Dynamics dog that runs around, that dog is very useful for let me see. Level two is autonomous mobility.
Speaker 1:Robots that can understand the open world navigate and traverse various terrains. And so early production phases for inspection and data collection roles. You send a drone out somewhere. Construction sites, oil and gas refineries, critical infrastructure. The the the default example is like you got the nuclear power plant and you want the robot dog to run around and take images of everything.
Speaker 1:But there's a bunch of different places and there are a bunch of different companies that essentially offer level two autonomously mobile robots now and it's real. It's like it's a real thing. It's just a narrow use case. They can't do everything. But if you wanna send the dog out on patrol, you can.
Speaker 1:And and of course, occasionally you'll want a humanoid, not a dog for certain things. But this is not, it can't do everything but it can get over rough terrain, it can climb stairs, it can do things that aren't pre programmed. Yeah. Where it has to understand, okay, there's a stair coming. I gotta move my balls.
Speaker 2:There's a Chinese company that's been showing off a robot that can crawl, swim and fly. They're gonna just like walk. It can walk around like it's like a spider. That's interesting. And then it can jump into the water and and swim through the water.
Speaker 2:Like actually go under and then come up to the surface and actually take off into the air.
Speaker 1:Can it do sales tax or does it need
Speaker 2:to use numeral h We'll dot have to use numeral.
Speaker 1:Okay. Well, we'll tell the robot, put your sales tax on autopilot. Spend less than five minutes per month on sales tax compliance. Go to numeralhq.com. So that's level two, autonomous mobility, the robot dog.
Speaker 1:Level three is low skill manipulation. These are getting more humanoid like robots that can perform basic, noncritical, low skill tasks. The unlock here is generalizable manipulation, advanced pick and place as a capability in mobile manipulation. So you want a robot to go and pick up a box and move it across. It's not a defined zone where the pick and place robot is gonna sit.
Speaker 1:You can kind of set it up anywhere, give it some basic rules, but you're still gonna be, you know, somewhat piloting it, giving it general general Yeah. Like, you know, overview of what it needs to be doing. And so, this is actually already deployed in some pilot stages in kitchens, laundromats, manufacturing, and logistics. And these are like bipedal humanoid robots. Now, don't have five fingers, five toes.
Speaker 1:They don't look perfectly human.
Speaker 2:Yep.
Speaker 1:But they can actually Yeah.
Speaker 2:The big thing is even a remotely operated humanoid that had the ability, that had fingers that could do traditional act you know, activities that were more complicated. Yep. Even a remotely operated humanoid could be completely valuable. Right? Because you could have you could have somebody somewhere else say like, pick up every single leaf leaf in my backyard and put it in the green bin.
Speaker 2:Yep. And there's and there's like problem there's like a bunch of like bunch of use cases you can think of. I mean, the big debate is around what is the level of human involvement in Waymo's. Right? Yep.
Speaker 2:That the allegedly, there's there's at least one person kind of overseeing every active Waymo remotely.
Speaker 1:I think that number is blended across the entire org. So like at a given time, there's probably like one human looking at a screen with four Waymo viewpoints on it and then they can kinda jump back and forth. But then there are other people Yeah. Like monitoring the network and checking on the tires.
Speaker 2:I guess my my point is that is that like having somebody remotely observe the activity of a robot Yeah. While we're trying to get to the point of full autonomy Yeah. Yeah. Is totally worthwhile. Yeah.
Speaker 2:And is what people should expect. Right?
Speaker 1:This Wait. Yeah. This should be pretty searchable. Tyler, can you look up the number of employees at Waymo and then the number of Waymo's on the road and get the ratio there? Because the real test of robotic leverage should be more vehicles on the road than employees of the company.
Speaker 1:But it seems like Okay.
Speaker 4:So there's 2,500 employees around and there's only 1,500 Waymo's.
Speaker 1:Yeah. So that's the number that we're that we're hearing. When people say like 1.4, 1.5, I think that's it.
Speaker 2:I'm sorry. These could easily be contractors
Speaker 1:that
Speaker 2:aren't technically employees that are hired to work round the clock for every single, you know, active waymo.
Speaker 1:So But still, you would expect I mean, the bottom line is that is that
Speaker 2:It's still a massive step up from not having somebody that's just sitting in the vehicle observing Yeah. It real time.
Speaker 1:Yep. But but even if we assume that there are zero contractors in there, like the job displacement narrative at least at this moment in time is completely debunked because because we put a 1,500 taxis on the road and it took 2,500 people to do that. Right? Like now the obviously the technological vision is that you'll have 2,002 employees thousand actually. 200,000.
Speaker 1:Yeah. Yeah. Just like, you know, you don't need you don't need just like you used to have, you know, one paper boy delivering a newspaper to every city block. Now you have, you know, a number of engineers that serve, you know, social networks and they just kind of go out and they're distributed across the Internet. So but but that is an interesting that is an interesting benchmark.
Speaker 1:And and something that should be like, the ratio of of vehicles on the road for Waymo to employees at Waymo is an interesting stat to follow. Even but the con I agree that the contractor thing is is is important. Anyway, let me tell you a profound Get Your Brand mentioned by ChatGPT. Reach millions of consumers who are using AI to discover new products and brands. ProFound is our latest sponsor and we're very happy to tell you about ProFound today.
Speaker 2:Get on it. If you're running a business or fund or anything like it, you should probably know how people are understanding your business through LLMs. Yes. Or found makes it super easy.
Speaker 1:So the last the last level of robotic autonomy. Level four, force dependent tasks. These are things that must be done very precisely. Robots can perform delicate tasks at this level that require force and weight understanding I e finding a phone in a pocket. Sounds easy.
Speaker 1:Very difficult if you're a robot.
Speaker 2:Doesn't sound that easy. I think everybody here has experienced
Speaker 1:Yeah. And you actually drop your phone a bunch. It's pretty it's one of the harder things you do, driving a screw in on the correct threads. So this is purely in the research phase. The capabilities that this will unlock are delicate, force dependent tasks, fine grained manipulation, and this is purely in the research.
Speaker 1:So there are different and and one of the examples that they give is like, praise place the soft bread on a plate. So you could imagine that being valuable in the kitchen context. Or, that would If you're just like, the robots just crushing the bread every time that's like
Speaker 2:a work. Trying to pass steak to your friend, they're sitting in a different part of the plane.
Speaker 1:Yes. Yes.
Speaker 2:Yes. That's
Speaker 1:That requires That's a force dependent task.
Speaker 2:Definitely. Yeah. Because you might get tackled
Speaker 1:And when the flight attendant comes up to you, you have to put your hand on their chest, not fully threateningly so that you get on the no fly Just gently.
Speaker 2:So they don't.
Speaker 1:But you wanna touch them. You you wanna place your hand on their chest. Just a little bit just to let them know this could go one of two ways.
Speaker 2:Probably shoulder.
Speaker 1:Yeah. Probably shoulder is more respectful. But you want you want to let them
Speaker 2:know out of my face.
Speaker 1:That you're ready to die.
Speaker 2:I took custody of that stake.
Speaker 1:Yeah. Yeah. That that this is happening one way or the other. This can go down one or two ways. But you don't want to actually cross the threshold.
Speaker 1:So, you know, if you're passing stake to your buddies in economy, don't use a level three robot
Speaker 2:And I have a tough
Speaker 1:because the robot will just push, shove right through them. Other examples include unstacking single plastic cups from a stack. Any any fraternity member should be familiar with that. But the robot has is still working. So there's still full employment for the solo cup out
Speaker 2:there saying I'd love to see a robe
Speaker 1:Robot set up set up
Speaker 2:stacked solo cups.
Speaker 1:What's the beer pong? Yeah. Yeah. Robots, you know, not gonna be able set up beer pong for a while, they're researching it right now. Place an egg in a pot, place a bag of chips on a plate, twist and lift a bottle cap, literally like open a bottle of medicine.
Speaker 1:Actually, one of the more useful things
Speaker 2:Very hard for children. Do? Very hard for children still. They're working they're working on it, but Yeah.
Speaker 1:Yeah. What's the arc AGI of of robotic tasks? That that's what we need. Maybe it's taking the phone out of the pocket. Something that anyone can do, even a child.
Speaker 1:Yeah. But but it'll be the last task solved by a humanoid robot. Yeah. But I mean, can imagine, like, twisting a bottle cap is actually, you know, we we have an aging population. We need more help in the in the elder care market in in hospitals and
Speaker 6:Yeah.
Speaker 1:And nursing contacts. And, if you have a robot that can dispense medicine effectively, you can imagine that that being very valuable. But right now, that would require like an entire rebuild of the way we distribute medicine because we distribute it in child safe and also robot safe bottles. Yeah. So, anyway, let me tell you about linear.
Speaker 1:Linear is a purpose built tool for planning and building products. All of these companies that are going to develop level four force dependent task robots, they're gonna need to be on linear.
Speaker 2:It probably is
Speaker 1:the system for modern software development and allows you to streamline issues, projects, and product roadmaps. So, moving on to the next story. There's a lot
Speaker 2:going What are going?
Speaker 1:Well, the big thing, we should talk about Cerebras because this was a company that was kinda dogged for a while. Are you familiar with this company? Yeah. So Cerberus makes a wafer scale GPU, wafer scale chip. When semiconductors are made, you go and you want an Apple, you know, Apple silicon chip or an Nvidia GPU.
Speaker 1:There is a wafer that is grown of silicon and then the wafer is etched with all the different transistors on there, the three nanometer, the four nanometer, the six nanometer transistors are put onto the chip. And then the chip is the wafer is sliced up into individual chips. And the benefit of that is that if one of the chips is bad, one of the transistors is off, that chip's not working, you can dump that one and the rest are gonna be fine. But with wafer scale computing, with wafer scale chip manufacturing, if there's even one defect anywhere on that wafer, you gotta throw the whole thing out.
Speaker 2:So, yeah.
Speaker 1:So everyone was very ups very worried that the yields would never get high enough. And they were saying, Cerberus also, there's other trade offs with when you're at wafer scale with memory and and inference. But what we've heard and what Andrew Feldman, the CEO, is saying is that a lot of the crazy bets that they place, they're paying off and it's working very well. So Andrew Feldman says, in 02/2016, Sam Altman and Andrew met. OpenAI was a vision.
Speaker 1:Cerebras Systems was a PowerPoint. Sam and the OpenAI founders became one of the early investors in Cerebras Systems. Good to see Sam getting a markup. He needs it. He needed that.
Speaker 1:Needed that badly badly. In the following years, the Cerberus and OpenAI frequently met. The teams frequently met to explore working together but the timing was too early. Large language models hadn't been invented yet.
Speaker 2:This is what being early looks like.
Speaker 1:Truly. Like developing Building technology. Foundational technology
Speaker 2:That's the trend
Speaker 5:that has
Speaker 1:foundational technology that doesn't exist yet. Today, the story comes full circle. OpenAI just released its most powerful open weight reasoning model and it runs fastest on Cerberus systems. Not a little bit faster than the competition. It smokes the competition.
Speaker 1:Running our running on our third generation wafer scale engine, GPT OSS one twenty b runs at up to 3,000 tokens per second. The fastest speed achieved by an open AI model in production. Reasoning that takes minutes on NVIDIA GPUs can take a single second on Cerberus systems. Good things Congratulations take to the Cerberus team. An overnight success.
Speaker 1:Been in the trenches for a while. But I I think this is interesting. We've talked to some folks who have started using Cerberus to speed up inference for specific use cases within larger AI systems. I think that's very interesting. And I think that we are we're like, it's very easy to collapse the narrative AI of AI into, you know, there's gonna be technology, one single path, one single implementation.
Speaker 1:But as we're seeing with the development of the new GPT models and the new OpenAI, ChatGPT functionality, it's like you squeeze out performance in a bunch of different ways. You give it a browser. You give it reasoning. You give it, you know, a Python REPL. You give it the ability to write code.
Speaker 1:And, like, you add all that up and you get something great, and it's the same thing on the inference side. Sometimes you want to do things on on device. Apple's, you know, kind of steering towards doing that with Apple intelligence. Yep. Sometimes you want to do it on a really big cluster of NVIDIA h one hundreds or big GPU cluster.
Speaker 1:And sometimes you need to just run something extremely fast and that's what Cerberus is powering. So I'm interested to understand what 3,000 tokens a second on the Yeah. Because I I was thinking about it in the context of that that famous Amazon
Speaker 2:Well, mean an example being like right now if you wanna use like if I open up chat GPT and I wanna use it as functionally like knowledge retrieval search than doing four o and just getting something like relatively instantly makes And then, but I know I would get a better result with o three pro. Yep. And, but if you're using using o o three pro for like raw knowledge retrieval in terms of like, I wanna understand this fact or this person, it's just not a great experience. Right? Yep.
Speaker 2:Because I don't wanna figure it out in like a few minutes. Wanna figure it out now. Right? And so theoretically, you could get to the point where you could get o three pro quality answers
Speaker 1:Yep.
Speaker 2:Relatively instantly.
Speaker 1:I want two things. The first thing is I want you to sign up for fin.ai, the number one AI agent for customer service, number one in performance benchmarks, number one in competitive bake offs, number one ranking on g two. The second thing I want is I want when I go to ChatGPT and I type in a query, I've been extremely frustrated by the the model picker because I'm constantly going back and forth between four o and o three pro. And one takes, you know, five seconds, the other takes fifteen minutes. And sometimes I accidentally hit something with o three that I should've gone to o four o with and then I have to open a new one and then I'd copy my prompt over and put it there.
Speaker 1:And then I'm like, actually, yeah, that's a great one. Like, this was Googleable and so it just put pulled it into the nice format. What I would love is is a system where I can where I can hit it with a prompt and it goes to Cerebras and it gives me just, hey, off the top of my head, here's what I know. Here's the basics of what I what what I'm pretty confident about, but I'm gonna keep working on it. So I kick hey, I I kicked off an o three pro heavy duty reasoning.
Speaker 1:I'm searching, I'm collecting data. I'm gonna get you the best possible answer on this, but while you're waiting, here's the thing that I can turn over in two seconds. Here's what I know right now.
Speaker 2:Yeah.
Speaker 1:And I think that that Yeah.
Speaker 2:And that's the same experience you might have working with somebody where you ask them a question and they're like, I'm 90% sure it's this. Give me thirty minutes. Yep. I'll come back to you Yep. With confirmation.
Speaker 2:We'll figure out the plan from
Speaker 1:there. Exactly. Exactly. And and that also allows you, if somebody says, I'm 90% sure that that that it's this direction, that allows the person that you're interacting with to go and think about that path and and now there's a 90% chance that that the work that they do.
Speaker 2:Something mission critical that Yeah. You can't make
Speaker 1:And then if they and then if they they need to adjust course, they haven't burned a bunch of time. So, I'm excited for more, you know, advanced model routing. We've talked about the the mixture of experts. We Tyler, what was the Grok of evolution? Was like a mixture of models?
Speaker 4:Mixture of models of experts.
Speaker 1:Well, yeah. What was the latest Grok heavy architecture? It was something else. It was like, it was a mixture of something on top of a mix. It was a bunch of mixture of experts models and then and then and then it was a bunch of mixture of models and then we were gonna do mixture of models on top of models, mixture of companies, mixture of
Speaker 4:Oh, yeah. Yeah. Because we're gonna make a router on top of that which would prompt
Speaker 1:Every time you prompt, it prompts all of them. Yeah. And then it and then there's
Speaker 4:a Mixture of models of
Speaker 3:models of experts.
Speaker 1:Yeah. And then it and then it and then and then there's a scoring that gives you the final best. Yeah. Okay.
Speaker 4:But I think apparently people, I mean this is all like
Speaker 1:Yeah.
Speaker 4:Leaked stuff on Twitter so it's like probably not true. But people are saying like GPT five is like supposed to be kind of What I described.
Speaker 1:Yeah. Yeah. Some kind of
Speaker 4:routing thing.
Speaker 1:Let's go. Yeah. Put me on the team. I just predicted it two days before it comes out or something. I'm good.
Speaker 1:Yeah. Took me a while to get there. But I think I think I'm excited for that. Yep. I I'm excited.
Speaker 1:Anyway, let me tell you about Adio. Customer relationship magic. Adio is the AI native CRM that builds scales and grows your company to the next level.
Speaker 2:Good Adio. Did
Speaker 1:you see this Hunter Biden clip? We stay away from politics but pulled this is up this video. This was this was very very insightful as to how people think about artificial intelligence and automation. So this is from channel five, Hunter Biden on AI automation and whether or not you should tip it in and out. And Growing Daniel has a very insightful post here says, when he says AI, he really means software and simple robotics.
Speaker 1:But still, I'm actually very surprised by how smart Hunter Biden is. Like, my friends are smarter, but I thought he'd be way dumber after all the crack. But listen to what he has
Speaker 3:to say.
Speaker 7:In and out is fine. You don't tip it in in and out.
Speaker 2:I do.
Speaker 7:What? You tip it in and out?
Speaker 2:Yeah. They have to wear those hats. You know what that feels like?
Speaker 7:Did did you serious conversation? I met somebody that is in the you know, owns fast food franchises. His McDonald's employs 55 people. Mhmm. K?
Speaker 7:He went all AI. Oh, It's about a $2,000,000 investment.
Speaker 1:Let me just show you
Speaker 6:a humanoid robot.
Speaker 1:It's like
Speaker 7:He only employs five people now. Oh. So his margins go up by like 27%. It'll make back the $2,000,000 investment in under like eighteen months.
Speaker 3:Mhmm.
Speaker 7:Think about this. There's about like 13,500 McDonald's in The United States Of America. I did the math. If every one of them went down to five from 55, lost 50 on average 50 jobs, it's 600 and, like, 70,000 jobs in America. Mhmm.
Speaker 7:And that's, like, it's a certainty. And that's just McDonald's. You think that, Burger King, Wendy's, Taco Bell, I mean, across the board Mhmm. You're talking, what, like, probably three and a half million jobs in the in the in the fast food industry alone that will with AI with easily within the next five years, if not three years. So I have I've flipped my thinking about this whole AI thing.
Speaker 7:You're either gonna have a massive extinction event
Speaker 2:Mhmm.
Speaker 7:Or it's gonna be really good with a rough patch in the middle. Because if between supercomputing power, which were were there already, okay, like quantum computer
Speaker 6:There we go.
Speaker 1:And We're not quite there on quantum computer.
Speaker 7:But that figure out
Speaker 1:the I think we are we are generating exactly zero tokens.
Speaker 7:Fusion within the next, like, five years. And if we do that And now fusion. Of Yeah.
Speaker 1:I have some friends that work on fusion. I've seen enough. I've seen enough.
Speaker 2:Give him a give him a hard tech fund.
Speaker 1:Yeah. Yeah. Yeah. Well, he doesn't
Speaker 2:He's even point of size.
Speaker 1:Yeah. He doesn't even need to be in the private markets. There's plenty of public names he could get into if he's bullish.
Speaker 2:Fusion, Yeah.
Speaker 1:I'm sure that'll work out great for him when he gets in this. Be rough. Anyway, the interesting thing here, yeah, he's talking about automation. I actually know an entrepreneur who built a, you know, you take a TV, you turn it horizontally, you touch screen and you can order at McDonald's. I don't know if he actually had McDonald's as a client but he had a number of those types of customers where you shop on a screen and check out on the screen.
Speaker 1:And that's something that the we had the slowest takeoff ever for that technology. Truly. Like when do you think it would have been capable from, you know, from first principles just the capability of software and hardware to show up, click buttons, pay, and then and then send the order to a human cook who's still cooking.
Speaker 2:Yeah. It's so
Speaker 1:interesting even even To you.
Speaker 2:Even at grocery store grocery store checkout.
Speaker 1:2,005 level technology in my opinion.
Speaker 2:A lot of grocery, I mean, Air One still doesn't have like self checkout. Yeah. But I just actively avoid self checkout.
Speaker 1:Yeah.
Speaker 2:And you wonder you know, I think a lot of people feel the exact same way. It's like being able to sort of outsource the scanning
Speaker 1:Yeah. Of People do the self checkout because it's a thrill. Because like it's this negotiation like will they catch you for how much you're stealing? Because like they're not really watching but there's someone that's kinda watching and you could get into altercation and so it's about like it's about getting your
Speaker 2:risk on?
Speaker 1:Exactly. It's
Speaker 2:about going risk on.
Speaker 1:Yeah. It's it's like the girls Grocery story to
Speaker 2:encourage thrill seekers should actually start having like armed security there.
Speaker 1:Yeah. It needs to be high stakes.
Speaker 2:Standing there like this.
Speaker 1:Exactly. High stakes.
Speaker 2:And so if you mess up and they catch you you're getting tackled.
Speaker 1:It is hilarious how Yeah. They kinda got rid of like the scanner but they definitely need to watch that stuff because people will just like fake scan and then check out. I don't endorse doing
Speaker 2:takes here where it's in areas where
Speaker 1:Yes. Yes. Yes. This is great take.
Speaker 2:There is
Speaker 1:And Aaron Gidden too.
Speaker 2:Yeah. Basically this idea that like, I think that twenty years from now, I will still go to restaurants and have a human waiter
Speaker 3:Yep.
Speaker 2:Because it's a great human waiter improves the experience.
Speaker 1:Yes.
Speaker 2:Right? It's it's enjoyable to have somebody that understands the restaurant you're hanging out with across
Speaker 1:But the person will look more like an educator and an entertainer than a than like a plate carrier.
Speaker 2:I wonder if anybody the way,
Speaker 1:wonder if anybody's you will be someone who talks about the food and gives you advice.
Speaker 2:Something. I wonder if anybody's building like a friend pendant style device for waiters. You just walk up to the table, have a conversation but it's just actively like submitting them through like the restaurants like order management system. So the waiters just hanging out there. They don't have to be like writing down stuff or in a phone.
Speaker 2:They can just have a conversation be you want this? No cheese? You want fries with that? You want a side salad? Great.
Speaker 2:Great. Great. And then it's just automatically in the system and starts getting I
Speaker 1:like this idea. Usually when when like consumer hardware goes to the enterprises like where it goes to die, Like the original HoloLens and the Google Glass. Like as soon as they said like, hey, we're actually gonna be focusing on niche enterprise use cases, usually a bad sign. But that could be kind of like a toast type, you know, vertical SaaS outcome. I don't know.
Speaker 1:I I I'm I'm more bullish on that idea than at least hearing it for ten seconds. But I don't know. At the same time, you go to a really nice restaurant, I would I would be leaning even more in the pure human world and being like I would like to go to the restaurant that doesn't even have phones. And there's actually a great post in here by Hip City Reggie. We will read through because I want your take on this.
Speaker 1:So Reggie James, friend of the show, says, screenshot essay on wearable AIs. Will all AIs leave the room? Sitting down at breakfast, Yatu reveals he's wearing an AI pendant product Omni. I've never heard of that one. Very cool.
Speaker 1:There's a bunch. Sean Jackson Freeze. A couple days later, I'm wearing a friend necklace, shout out Avi, and talking to my wife, and I stopped to look at it wondering if it should be included in the goings on of my home life. I think it's clear that we will start to create a set of social norms around AI that's extremely explicit. We will state things like, can all AIs leave the room?
Speaker 1:Spaces will have machinery running that renders connected electronics useless. So, yeah, we should have a Faraday cage that we can go hang out in. At the core is a it's a question of which mind's authority and priority in a given space. It's probably a good idea to assert the human ones. What do you think?
Speaker 2:So Jackson Doll had a review of Friend. I guess he got an early one from Avi. The review was generally positive. He said, clearly feels different to talk to a thing you're wearing and must touch to get a response from. With friend, you put voice in and text out, which is like kind of an interesting feature.
Speaker 2:So you're it you're it's just hanging out with you, but then it's messaging you
Speaker 1:Mhmm.
Speaker 2:On your phone Mhmm. About your day, which is kind of a new just a new format. He he says, all said, feels like Avi have built something truly different, a hardware device that embodies a new set of values. I suspect they will find it in especially young group of people who quickly find themselves in daily communion with their new friend. And again, this seems to just continue to be incredibly controversial and I'm sure it will for a while.
Speaker 2:Daniel says, how do you feel about recording everyone you meet without their consent? Jackson says, bad. Ought to figure out society societally with these types of things.
Speaker 1:Yeah. The voice in text out thing is interesting. I feel like there's there's a ton of different surface area to explore outside of just give someone a blank text box like Yeah. That worked for Google with the 10 blue links. It works for ChatGPT but I think now the new surface area is figure out how to push stuff to the user and this is a way to do that.
Speaker 1:You're just ambiently recording and then I feel like the retention is gonna be way higher than other devices because as long as you put it on it's going to be sending you messages.
Speaker 2:Yep.
Speaker 1:And so, I think that's gonna be really really good for retention.
Speaker 2:Yeah. There's this there's do you get push notifications from ChatGPT at all?
Speaker 1:Only if only post prompt.
Speaker 8:Yeah.
Speaker 1:So, if I fire off deep research, it will give me a push notification telling me, hey, we're done with that. Yeah. But But never
Speaker 2:the future, for example, where ChatGPT has access to your calendar Yep. And it's like, hey, I saw your meeting with this person this Yep.
Speaker 6:Do you
Speaker 2:want me to run a deep research report
Speaker 1:Yep.
Speaker 2:On what they've been up to in the last like few months? Yep. And it's like, they shared this update on LinkedIn article and they went on this podcast and talked about this thing. Yep. Right?
Speaker 2:You
Speaker 1:can get a of it.
Speaker 2:More proactive.
Speaker 1:If you go to the ChatGPT app, it will actually populate ideas for prompts. And so for me right now, tells you a lot about me, it says Hollywood movies AI and filmmaking clearly because I was searching about Disney. Stock market, mag seven performance. I can just click that and get an update and it says how have the mag seven stocks performed over the past decade? What factors have driven their driven their growth?
Speaker 1:And it just boom, pulls that prompt up. Media industry, luxury watches, automotive industry, f one schedule, venture capital, tech business. And so some of those, if there was something triggering in the system that, you know, hey, this is there's there's this interesting thing going on, we should just generate this prompt and send it to John. That's that's probably an interesting feature that they'll probably explore at some point. But friend seems to have at least be they at least be seem to be exploring this type of thing.
Speaker 1:But voice in, text out, very exciting. Sleep in, rest out, also exciting. 8sleep.com, pod five. Five year warranty, thirty day risk free trial, free free returns, free shipping. Go check out.
Speaker 2:I was riding a high Monday night. I put up a 95.
Speaker 1:Let's go.
Speaker 2:And I'm down in the dumps again, John. I I got a little cocky going
Speaker 1:Well, you know what's not in the dumps? The future of nuclear uranium enrichment because general matter is bringing uranium enrichments back to The United States starting at the site where The US enrichment industry was born. We've signed a lease with the Department of Energy to establish the nation's first US owned privately developed uranium enrichment facility at the former Paducah Gaseous Diffusion Plant. Seventy five years ago, the US Atomic Energy Commission selected Paducah to help lead the nation's original enrichment efforts. Today, we are proud to return to and rebuild this historic site to power a new era of energy independence.
Speaker 1:This is Scott Nolan's company. I hung out with him while I was at Founders Fund. He's an absolute dog.
Speaker 2:An absolute dog.
Speaker 1:One of greatest to ever do it. And he's been on absolute terror. Spent I think over a decade at Founders Fund. Helped Peter Thiel with the original zero to one lectures while at Stanford. Helped, you know, ideate and bounce ideas around for that book.
Speaker 1:Then invested at Founders Fund for a decade and was, you know, kind of thinking about maybe starting a company but didn't wanna force it and just waited waited waited until the perfect opportunity came around and really put together the the the perfect team, perfect partners and has and has accelerated way faster than When general
Speaker 2:matter first announced, my first reaction which is always a positive reaction is nobody I haven't seen a pitch for this anywhere
Speaker 1:Yep.
Speaker 2:But it's incredibly obvious Yep. That this company needs to exist.
Speaker 1:Yep. Yep. And so, it seems like it's working. They they they won a contract with the government very early, earlier than they expected. And so they are moving timelines up and now they say we will enrich uranium by the end of the decade.
Speaker 1:US leadership and enrichment will allow us to lead once again in nuclear energy. Let this lets us lead in everything downstream of safe clean baseload power AI manufacturing economy. Today marks the beginning of America's restored leadership in nuclear enrichment. We thank our partners in Kentucky and at the DOE for supporting us. And you can see a beautiful render of the future facility that is absolutely massive.
Speaker 1:But you know, they're thinking big and they're and they're going for it. Yeah. There's also a great post in PirateWire Which you should subscribe to. Digging into this from a different perspective and and profiling the company, which is very exciting. Anyway, if you are interested in investing, go to public.com.
Speaker 1:Investing for those that take it seriously, but they have multi asset investing, industry leading yields.
Speaker 2:Not financial advice.
Speaker 1:And they're trusted by millions, not for casuals.
Speaker 2:Taking investment investing seriously is not financial advice.
Speaker 1:Go to Adam, person of swag. He says he started a startup to impress a girl, starts seeing product market fit, gets more compliments from male users, girls don't care, keep trying to get more MRR. Now I spend every day in a dark room coding with four men. What is even the point of this? And the best photo you could imagine.
Speaker 2:Well, would love to see Adam ring ring ring hit the gong with us at the New York Stock Exchange and say Adam why did you start this company? And he just says I just did it to impress.
Speaker 1:You know you know what's funny about this? This is this is the apocryphal tale of the founding of Facebook. Like in the Aaron Sorkin Social Network movie, the whole premise, I know you haven't seen the movie but I have seen that one.
Speaker 8:What? What?
Speaker 1:Jordy Hayes has seen a movie? Incredible. But the the the the the story that Aaron Sorkin decided to tell was basically that Mark Zuckerberg started Facebook as like, know, a way to get a date or something like that. And then Mark like was like fact check false. Like I was dating Priscilla happily for years before starting Facebook.
Speaker 1:So your whole your whole You
Speaker 2:know the truth.
Speaker 1:Your whole plot is fake. But he was kind of just like whatever, know. People like telling stories and maybe a better story that way. But the social network too will be dropping soon. If you have a way to get us in that movie, make it happen Hollywood.
Speaker 1:You're listening. We're ready to be extras. Get Tyler in I this think it'd so good if we could be extras just in the background. I think it's pretty doable. We're in Hollywood already, make some calls.
Speaker 1:This is my number one like manifest it, put it on the vision board because
Speaker 2:Let's make it happen.
Speaker 1:A very small crew of people. Those of you in the chat, Azar, Da Game, you guys would see the movie. You'd see us and be like, wow, they pulled it off. So we'll have to make that happen. Then we'll have to buy a billboard on adquick.com.
Speaker 1:Out of home advertising made easy and measurable. Say goodbye to the headaches of out of home advertising. Only adquick combines technology. Out of home expertise and data to enable efficient and seamless
Speaker 2:Adam, D'Angelo says I love the fact that all the billboards on one on one for AI products. And certainly, of them are are for regular enterprise SaaS companies Yeah. Announcing AI products.
Speaker 1:What this Oh, interesting. Do you see this do you see this response from Jasper? He is advertising, and he says cheap on demand GPU clusters. Hyperbolic dot a I. Hyperbolic is an on trend term right now.
Speaker 1:Hyperbolic can refer to several different concepts. In language, it means exaggerated. In geometry, it's related to a hyperbola or hyperbolic space. And in functions, it's related to hyperbolic curves.
Speaker 2:The irony here that hyperbolic AI, you could read it as exaggerated AI, and then every billboard on the one zero one
Speaker 1:is
Speaker 2:just
Speaker 1:It's very funny Yeah. Yeah. Yeah. The nominative determinism is that they're overpromising.
Speaker 2:But I think in this case, it's like a neoclass.
Speaker 1:Love Jasper. No hate on Jasper. Good luck to him. I hope I hope he can deliver and I hope he can go
Speaker 2:next that can be delivered quite well today.
Speaker 1:Yes. But but a hyperbolic function is something that goes up into the right and and and reaches an asymptote and and goes to infinity essentially. So, it is it is a good example and it is something that is important in AI as we scale to infinity and beyond. David George has post.
Speaker 2:He says, what do Roblox, Andoril, CrowdStrike and Apple all have in common? None of them look like obvious winners from the start but they built something far bigger than anyone expected. We call these companies model busters. Great. Name model busters either reveal a market that's much larger than anticipated or expand into new product lines so effectively that they break out of their original category entirely.
Speaker 2:We're talking about model busters now because we believe AI is creating many more of them. AI will maybe the defining platform shift of our time. It's changing how products are built, how they're distributed and how buying decisions get made. It's creating new consumer experiences, new workflows, and entirely new business models. Platform shifts often create new winners.
Speaker 2:AI is no exception. Today's most ambitious companies will grow faster and become bigger than anything we've seen before. Example here, if you were an investor modeling out Figma in the early days and you thought it would always be a Yeah. Design tool. Yep.
Speaker 2:Again, this is not how Dylan was pitching the business. But if you thought it was gonna be a design tool, you could simply look and see, alright, how many designers are in the world? And if you could get 5%, 10%, 20% of them using it, would this be a big company? Still would have been a big company but wouldn't have been a, you know, $50,000,000,000 public company most likely. And and and it ultimately kind of like broke out of that TAM by being the collaboration tool across, you know, the across entire companies.
Speaker 1:We should have we should have David back on. I really enjoyed talking to him during Andreessen LP Day. I do wonder, like, is it a tautology that a model buster cannot be modeled? Like, are we talking about an ineffable quality that cannot be defined? Like, is there is there a pattern for finding model busters?
Speaker 1:Because the, like definitionally, the model busters are things that cannot be modeled. It's funny because he's also on the growth team and he probably does like the most modeling of anyone at in Yeah. Houston.
Speaker 2:Well, Roblox is an example. So Roblox had has twenty twenty point six million DAUs in The US and Canada last quarter.
Speaker 1:Yep.
Speaker 2:And there's I think that I don't know how many people, young people 18 there are in Canada, but in The US, it's like something like 70,000,000. And so that is like a meaning, like if you were if you were evaluating Roblox and saying like more than a quarter of people under the 18 are gonna be playing this game every single day
Speaker 6:Mhmm.
Speaker 2:By 2025, you would have sounded a little bit crazy. Because I don't know that there's that many video games that I don't know how many video games have ever achieved that level of of daily active usage in a cohort like that.
Speaker 1:Video games in general have been like a model buster in the sense that people were expecting it to be comped to the film industry and I believe the video game industry is like an order of magnitude bigger than the film and television industry. Yeah. It is it is a significant expansion of growth. But my question about like how much time should you spend trying to codify model busters Or should it just be something that we refer to looking backwards? Because my my question is like, if you go back and you look at Danny Reimer in the c is seed series a of Figma or Mamoun at KP doing the b or Andrew Reed doing the c, like, at what point did it become important to win that deal to identify Figma as a model buster
Speaker 8:Yep.
Speaker 1:Versus just say the metrics are really good. Dylan Fields a killer. I'm investing on that.
Speaker 2:Yep.
Speaker 1:And then and then, yes. Maybe there's a second act. But if I get a bunch of those ultra high quality entrepreneur, ultra high quality product, ultra high quality KPIs, I'm good enough and I don't even need to really predict that this will, you know, have a second act or expand out and and the TAM will will moon like Yeah. That it's not And and you could see the same thing about like, you know, Andrew, Palmer, Lucky, like you just look at the team and and and and like the market's big enough to justify the investment at that phase and then you just keep doubling down and then it busts your model but you're in it for different reasons. You're not in it because you predicted the model would be bust.
Speaker 1:So I I I wonder what it teaches you about like the philosophy of of Yep. Of early stage investing.
Speaker 2:Yeah. I mean, I think you could have you could have underwrote SpaceX for a long time ignoring It's a great example. Ignoring the opportunity Right? For And it's still Who was thinking about probably be I I I I'd be interesting to see, you know, how
Speaker 1:SpaceX Into would value its first deck.
Speaker 2:Yeah. Or its first model.
Speaker 1:Yeah. Probably ten years into the business. I I I have to imagine it was not in any of the series a through c Yeah. Three c decks.
Speaker 2:People are like, I thought I was investing in a rocket ship company. Yeah. Accidentally invested in
Speaker 1:Internet company. Internet company. The accidental Internet company again and again and again. The Internet is the it is the category and that every company makes money.
Speaker 2:Yeah. And I still I still remember as a kid when when I grew up in an Apple household. I never had a, like, I never used Microsoft products really ever Mhmm. As a kid. And I remember it was still at a time where you were kind of like weird if you didn't have a like a traditional PC at home.
Speaker 2:Yeah. And then ten years later, everybody has an iPhone. Yeah. Right? So it was impossible to like underwrite having a breakout product of that caliber.
Speaker 1:Kind of like luxury watches. Not many people wear them right now, but in the future, it'll be weird if you don't have one. So you gotta go to getbezel.com. Your bezel concierge is available now to source you any watch on the planet. Seriously, any watch.
Speaker 2:Someone in the chat yesterday said they got a moonswatch on
Speaker 1:No way. Yeah. Amazing. Yeah. I didn't even know that those would be on there.
Speaker 2:That's amazing. Been out they've
Speaker 1:Moonwatch or moon swap? They've had different variations. Okay. Cool. Very cool.
Speaker 1:Well, congrats to them. Hope they enjoy it. Send us a picture. We have some breaking news about SiriusXM. They are canceling the Howard Stern show.
Speaker 1:Can you call it a cancellation when the guy's 71 years old and he's been doing it for twenty years? And they say it's no longer worth the investment. They've been paying him a $100,000,000 a year. That is a huge salary. And that's what three four times Colbert?
Speaker 1:Wow. That is that's big. That's power power of of radio power of you know the power law. He's done fantastically. Congrats to him.
Speaker 1:Emerged if looking for a new gig you're welcome to come and hang out at the Ultradome. You can sit at the intern table next to Tyler and we'll we'll we'll bounce ideas off you.
Speaker 2:Yeah. It's wild. I I really wonder where SiriusXM business goes.
Speaker 1:Right? I know I know where this goes. Post AGI, you're gonna listen to every hour of Howard Stern. I know you've listened to zero hours but there's probably twenty thousand hours in the catalog or something like that of Howard Stern content. You could listen to it from the beginning.
Speaker 2:Do people listen to the back catalog ever? Absolutely not. Serious, sound silly $7,000,000,000 company.
Speaker 1:Wow.
Speaker 2:That's bigger than I would have thought.
Speaker 1:I wonder, yeah, revenue like how much of that cost. I mean, makes sense to give him a huge slice of that. It is a talent driven business and he could go to Spotify, he could go somewhere else. My question is like, he is old, will he retire or will he do a podcast or do something independent? Is there news?
Speaker 2:No. They what? They apparently did how much?
Speaker 1:Okay. You look that up while I tell you about wander. Find your happy place. Book a wander with inspiring views, hotel grade amenities, dreamy beds, top tier cleaning, twenty four seven concierge service. It's a vacation home but better.
Speaker 2:Now, Jordan, you have to go. 600,000,000.0 in 2024 revenue. Yeah. So they're trading at less than 1x revenue which says when you have a shrinking business Yep. It is place a to be.
Speaker 1:Not stock, a I suppose. Yeah. I wonder how much of that is getting eaten up by talent. Yeah. This is
Speaker 2:a trillion stock if they have
Speaker 1:Yeah. I wonder how much I wonder what percent of SiriusXM content is, like, power loss, celebrity, host red, high salary contract versus essentially programmatic or AI content. Because it's probably not even AI, but if you're just like, there's a there's a station on SiriusXM that's just the Grateful Dead, and it just plays them the whole time. Like, I don't think you need someone making a $100,000,000 to, like, randomly play Grateful Dead tracks. Like, there's probably some Grateful Dead fan who manages that and picks the songs and orders them.
Speaker 1:But, like, that could essentially be pseudo random. Maybe one day you go through the the back catalog and then the new stuff and then you mix it up and then you play the hits or something. I don't even know if they have hits in that way. I know it's kind of a jam band. But wonder I wonder of their of their like of their content, of their tonnage.
Speaker 1:Is that the term? Tonnage is like the the amount of content on the network. I wonder how much of it is is driven by these high high dollar deals. And I wonder if they'll get a new a new host in the seat. I wonder who this generation's Howard Stern is.
Speaker 1:Maybe it's like Tim Dhillon or something, some irreverent comic I think
Speaker 2:the is as content is on demand Yeah. Fewer and fewer people are just turning on the radio or turning on the television and listening to whatever they, whatever just happens to be playing. Yep. And so if you take
Speaker 6:Go straight
Speaker 2:people that were subscribed to Howard Stern
Speaker 1:Yep.
Speaker 2:And were like, you liked Howard Stern. We're now just gonna play this other person through his channel. Yeah. They're just gonna be they're just gonna ask what's going on here.
Speaker 1:Yeah. I mean, certainly, if you have a specific car that has SiriusXM and it doesn't have Spotify and Howard Stern's new show is on Spotify because it's a podcast, Like, you might stick around on Sirius. Maybe they get someone new in the seat who's, you know, almost as good or can build a relationship, but it does seem like a challenge to fill that. But also, you know, it's a lot of money to pay. So clearly, it wasn't penciling out, so they had to move on.
Speaker 1:Anyway, x is now noticing when you take screenshots. Did you see this? I've seen this in other apps. It's usually pretty annoying, honestly. But when you take a screenshot, it triggers a UI element that says, hey, do you want to actually just copy the link to this post instead of taking our content elsewhere?
Speaker 1:So it's a little bit of a retention hack. I don't know if Nikita Beers in Nikita's involved in this. But it's it's it it's just like a classic UI thing. I wonder what the actual Makes sense. Benefit of
Speaker 2:this. Many people still just screenshot a post and share it in like a group chat.
Speaker 1:Well, yeah. Because post get deleted and then post it's like, oh, that person blocked me or that person is a locked account. And so the screenshot is just the universal language of like, you know, sharing information and content. And a of people still share links, but the like the the screenshot is super Lindy and I don't see it going anywhere. So Yeah.
Speaker 1:I mean the good thing is that this doesn't block your screenshot. Like your screenshot is still added to your camera roll, but then you're prompted to, hey, do you wanna actually share the link? I haven't actually run into this. I I don't I take a lot of screenshots of posts, but I do it on my computer, not on my phone. So anyway and Preston continues and says Nikita is going to look like a hero for putting features on Twitter that have existed on TikTok for a decade.
Speaker 1:I don't know enough about TikTok features to know what he would port over, but I know he's a student of algorithms and student of social apps, so I'm sure he'll find something.
Speaker 2:TikTok has is very smart about all these type all the different ways that con people are like diverting attention
Speaker 3:Yep.
Speaker 2:And hacking it. It would make a lot of sense for to just copy best practices from there. So I think this is a great good take.
Speaker 1:Yeah. Well, we have Mark Andreessen joining in about ten minutes. If you have questions for Mark, throw them in the chat and we'll try and get to them during our interview with him. Ray Sullivan says, once the summer is over and Mistral is back to work, I'm sure they're gonna be dropping some cool stuff. 1.6 k legs.
Speaker 1:How do you even fight that? It's that's so rough. Just Europe is is down bad. The meme in the memetic war. I
Speaker 2:would be very interested to to actually understand. We should have somebody on for mister Al about it. There are that the meme that that European founders and teams take off eight weeks in the summer is is extremely real. And and it's not
Speaker 1:always I mean
Speaker 2:A full eight weeks.
Speaker 1:We not have taken this summer, we've taken one day off. July 4. Yeah. And it's like extremely evident to what's going on over here in America. We run a media company.
Speaker 2:Yeah.
Speaker 1:And it's like you're in the most you're there. Yeah. You're in the most aggressive fight ever. Not not not to say that Mr. All's taking days off.
Speaker 1:I actually don't know about that company specifically. But but I have seen some some friends on the show proudly take time off.
Speaker 2:I know. I have I have friends that are European founders Yep. That have massive companies that are very successful.
Speaker 1:Yeah.
Speaker 2:And they, their businesses allow them to take time off. Totally. They can go. They can have a nice vacation with family, friends, whatever it is. Yeah.
Speaker 2:They can maybe just dial down meetings quite a lot. Good. And their businesses are gonna be fine. Probably still gonna have great quarters. They're gonna put up great numbers.
Speaker 1:Yeah.
Speaker 2:The issue with Mistral is you are competing with the entire world, an entire where if you're not at the frontier Yeah. You're not gonna get usage. Yeah. And so, I wouldn't be surprised if Mr. Al said, hey, no no Euro summer.
Speaker 2:Yeah. This summer.
Speaker 1:But we don't know. I mean, we don't know that they took a summer. We don't know That's I'm saying. Mistralt took time off. I'm saying I wouldn't.
Speaker 1:But, yeah. I mean, there there's also, like, the so there's the there's the facts of the matter. Like, you probably shouldn't take a huge vacation in the middle of the biggest fight over new technology in the past decade or two. Not that they are. But the the other interesting thing is, like, the vibes and the aura farming that comes from doing things that show that you're working extra hard.
Speaker 1:So this is the Elon, you know, taking a meeting really late at night with a journalist in the room, and then that gets out and you see the, oh, he really was sleeping, the picture of sleeping bag.
Speaker 2:Team having tents
Speaker 1:in Another example is Mark Zuckerberg. Meta dropped llama on a Saturday or a Sunday or something. And somebody asked, Mark, why'd you drop it on a Sunday? He said, because that's when he was ready. And it was a little bit rough because Llama wasn't, like, fully ready to the full extent, but it just showed that they were trying to move as fast as possible very clearly.
Speaker 1:Yeah. And then similarly, Sam Altman and the OpenAI team, they dropped that IMO stuff at, like, 2AM on a Saturday. And it was like, okay. There's like all this debate over, you know, were they inside the stadium? Were they running in the parking lot outside?
Speaker 1:You know? Was it
Speaker 2:signed off
Speaker 1:or it signed off or whatever? But you can't say that they weren't up late working. Like That's true. That's the one thing you can't say.
Speaker 2:You can't say
Speaker 1:they didn't
Speaker 2:have that dog.
Speaker 1:Yeah. Yeah. Exactly. You can't say they didn't have that dog with him. They might not have been nice with it, but they definitely had the dog in them.
Speaker 1:Okay?
Speaker 2:That's true.
Speaker 1:Like it wasn't very nice with it to you know kind of like frustrate
Speaker 2:Krishna here says the irony is that Mistral the meteorologic the meteorological event the company was named after mostly occurs in the winter and spring.
Speaker 1:That's wild. Non determinism strikes again.
Speaker 2:T. J. Parker says the best Amazon leadership principle is write a lot and it's not particularly close. Quote, leaders are right a lot. They have strong judgment and good instincts.
Speaker 2:They seek diverse perspectives and work to disc disconfirm their beliefs.
Speaker 1:Mhmm.
Speaker 2:Thought this was interesting. I thought it was a
Speaker 1:A typo.
Speaker 2:A typo.
Speaker 1:Because Amazon famously writes a lot WR.
Speaker 3:Yep.
Speaker 1:But this is r I g h t. They are correct a lot. Interesting.
Speaker 2:Stewart says, kinda true with VCs too. Feels like the best ones just have good sense broadly and pick really well. TJ says, yep. TJ Mhmm. Has been right a lot himself.
Speaker 2:Created PillPack sold it to Amazon for a billion dollars. So pays to be right.
Speaker 1:He's also been right a lot about his selection of timepieces. He's a fantastic collection of watches. Some of them are on display from time to time. Every now.
Speaker 2:Andrew Reed says, sector focused VC firm called Specific Catalysts.
Speaker 1:Okay. Andrew's been, you know, yeah. Yeah. He, yeah, he took Figma out at IPO. He's been on a generational run.
Speaker 1:He's backed, like, a dozen deck of corns. What potentially greatest allocator of this generation doing very great. Getting a little cocky on the timeline. Coming for general catalyst, making fun of their name. Coming for a 16 z.
Speaker 1:You remember this? He said, a 16 z, the 16 doesn't count the space in the middle. So he's taking shots from his high high perch. Heavy is the head that wears the crown Andrew. Be careful or else people are gonna start asking questions about why you don't own sequoia.com.
Speaker 1:And you don't want that to happen. Woah. You know this?
Speaker 9:Yes.
Speaker 1:No. But I think he's having fun. I don't think he crossed any lines. But it is funny because he's just he's just like, I'm I'm having a good time. Let me just fire off some some some jokes at the expense of my competitors.
Speaker 1:But
Speaker 2:got it. He's
Speaker 1:having fun. Is I love this.
Speaker 2:Yep. There's certainly plenty of VC firms formed to capitalize on a specific technological trend.
Speaker 1:For sure.
Speaker 2:And maybe Highly specific catalyst
Speaker 1:maybe we'll ask Mark to settle the debate. Is it a 16 z or is it a 17 z? Or is it like Wilmer Hale where Wilmer Hale, the law firm, two names, there's no space in between Wilmer and Hale. And so, if Wilmer Hale were to do the a 16 z thing and abbreviate it, they would be correct.
Speaker 2:Yep.
Speaker 1:So, you never know. Maybe Andrew Sonorowicz doesn't have a space in the middle.
Speaker 2:Post here from Dan Toomey. Quote, I don't do drugs. Lame, weak, beta, childish. I don't touch the stuff. Refined, respectable, aged wise.
Speaker 1:It does sound like, yeah, you have experience. I don't touch the stuff.
Speaker 2:Trump's line has never been big into that whole world.
Speaker 1:Yeah. Yeah. Yeah. It just it really really hits way way differently when you say that. So yeah.
Speaker 1:Kids, just say no. Just say you don't touch the stuff.
Speaker 2:It's great. Post here from Carl Rivera over Shopify. Being an angel investor is just a different way of subscribing to extremely expensive email newsletters. Yeah. You're oftentimes, you know, basically giving somebody 25 k for five to ten years of of monthly sends.
Speaker 1:Don't we know an angel investor that writes like $1,000 checks to get
Speaker 2:the Just email
Speaker 1:to get And LPs and funds too. And then gets all of that information. He's just like a master of information collection. Do. I
Speaker 2:had a portfolio company that I hadn't heard from for years. Mhmm. I I got updates for a while after And I I got pinged to sign some docs and they And I assume that the company was shutting
Speaker 1:shutting down
Speaker 2:and they got a massive
Speaker 1:Oh, acquisition. That's Yeah.
Speaker 2:Was it was it extremely pleasant pleasant surprise. Like normally if you just Yeah. The updates trail off, know, things aren't going that well. Every once in a while, you get a really nice surprise.
Speaker 1:That's great. Reads with Ravi says, great leaders think like farmers, think like a farmer. Don't shout at the crops. Don't blame the crops for not growing fast enough. Don't uproot crops before they've had a chance to grow.
Speaker 1:Choose the best plants for the soil. Irrigate and fertilize. Remove weeds. Remember, you will have good seasons and bad seasons. You can't control the weather.
Speaker 1:Only be prepared for it.
Speaker 2:Very nice Think like a farmer.
Speaker 1:I wonder farmer. Think like an aura farmer. Don't shout at the aura.
Speaker 2:Still need to we still need to have this debate with with Tyler around aura farming.
Speaker 1:Well, I'm trying to get him to coin it Cosgrove's law.
Speaker 4:I'm still writing it.
Speaker 1:You're still writing the post?
Speaker 4:I gotta get it perfect.
Speaker 1:Okay.
Speaker 4:Because the tweet in and of itself is aura farming.
Speaker 1:Exactly. Right? It is. Yeah.
Speaker 4:Kind of recursive in that way.
Speaker 1:Same with Coogan's law. Kugans law Exactly. Is a recursive Yeah. Yeah. I think this could do really well.
Speaker 1:This has one k likes written all over it.
Speaker 2:It's happening.
Speaker 1:And and and endless citations of Cosgrove's law. So we will work on that. Merrill from Graphite says it's a massive week for his customers. Figma IPO ed at 36,300,000,000.0. Ramp raised at 22,000,000,000 and Clay raised at 3,100,000,000.0.
Speaker 1:The future is being built with graphite. Congratulations to all those companies. Congratulations to graphite. You got an absolute murderer's row of clients. Congratulations.
Speaker 2:Line up.
Speaker 1:Well, we have Marc Andreessen joining us. He's live from the TVP and Ultradrone. Welcome to the stream. How are doing, Marc?
Speaker 3:Hey. What's happening?
Speaker 2:Great to see you.
Speaker 3:Yeah. You too.
Speaker 1:A lot. It's, it's a little bit of a slow news day, but, exciting stuff with GPT open source.
Speaker 2:It's not a slow August. I was
Speaker 1:It's not a slow August. We're glad. We were just reflecting that we've taken exactly one day off this summer that was July 4, and we're showing the Europeans how American companies work. American work. We're setting an example.
Speaker 1:And the and the and we have proof of work because we exist on the Internet, and you can see us live every day. So we're setting an example. How are you doing? How's your summer going?
Speaker 3:Fantastic. Going really well. So how long is it gonna be until you guys put up avatars that make claims that you're working hard all through the summer when it turns out you're on you're on the beach?
Speaker 2:You might have caught us.
Speaker 1:I think you'll know better than us as to when the technology gets there. We we we've been demoing some of the stuff. People have been doing a lot of deep fakes of us, and fortunately, all of them have been clockable. So it doesn't feel like a brand risk, but they're getting closer and closer. And I know that there's gonna be a moment where we have to say, hey, that's actually using our name and likeness to endorse something that we don't necessarily endorse.
Speaker 1:Can you please take that down? So we're we're approaching the the touring test, the uncanny valley. We're escaping I think the uncanny
Speaker 2:question, like looking back over the, you know, maybe ten or ten or fifteen years, was was what moments did you feel like there just was not a lot of action happening? Because this summer is just the pace from so many different teams has been absolutely insane. Everybody's, like, trying to keep up, and it didn't used to feel that way, at least from my point of view.
Speaker 3:So my my view that always is there's like these there there's this this disconnected, you know, kind of patterns or trends. There's there's sort of the the sort of day to day phenomenon where, like, engineers show up every day and they make things a little bit better. And then every once in a while, you know, you you get a technical breakthrough or or a new platform. And and and that process kind of this, you know, a kind of sawtooth kind of up to the right kind of process kind of plays out over time kind of regardless of what else is happening in the world. And so it it keeps happening through recessions and depressions and wars and, like, all kinds of crazy crazy crazy stuff that's happening.
Speaker 3:But basically, you know, the the technology keeps getting better. So there's there's kind of that curve, and then and then there's the the sort of enthusiasm curve and and the and then the adoption curve, you know, which is basically, like, when do these things actually show up in the world? And then by the way, when are people actually ready, you know, for the for for the new thing? Like, you talk to people who work on I'm sure you guys have talked to people who work on language models, they will tell you that they were surprised that ChatGPT was the breakthrough moment because they thought everybody already knew what these models could do for, you know, three years before that. So And they were, you know, they were shocked that it was the chatbot interface that made that made the thing go.
Speaker 3:And so so there there's somewhat of a sort of arbitrary disconnection between what's actually happening in the substance and then what what what what people are are seeing and feeling. And so it's just it's it's really hard to predict when these things pop. But also, if if you're in this day to day, it's it's really hard to tell, you know, when things are gonna be hot or not, because it doesn't necessarily map to how much the technology is improving.
Speaker 1:Yeah. We were just talking about that in the context of of Google's new world model. It's this like generative video game that you can kind of move around in and it feels like DeepMind is just absolutely crushing at the AI research frontier. They have the best world model simulator that you can walk around in. The question is like if they let another lab do the chat GPT thing and just get it out into the consumer three months earlier, they might wind up kind of chasing and trying to catch up if somebody actually figures out how to make it like a dominant consumer product.
Speaker 1:Now in the enterprise, it's more oligopolistic, but consumer seems to be winner take all. I guess the question is, like, how much value, do you place right now in the AI race to just, like, moving fast, breaking things, you know, dealing having, like, the thick skin to deal with, like, the safety constraints and all of the different stuff, obviously, not being irresponsible, but just speeding up the organization as much as possible. It feels like now is the time to really push on that.
Speaker 3:Yeah. Well, first of all, need to correct you. It's it's moving fast and making things. Making things. That's right.
Speaker 3:I I I don't even know where that is. I'm from. Yeah. I I have no idea what you're saying.
Speaker 2:Heard of it.
Speaker 3:I mean, technically, he
Speaker 1:didn't really break anything. I I think that's a good point. It really did just move fast and make things the first things it made were weird, but that was fine. And it failed, and it and it hallucinated a ton, but it didn't really break anything. I don't know.
Speaker 3:Yeah. I I believe that I believe in this case, total deaths attributable to to Jet GPT are still zero. Zero. So not not notwithstanding all of it notwithstanding all of the all the caterwauling. But Yep.
Speaker 3:Yeah. So look. I think the AI industry in particular has a very acute version of the of the of the sort of challenge that you identified with. And and, you know, and and I don't say this negatively, just an observation, which is that they're, you know like, in sort of a normal technology company, you've kind of got engineers who make products and then you've got, you know, kind of salespeople or marketing people who sell them. You know, in the in the AI companies, you have this third tier of, you know, the quote unquote researchers.
Speaker 3:Yeah. Right? And so well, you know, which has which has worked out incredibly well. I mean, the researchers have done you know, they've they've just done, like, amazing breakthroughs at at these companies. But, you know, the the the the the handoff, you know, there's not necessarily a clean handoff from the researchers to to the market.
Speaker 3:And so it kinda raises this question of, like, okay. Like, is there is yeah. Are these companies therefore kind of three, you know, kind of three segment companies where they have research and then they have product development, and then and then they have go to market? And I and I think that's a really open issue. I mean, if you know, Google's kind of a case study of this.
Speaker 3:You know, you alluded to DeepMind, but even more broadly, Google, you know, Google developed the transformer in 2017. And then they basically let it sit on the shelf. Right? Because it was a research project. They they didn't productize it.
Speaker 3:They were very worried about you know, from people I've talked to, they were very worried about the, know, brand issues and safety issue, you know, kind of all these all these they had all these reasons to not productize it. I talked to somebody senior who was there at the time who and I I asked them, you know, when when could you have had ChatGPT with GPT four level output if you had just got, you know, gone gone flat out starting in 2017? And they said by 2019. Yeah. You know, they they already knew how to do it.
Speaker 3:And then, you know, they've now caught up, but it took it took an extra five years five years to catch up. And and so I I think a lot of these companies kinda have that challenge. Elon, as usual, of course, is is provoking this question. Yeah. As I'm sure you guys talked about, but, you know, he he has now you know, with the next AI, he's now collapsed, you know he's eliminated the distinction between research and product.
Speaker 3:Yeah. And so, you know, of course, he you know, he's pushing as hard as he can. And I I think it's a it's a good question for a lot of these other companies kinda how hard they wanna push on actually getting these things in fully productized form out to the market.
Speaker 1:Yeah. Yeah. On on on Elon's, like, distinction, it feels like there is more research to be done, but it feels like we're we're entering, a new cycle of, you know, just focus on the engineering, focus on the deployment, the applications. Let's get all this technology out into the world. Let's reap all that benefit.
Speaker 1:And, yes, there will be a a different track of fundamental research that's happening somewhere but it's really really hard to predict. And so if you have something that's working, just double down and just go really aggressive on it. I'm wondering more on that but also on Apple's strategy. It feels like Apple's been kind of like, you know, people have been maligning them for not for missing the AI opportunity and Tim Cook's just there on the earnings call being like, look, we acquired a couple small companies and Seven.
Speaker 3:This
Speaker 1:year. Seven companies. But then
Speaker 2:Not all
Speaker 1:of it seems like they're taking more of like an American dynamism approach. Like there was news today in the journal that they that they're investing a $100,000,000 in American manufacturing. They're certainly doing stuff. They're just not chasing the, you know, the shiny tennis ball.
Speaker 2:Headline, $100,000,000,000 CapEx. So
Speaker 1:I'm wondering about your thoughts on when you have a, you know, when you have a platform, how hard is it to resist chasing the new shiny object? Is that the right move? Or are are there any other things that you think Apple should be, you know, changing their strategy on?
Speaker 3:Yeah. So, look, Apple's always had this, you know, very clearly defined strategy that, you know, Steve Steve and and Tim, you know, working together figured out a long time ago, which is, you know, they they I I forget the exact term, it's it's something like basically, they they invest deeply into the core of what they do. You know, they'll basically work internally on things for many years. They all they only actually release things when they feel like they're kinda fully baked. Yeah.
Speaker 3:Right? And and and so as a consequence, they they have this thing where and and and Tim says this. Right? You know, they're rarely first to market with new technologies. You know, they're they're they're more often in the category of what, know, Peter Peter Thiel calls last to market.
Speaker 3:Know, they're, you know, they'll they'll come out whatever three years later, whatever five years later. You know, there, you know, there were tablets for years before the iPad. There were, you know, smartphones for years before the iPhone.
Speaker 1:Folding phones. They're about to do a folding phone. It's like ten years into that technology. I'm sure if they do
Speaker 4:it, they'll The
Speaker 2:last mover the last mover.
Speaker 1:Yeah. Yeah. Yeah. Sorry.
Speaker 3:The the the last mover. And I I guess yeah. What what I would say is, like, look, that that clearly works if you're Apple. Right? Yeah.
Speaker 3:And so it it it clearly works if you're Apple. But I would say there's a fine line between that strategy and just and simply becoming obsolete. Right? Yeah. And so the the problem is, like, if you're not Apple, and you don't have all the other kind of super strengths and, you know, kind of now the market position that Apple has, you know, do you really wanna be a company?
Speaker 3:You you know, you're not Apple, do you really wanna be a company that basically sits there and says, yeah, the world's moving and we're very deliberately not gonna lean as hard as we can into it? And so I I I think there's a lot of survivorship bias in these kinds of strategy discussions where people look at the one company that's able to pull this off, and they don't look at the 50 other companies that are in the graveyard, you know, because they, you know, because because they didn't adapt. I mean, you know, all the other smartphone companies when the iPhone came out, they were like, oh, yeah. Well, we could do touch too. Right?
Speaker 3:You know, we'll just, know, we'll get to it. Right? And, you know, you know, they're gone.
Speaker 5:Yeah. What was the sound black thing?
Speaker 1:Bold. I I remember it was like an iPhone knockoff.
Speaker 2:What what do you think Yeah. You know, right now, people are are variety of, you know, shareholders are annoyed at Apple around their reaction to AI, LLMs. John's annoyed around just like transcription
Speaker 1:Yeah. Generally
Speaker 2:Basic. Super basic stuff. Actually. But it doesn't feel like the the core business is immediately threatened today. It feels like it's still on the horizon around these sort of like, you know, eyewear based computing, you know, potentially net new devices that we're that that we'll see from, you know, companies like OpenAI over time.
Speaker 2:But where do you, like like, how how real is the threat, you know, this year versus ten years from today and and kinda what's your framework?
Speaker 3:Yeah. Well, look, mean, think the biggest ultimate danger I mean, the biggest ultimate danger is very clear, is just like at what point do you not carry around a pane of glass in your hand that, you know, call the phone, you know, because other things have superseded it. And then, you know, like, everything, you know, everything becomes obsolete at this point. So there will there will come some time to make sure when we're not, you know, carrying phones around and we'll we'll watch movies where people have phones and we'll be like, yeah. Look at look at how primitive they were.
Speaker 3:Right? Because because we'll have moved on to other things and whether those things are eye based or, you know, you know, the other kinds of wearables or whether it's just kind of, you know, computing happening in the environment or just, you know, entirely voice based or, you know, who knows what it is. But, you know, there will come a time when that happens. You know, is that time three years from now because there's like some, you know, huge breakthrough, you know, from from some company that figures out the the the product that obsolete the phone right away, or is that twenty years from now because the phone is just, you know, such a standard platform for everything that we do in our lives and everything else, you know, kinda remains a peripheral to the phone. Mean, that, you know, that's, you know, that that's the game of elephants that's playing out there.
Speaker 3:You know, obviously, I think, you know, I I think it's highly likely that we'll we'll have a phone for a very long time. Yeah. Having said that, it is it is exciting that there are companies that are going directly at that challenge. And, you know, who whoever cracks the code on that will be the will be the next Apple. And by the way, that that may in the fullness of time be Apple itself.
Speaker 3:You know, they they they may be the company that figures that out.
Speaker 1:Yeah. I remember being in a board meeting at Andrews and Horowitz maybe a decade ago or something, and Chris Dixon showed me the HoloLens and I was like, okay. We're one year away from this band everywhere. And and I feel like today I'm still in the like, yeah, VR, it's definitely one year away. The next quest I'm gonna be wearing daily.
Speaker 1:And and it feels like we're always there, but it does feel like Apple did a lot of work on the on the fundamental, you know, pixel density of the resolution of the display. And then Meta's been doing a ton of work on just getting it light and affordable. Like, it feels closer than ever, but, you know, you you always gotta wait until you see the churn numbers until you really call the game. Right?
Speaker 3:Well, you say the same, but, you know, think that's true. But it you'd say, you know, I'm I'm on the on the meta board, so I'm,
Speaker 1:you know,
Speaker 3:kind of a dog hunt on this one. Like, the the Meta microphone, integrated speaker. Yep. You know, that's a very interesting platform. Know, the watch clearly works by the way, which Apple, of course, you know, has played a significant role in making happen.
Speaker 3:You know, that now sells in in in huge volume. Yeah. You know, so that's the second data point. And then, you know, look, I think these, you know, these these I I think some form of AI pin is gonna Yep. I also think head you know, headphones are gonna get a lot more sophisticated which is already happening.
Speaker 3:Yep. And and so, you you know, you do have these, you know, kind of data points coming out and then yeah. Look, the the the the trillion dollar question ultimately is are are these are these peripherals to the phone. You know, which is what they are today, or are these replacements for the phone? And, know, we we yeah.
Speaker 3:I would say we, you know, we have we allowed we I think we have a lot of invention coming both from new companies and from incumbents who are gonna try to figure that out.
Speaker 1:Yeah. I always think about the value of, like, narrowing the aperture on these new technologies. Like, with with the the meta Ray Bans, I feel like the fact that they aren't also trying to be a screen is actually a feature, not a bug. And I always go back to the iPhone. Like, it was first and foremost a phone.
Speaker 1:And people bought it because it could make calls, and then it could make text messages, and then it was an iPod. But I do you disagree with that? Please.
Speaker 3:Well, you you guys Adam, you you guys might be too young. The the first iPhone actually was a bad phone.
Speaker 1:How so?
Speaker 3:Don't you guys for the first two years, I couldn't reliably make phone calls.
Speaker 1:I I had Do remember?
Speaker 3:I had, like, a third
Speaker 1:one and a friend had one, but I feel like it was still, like, people were carrying cell phones and that was the at least of the expectation. But, yeah, I mean,
Speaker 8:I guess
Speaker 1:you're right.
Speaker 3:So for the for the for the first year, it was a classic Apple story because the first for the first two years, the thing couldn't make phone reliably make phone calls, and then it turned out there was an issue with the antenna and with with how you held it, there was a that Steve got the email. Yeah.
Speaker 2:Heard it.
Speaker 1:And you would and you would disconnect it. Yeah.
Speaker 3:Based on how you held it and somebody emailed this is when Steve would would respond to emails from random people and somebody emailed Steve saying, if I, you know, hold the phone this way, it doesn't make phone calls. He's like, well, don't hold it that way.
Speaker 5:That's great.
Speaker 3:Yeah. Right? Yeah. So so even there, it was like yeah. Okay.
Speaker 3:And people, you know, people forget. It took like five years for the iPhone to find its footing. It took like two years to get the I remember also the original iPhone didn't have it didn't have broadband data. Yeah. Was on it was on the the old two g.
Speaker 3:One g. It was called the AT and T Edge Network. So it didn't have broadband data and then of course, didn't have an app Right? Was completely locked down. Right?
Speaker 3:So the challenge
Speaker 2:is the challenges for Apple now is that people are so used to perfection with the device that launching a product that isn't perfect, like is embarrassing. Right? Like you look at the Vision Pro and it's like, the battery is big. Steve would have hated this. Right?
Speaker 2:Like how he never would have shipped this and that being constrained and and not being able to innovate because you're tied to this like impossible standard of being on whatever generation 17 of the iPhone and perfecting every element is Yeah. Is a real challenge.
Speaker 3:So I would say there's a corollary to that. One of the things I've observed over the years is I I think LG products become obsolete at the precise moment they become perfect. And and and did you find what I mean what I mean by perfect basically is, like, yeah, it's like the perfect idealized complete product. Like, it does everything you could possibly ever imagine. Everything a customer could imagine, everything you as the technology developer can imagine, it's absolutely perfect.
Speaker 3:And there there's there's been tons of examples of this over the last fifty years, where it's like the absolute perfect permanent it it seems to be the permanent version of that product, and then it just turns out that's actually the point of obsolescence because it means creativity is no longer being applied right into that platform. You're just like, there's just nothing else to do. You're just like, you're you're you're done. Right? The product has been realized.
Speaker 3:And then and then the cycle is what happens to your point. The cycle is other people come in with completely different approaches, completely different kinds of products that are broken and weird in all kinds of ways, you know, but are but are fundamentally different. And so, you know, that is one of the time honored traditions. And, you know, one of the, you know, one of the, you know, things you could say about, you know, Tim is his, you know, his willingness to kinda break the mold of Apple only ships for perfect products, you know, be willing be being willing to ship the, you know, the Vision Pro, you know, you know, shows a level of determination to kinda stay in the innovation game.
Speaker 1:I like that.
Speaker 3:Which I think is very positive.
Speaker 1:Yeah. Yeah. Yeah. Yeah. That's great.
Speaker 2:Updated thinking on open source since we last There's there's a lot that's been
Speaker 1:OpenAI is an open source company here.
Speaker 2:Yes. OpenAI is open again.
Speaker 1:Yes.
Speaker 3:Yeah. Yeah. Look. Very encouraging. You know, a year ago, I was very you know, I was I was getting very distressed about open you know, whether open source AI was gonna be allowed.
Speaker 3:Yeah. Right? It was even gonna be illegal. Yeah. And so I think, you know, we're basically through that at this point.
Speaker 3:Right. I was gonna say, we're through that in The US. Yep. You know, we'll we'll see about we'll see about the rest of the world. And and then, look, know, The US China thing is obviously a big deal, but it you know, I think it's been positive for the world that China has been been so enthusiastic about open source AI coming out of China Mhmm.
Speaker 3:Which has been great. And then, yeah, look, OpenAI leaning hard into this, you know, and releasing what, you know, what they did as I as I think fantastic. Both because of of what they released, which is great, but also just the fact that they are now, you willing to do that. And then Elon reconfirmed overnight that he's gonna, you know, open source you know, start open sourcing previous versions of Grok. And so So we, you know, we we we we seem to be we seem to be in the timeline where open source AI is gonna happen.
Speaker 3:You know, right now, you know, which I think what you would say is it it kind of lags the leading edge proprietary implementations by, you know, six months or something like that. Yep. But but I think that, you know, that's a good if that's the status quo that continues, I think that would be a very good status
Speaker 1:What are the rough edges that we need to kinda sand down when we're thinking about, Chinese open source models specifically? Is it we need to do some fine tuning on top of them to add back free speech, or do we need to watch for backdoors? Say, it's phone and home if it runs into this specific thing. Like, the Chinese open source thing, it was remarkable because I feel like it really does accelerate the pace of innovation because everyone gets to see, oh, this is how reasoning works. I think that's great.
Speaker 1:At the same time, it made me very it made me much more appreciative of AI safety research and capability research and actually being able to interpret what's going on and and say definitively, this model is gonna behave weird in this weird way, like the Manchurian candidate problem. Haven't found any of that, but it certainly seems like something we'd wanna keep an eye on. But in from your perspective, like, what what are the what are the risks that we need to be aware of going into a world where China is really pushing hard into open source?
Speaker 3:Yeah. There's two there's two, and you identified them, but let's let's let's talk about both of them. So the phone so the phone home thing is the is the easy one, which is you can put up you know, you can packet sniff, you know, a network and you can tell when the thing is doing that. Yep. And you and and plus you can go in you can go in the code and you can see what it's doing that.
Speaker 3:And so you can validate you can even validate that that's either happening or not happening, and I think that, you know, that's important. But, you know, I think people are gonna people are gonna are are gonna figure that out. You you you can kinda gate that problem practically. Yeah. The the the the bigger issue is, we we have this term in the field, right now called open weights.
Speaker 3:And open weights is a loaded term. It it uses the open term from open source, but, of course, with open source, the thing is you you can actually read the code. Mhmm. You know, with open weights, you have, you know, just a giant file full of numbers as as you said that you you can't really interpret. And then what you don't what you don't have what what most what most of the open source open weights models don't have including, you know, DeepSeq specifically, what they don't have is they don't have open data.
Speaker 3:Right? Or open corpus. Right? So you you you can't actually see the training data that went went into And, of course, you know, most of the people building models are kind of obscuring what that, you know, what that training data is in various ways. And and so when you get an open weight model, you know, the good news is the the the the software source is open.
Speaker 3:The good news is you can run it on machine. You can verify that it doesn't phone home, but you don't actually know what's happening inside the weights. And so I I think that that is going to be a bigger and bigger issue, which is like, okay. How the thing behaves? Like, yeah, what what has it actually been trained to do, and what restrictions or directives has it been given in the training, you know, that are embedded in the weights that that that you need to be able to see.
Speaker 3:You know, this is I would say this is coming up as sort of, I would say, a global issue, you know, which, you know, we worry about when these models come from China. Other countries worry when these models come from The US. Right? Which is right. So one of the one of the phrases you'll hear when you talk to people kind of outside The US is kind of this this phrase people kicking around, which is not my weight, it's not my culture.
Speaker 3:Okay. Right? Right? Or or by the way, for that matter, not my weight, not my laws. Yeah.
Speaker 3:Right? Which is like, okay. Like, what actually is this thing going to do? Right? And to your point, the Chinese models, for example, might, you
Speaker 1:know,
Speaker 3:never criticize communism or something. Sure. I can tell you, the American models have all kinds of constraints also. Yeah. Right?
Speaker 3:Implemented, you know, usually by a very specific kind of person, in a very specific location in The US.
Speaker 2:Yep. Yep.
Speaker 3:And so, you know, I think that that this is a this is a general issue, and and we're and we're gonna to see basically people's tolerance levels, being willing to run open weights models where they don't fundamentally have access to the data. And then correspondingly, I think what we'll see is more open source developers also doing, open corpus open data so you can see what's actually in them.
Speaker 1:Yeah. Obviously, open source is very important in terms of just distributing intelligence broadly, giving people the ability to run their own models and and really fine tune them and have control. There's also the big push just to make frontier models and high capability models free. One model is you charge for the premium, you give the free away. It's a freemium model.
Speaker 1:That's what we're seeing at most of the labs right now. There's also this kind of specter on the horizon of potentially putting ads in LLMs and what that would do to the world. Jordy got in a little dust up with Mark Cuban on the timeline deciding whether or not it would be a net good to put advertising in LLMs. What might happen that might be bad there? What do
Speaker 2:you Yeah. Have My my point broadly was Yeah. That ads have been an incredible way to make a variety of products and services online free and just saying like default, there's no ads would would potentially, you know, be incredibly destructive. But, yeah, curious your framework.
Speaker 3:Yeah. So I should start by saying, like, whenever I personally use Internet service, I always try to buy the premium version of it that doesn't have ads. Right? And so if if I if I can, like, live personally inside an ad free universe and pay for it, like, that's great. And I'll I'll free I'll freely admit, you know, whatever level of, you know, hypocrisy or incongruence, you know, kinda kinda kinda kinda results from that.
Speaker 2:No. The point is choice. The point is choice.
Speaker 3:Well, the point is right. No. The point is exactly what you said. It's affordability. So the the the problem is if you really wanna get to if you wanna get to a billion and then 5,000,000,000 people, you you you can't do that with a paid offering.
Speaker 3:Like, it's just you you at any sort of reasonable price point, it's it's just not possible. The, you know, global per capita GDP is not high enough for that. People don't have enough income for that, at least today. And so if if you wanna get to you know, if you want the Google if you want the Google search engine or the Facebook social app or the whatever AI, you know, frontier AI model to be available to 5,000,000,000 people for free. You you you need to have a business model.
Speaker 3:You need to have an indirect business model and and and as is the obvious one. And so I I do think if, you know, if if if you take some principle stand against ads, I think you unfortunately are also taking a stand against against against broad access just in the way the world works today. And then and then, look, the other the other really salient question is, you know, the same question that the companies like Google and Facebook have been dealing with for a long time, which is, are ads purely destructive or negative the user experience, or are they actually if done properly, are they actually either neutral or even positive? Yeah. Right?
Speaker 3:And and this was something that, you know, Google, I think, their credit figured out very early, which is, you know, a a a well targeted ad at a specifically relevant point in time is actually content. Like, it actually enhances the the experience. Right? Because it's an obvious case. You're searching on a product.
Speaker 3:There's an ad. You can buy the product. You click to buy the product. That was actually a useful piece of functionality. And so, you know, can you can you have ads or or or other things that are like ads or look like ads, know, different different kinds of referrals, you know, mechanisms or whatever.
Speaker 3:Can you have them in such a way that they're actually additive to the to the product experience? And you can just like with searching with social networking, you could imagine lots of examples of that. People will, you know, the people will, you know, they'll whine or hold up in a lots of different ways. But I think it you know, I think that hasn't been a bad outcome overall. And I think that I think it's entirely possible that that's what what happens with with with these models as well.
Speaker 2:Yeah. So kind of similar kind of question, what what should be legal kind of trying to create legal frameworks on on a number of issues with AI. There's been a number of IP cases that have been working their way through the courts. What can labs use to train models, etcetera. There's been some good outcomes recently.
Speaker 2:Sam also was talking about how a lot of people are using AI as like a confidant, like a, you know, a friend, things like that. And he mentioned that currently your chats are not privileged. They can be used in in in a in a lawsuit or or other situations. How how optimistic are you that our sort of legal system in The US can get some of these issues right where maybe it can't just be, know, total free markets kind of lawless, whatever goes?
Speaker 3:You know, so in the case of training data, I think that there I mean, there's a bunch of these copyright, you know, kind of lawsuits happening right now. There's, you know, the big New York Times opening I one and there's, you know, been a bunch of others. Yeah. I I think in that but for that particular problem, my guess is that problem ultimately has to be solved through legislation. It's it's it's ultimately a legislative question.
Speaker 3:The reason is because it goes to the nature of copyright law itself, you know, which which is legislation. And and and, of course, know, the the the content industry is already claiming that, of course, know, using using copyrighted data to train, you know, without permission or without paying is is is sort of, you know they they believe illegal on its face, you know, due to violation of copyright law. The the counterargument to that, which, know, which we believe is, well, it it's not copying. Right? There's there's a distinction between training and copying.
Speaker 3:Just like in the real world, there's a distinction between reading a book and copying the book, you know, as a person. And so there there there's gonna need I I think, you know, the courts are trying to grapple with that. There's a whole bunch of cases. There's jurisdictional questions. You know, probably, ultimately, congress is gonna have to figure out a you know, figure out an answer on that.
Speaker 3:And by the way, the president has kind of, you know, thrown down that gauntlet in his I think the speech he gave last week or two weeks ago, you know, where he said that, you know, Washington probably needs to deal deal with that as an issue. So that's one. On the on the on the on the privacy thing, I I think that one that one feels like it's a supreme court thing to me. It feels like that's the kind of issue set in supreme court. And the in other words, like, for example, your chat transcripts are are considered your property and whether they're protected against, you know, warrantless search and seizure.
Speaker 3:Mhmm. And and the observation I would make there is if you look at the march of technology over so the the constitution has, like, very clear, you know, fourth, fifth amendments, you know, very specific rights around the, you know, the things that are yours, you know, such as, you know, your home, you know, being in your home, you know, by the way, the thoughts in your head. Right? You know, that the government can't just, like, come in and take. They can't, you know, they can't just come in and search your house without a warrant.
Speaker 3:Mhmm. You know, they can't, like, you know, put you in a jail cell and beat you until you fess up. Like, you know, there are there are you know, we we have constitutional protections against the government being able to basically, you know, take information, you know, fundamentally, you know, as well as possessions. And and then basically what happens is every time there's a new technology that creates a new kind of sort of, you know, thing that you own, you know, thing that's yours, thing that you would consider to be private, thing that you wouldn't want the government to be able to take without a warrant, you know, out of the gate, law enforcement agencies just naturally go try to get those things because they're ways to solve crimes and, you know, they it it feels like that that's a legal thing to do. And then, basically, the courts come in later and they, know, rule one way or the other and basically say, no.
Speaker 3:That that actually is also a thing that is protected against, you know, warrantless for example, warrantless search, you know, warrantless wiretapping. And so I I I feel like, you know, this is the latest of probably, I don't know, 20 of those over the last hundred years. And, you know, I I don't know which way it'll go, but I think it's it's gonna be a a key thing because as you know, people are are already telling these models, you know, lots lots of things that they're, you know, that that that are very personal.
Speaker 1:K. Lightning round. Quick questions. We're letting you get out of here in a couple minutes. We're in this age of spiky intelligence.
Speaker 1:Models are great at some things and then terrible at others. Where are you actually getting value out of AI right now? Where is it falling down for you? Where are you how are you using AI day to day?
Speaker 3:Yeah. So I I I have two kind of, I don't know, bar barbell approach. One is for for serious stuff. I love the deep research capabilities. Yeah.
Speaker 3:And so and I'm I'm doing this in a bunch of models, but, like, the the ability to basically say, I'm interested in this topic. You know what? I just I just don't like write me a book. And I, you know, I I'm kinda hoping for the longest book I can get. I always tell it, like, longer go longer, more sophisticated.
Speaker 3:You know, but the the leading edge models now, they're getting up to, 30 page PDFs, you know, that are, like, completely well formulated, you know, basically long form long form essays. You know, it's just like incredible richness and depth. And, you know, if it's 30 pages today, I'm sort of crossing my fingers that it'll get to, you know, 300 pages coming up here in the next few years. And so I I you know, I'm able to basically have the thing generate enormous amounts of of of reading material with just like, I think, incredible richness and depth and complexity. And then and then on the other side of the barbell is humor.
Speaker 3:And I've I've posted some of these to my my ex ex feed over over the last couple of years, but I think these models are already much funnier than people give them credit for.
Speaker 1:Really?
Speaker 3:Yeah. I think I think they're they're actually quite highly entertaining. While ago Specific I suppose I had
Speaker 2:specific formats like, know, the the chatting back before. Mark Andreessen Yeah. You know, that that format.
Speaker 1:To take a dip in my pool, in my office.
Speaker 3:They're really good. So they're really good at green text. Yep. That that works really well. But the the the for some reason, the ones I find hysterical are the I haven't write screenplays, you know, for like TV shows or or or plays or movies.
Speaker 3:And I I posted I had it write a new season of the HBO Silicon Valley, you know, set ten years later.
Speaker 6:Yep.
Speaker 3:And I had it write, like, an entire yeah. I had it write, like, ten ten scripts for complete season. And, course, I just said, you know, make it like Silicon Valley except, you know, it's happening at at it is it's in 2021, it kinda peak And and I thought it was just I think it's just you know, I'll sit there at two in the morning and just, laughing my ass off at how funny this thing is. And so I I think these things are actually are actually already, like, extremely funny. They're extremely entertaining when they're when they're, you know, when they're used in that way.
Speaker 3:And I I I do I I do enjoy that a lot, and I generate a lot of those, that I that I don't post. Stay in the
Speaker 1:group chats.
Speaker 3:It's it's probably a good idea.
Speaker 2:They're your property.
Speaker 1:Yeah. Hopefully, the fourth amendment holds on these. Yeah. It's great. I have one last question.
Speaker 1:Go
Speaker 2:for it,
Speaker 1:and then I've got one more. How do you get a job as a venture capitalist in 2025?
Speaker 3:So I think I mean, look, the the best way the best way to do it is to have a a track record early as somebody who is, like, in the loop specifically on new product development. And so somebody who, you know, be be, like, deeply in the trenches at one of these new companies in one of these spaces, you know, participate in the creation of a of a great new product and and a and a great new company and, you know, really demonstrate that you know how to do you know, there's there you know, there are there are great VCs who have not done that, but, you know, I think that is sort of a foundational skill set Mhmm. Know, for working with the kinds of founders that that that you wanna work with who are gonna who, you know, are gonna want you to have, you know, kind of very interesting things to say on that, as I think that, you know, still the the the best way to do it.
Speaker 1:Yeah. Like, feel the growth. Be immerse yourself in the growth, the the Yeah. The the the aggressive growth environment, and then you'll be able to identify it when you see it from afar.
Speaker 3:Yeah. That's right.
Speaker 2:Last question for me. State of m and a in your mind, how are you advising, you know, companies where where you're on the board or just the portfolio broadly around what they should expect now and and in the near future?
Speaker 3:You mean in terms of where where they can get things approved?
Speaker 2:Or Basically. Yeah.
Speaker 3:Yeah. Yes. So, look, approval still approval is not a slam dunk. There was a there was a, you know, there was a buy I I just saw there was a medical device company this morning, you know, where the the acquisition was not allowed by the FTC. So, you know, like, there there is still scrutiny.
Speaker 3:It's, you know, it's obviously a very different political regime in Washington, but, know, this is this is not an minute you know, by by their own statements, this is not an administration that believes it's in total laissez faire. Mhmm. M and A and it definitely wants to, you know, in in in their view, maintain a a very healthy level of of market competition.
Speaker 2:Yeah. How many do do you expect do you expect certain companies to be negatively impacted by the Figma story? Right? You have this deal gets blocked, successful, you know, IPO. Lina Khan is taking a victory lap.
Speaker 2:You know, many people are responding and and joking saying, you know, someone Lena cuts off the arm of a pianist and they endure and can create a masterpiece and then That's great. And so I expect and and then you look at the example with, you know, Roomba, I think it was, where where Roomba had a deal with Amazon. It was blocked and and
Speaker 1:Fell apart.
Speaker 2:And the company has
Speaker 1:just been
Speaker 2:shambles ever since. So my concern is that people look at Figma and say, you should be independent. You just figure it out.
Speaker 1:Nothing can go wrong.
Speaker 3:Yes. Yeah. I mean, Scott taking a victory lap was very disconcerting. And and for exactly the reason you said, which is survivorship bias. Right?
Speaker 3:Which is you you you pick the one that worked out and then and then would, know, it's the it's the airplane. The red dots, the airplane You know, you you you ignore the 50 that are in the ground, that you've never heard of. And so that that was very disconcerting because that, you know, it's sort of the central planning fallacy, which is, like, we make centrally planned economic decisions. We have one example. You know, it's like in Europe.
Speaker 3:It's like, yeah. Well, the the bottle caps actually don't fall off the bottle. Right? Like, you know, it works. Right?
Speaker 3:It's like, okay. But do you but do you wanna live in do you wanna live in an economic regime in which that, you know, the government has dictated bottle cap design? The answer is clearly no. Yep. Because the downside consequences Or
Speaker 2:even even looking at that, you know, the Chinese model which is, you know, people can say they're picking winners but to get to maybe picking a winner, you have this intense bloodbath of competition where, you know, teams need to rise to the top and sort of prove themselves before they get any of that real, like, you know, meaningful state benefit.
Speaker 3:Yeah. That's right. And so, you just you just yeah. You just you just have this adverse selection, survivorship bias thing where you just you you don't pay attention to all the collateral damage. So I I I I do think that mentality is, like, super super dangerous.
Speaker 3:And so yeah. Look. I I think companies just have to be very thoughtful about this, both acquirers and the inquiries. You know? And was you know, the big thing is if structured on on the one hand?
Speaker 3:And then two is, yeah, look, do you have the kind of company culture that's gonna be able to withstand that? And and and is your business, you know, strong strong enough to be able to be able to get through that? And it's it it it is a real risk and something worth, you know, taking very seriously.
Speaker 2:Yeah. And that's that that's why it felt emotion we were
Speaker 1:at Yeah.
Speaker 2:NICEE last week. It felt emotional emotional this that that the the Figma team was was able to, like, effectively just, like, restart the business and say, like, we're we're we're taking this all the way.
Speaker 3:So If if you talk and the way you think about it, if you talk to any really successful company, what they'll tell you is, yeah, over the years, we have these, like, crucible moments in which, like, we almost died. Right? But we, like, pulled together and we pulled it off and then that became, like, you know, one of these central kind of mythical events in the history of the company that we always refer to and, like, my god, we got through that and we're so strong and tough and we've been forged in fire and now we can do anything. And it's like, yeah, that's great. And then there's 50 other companies that have those personal moments blew up and died.
Speaker 3:Right? And so Yeah. That's right. Yeah. Like, it's it's all of the, quote, lessons learned on this stuff, they're all conditional on on, like, survival.
Speaker 3:And so they they they these things need to be taken incredibly seriously, you know, which which the great CEOs do.
Speaker 1:Yeah. Well, thanks so much for joining. We'll let you get back to your day.
Speaker 7:Are Oh,
Speaker 1:it fun. Five minutes over. Next time, we have to book five hours because this is fantastic. I got
Speaker 4:Let's do the first of the way
Speaker 1:through twenty four hour TV. Yeah. We would love to have you again. Married a lot. The rest of your day.
Speaker 1:We'll talk to you soon, Mark.
Speaker 3:Have a
Speaker 1:good day. Bye.
Speaker 3:Cheers. That's good. Thank you, guys.
Speaker 1:Thank you. Up next, we have Harley from Shopify coming in the temple of technology, the fortress of finance. The capital of capital, welcome to the stream. Harley, get that gong ready, Jordy. What happened?
Speaker 2:Talk to
Speaker 1:update, Harley. How you doing?
Speaker 8:The update's good. I just finished watching you guys with with Mark.
Speaker 6:It was it
Speaker 8:was an amazing interview.
Speaker 1:It was really He's fantastic. Before
Speaker 8:I get into Shopify Please. You guys you guys mentioned the emotion of being at the NIC with Figma Yeah. Yesterday, I think. Right?
Speaker 1:Yeah.
Speaker 8:So we we are 41 now and maybe forty two quarters post IPO. Yeah. I think it's emotional for anybody. I mean, obviously, that story is incredibly emotional because of what happened with with, you know, with Adobe and all that, but I think it's it's I think it's emotional for anyone who who goes there. Although I I do think, you know, you'd said that is is that going to, you know, create some momentum for more companies to do it independently?
Speaker 8:I don't know if that's gonna be the main catalyst or not, but I said this last time when I was on on your show. I I wanna say it again. For those companies that are out there, there is this perception that, like, the public markets are something to avoid as much as possible. I I you know, 42 quarters in, let me just say, like, one of the best things Shopify did was was was go public. It's it's made us a better company.
Speaker 8:It's allowed us to to be a lot more transparent. I think there's, like, this hygiene thing that that these quarterly the quarterly reports do. So I I don't know I don't know how to where else to do that other than a show like this, but this is my endorsement that if your company is ready, the team is ready, the business is ready, accessing the public markets should not be this thing that is like, if I don't get acquired, I I guess I'll have to take the IPO route. It's been an amazing experience for us.
Speaker 1:That's awesome. Forty one quarters. Yeah. Amazing run. Advice for Dylan Field.
Speaker 1:How can he make the first forty one quarters of Figma, their public debut a success?
Speaker 8:Oh, wow. Oh, I know Dylan is an amazing founder, great, great entrepreneur. So I don't know if I much need each other than say that, you know, we looked at the we looked at the IPO as sort of, like, we we actually called it game day, like we were graduating from the the minor leagues to the major leagues. Yep. And I actually think that type of that that metaphor actually works really well.
Speaker 8:It's it's not like you're done. In fact, it it just, you're just sort of graduating to the next step. The thing that I think on the earnings call today, spent a lot of time talking about this and getting to the results in a moment. This idea of providing these breadcrumbs to the public, to to the street, to your you know, you have this huge book of investors, including retail, but you have these 10 or 20 funds that if you're lucky, and we've been lucky, I assume Dylan will have the same fate, they kinda hold your stock, you know, for a very long time. And making sure you leave enough breadcrumbs so that they can anticipate where things are going to provide some consistency, I think, is really, really important.
Speaker 8:So I don't know. Like, becoming a trusted version of Figma in the public markets is a much better way to, I think, do things than just becoming like a different version of Figma. Think the reason that Figma is so successful is because they understand their culture, their product, their customer base. I think this is just sort of the next phase for them as opposed to like, okay, we're done. Let's now change the company, become something different.
Speaker 8:And in sort of this era of founder led companies and founders being allowed and and permissible to run their companies over the long period of time, I think that works much better.
Speaker 2:One thing that stood out to me is Figma was launching new features on the day of the IPO It was very cool. Which to me just sent this signal that we're still the same company that Totally. Shared like
Speaker 1:Dylan was replying to customer support posts on the on the IPO day.
Speaker 8:It's it's amazing. I mean, that that is, like, we we we do the same thing. There's there's something different about founder led companies. Yep. And with that, less about Figma, more about Shopify.
Speaker 8:Yes. Okay. So, obviously, you know, we had our results this morning.
Speaker 1:Give us the news.
Speaker 8:The news is q two GMV was 87,000,000,000, that's up 31%.
Speaker 1:Let's go.
Speaker 3:Revenue was 2,700,000,000.0, free
Speaker 8:cash flow was 422,000,000, is 6% of revenue. So back to the consistency point, we've now had 11 consecutive quarters of positive free cash flow, eight consecutive quarters of double digit free cash flow. And it's you know, this is Shopify operating on all cylinders. Amazing. And and, yeah, I I think that it was it was a really good quarter.
Speaker 8:I think there was, like, a a bunch of these interesting uncertainties that the Street had, tariffs, de minimis, macro. But our our merchants, you know, did disproportionately better than the overall e commerce market, which is really cool. And then I got to announce some, like, amazing brands, you know, Michael Kors, Canada Goose, Starbucks, these incredible companies that are now coming to shop. Like Burton came, Miele came. Amazing.
Speaker 8:So really cool to also be able to talk about some of the big brands that are now joining Shopify too.
Speaker 2:Break down some of those concerns kind of one by one, I'm sure you did, but but tariffs, de minimis, you know, the market broadly, how have you got how how have you guys been kind of approaching that? And and
Speaker 1:Yeah. How did you how do you think you got through it? Is it just that it was always, you know, kind of, like, a lot of these a lot of these political changes, it feels like really crazy and then it rolls back and it's actually fine. Is that the right narrative? Or is it the actual, like, adaptation and agility of both Shopify and the merchants to actually work around a changing environment?
Speaker 2:I mean, a team effort too because each individual brand has to say, hey, we're facing some headwinds here
Speaker 1:Totally.
Speaker 2:And we have to figure this out. We have to navigate this and, you know, just find a way. Yeah.
Speaker 3:Yeah.
Speaker 8:Yeah. It it actually carries all the way to consumer because the consumer also is like, well, what if I lose my job? If I, you know, have less disposable income? Now do I have to select? Do I have to make choices and trade offs of what I buy, what I don't?
Speaker 8:I mean, you know, just to kind of at the high level, we are not seeing signs of a slowdown. I'll just start with that. We can look at data actually through early August. We're August 6 today, so not obviously, not half the month, but certainly the August. Generally, we're not seeing any slowdown.
Speaker 8:The factors we monitor at Shopify are consumer spending, household savings, tariffs, foreign exchange trends, and then supply chains. And generally, we're not seeing nearly what what I think a lot of us were were concerned about. The other thing that I think is is interesting is that I mentioned, like, you know, Starbucks and Burton Canagoose joining Shopify. One of the interesting things that happened that I don't think we fully I didn't certainly didn't anticipate this is that because of this uncertainty, a lot of these bigger companies were beginning to be like they were rethinking whether or not their tech stack was future proof. Like, am I spending too much money on technology?
Speaker 8:Is my technology partner in in commerce, in our case, platform? Are they future proofed? Like, I'm hearing all you know, you think about, like, you know, think about, like, a metaphorical board meeting at one of these very large retailers. Someone is gonna raise your hand and say, how are you guys thinking about AI inside the company? And then what about, like, agent to commerce?
Speaker 8:And so I think one of the neat parts for us is act as as a as a tailwind has been that a lot of the big brands that historically said, we we we our stack is not great, but we're fine with it are now think are now looking and saying, like, alright. This is ridiculous. It's, like, duct taped together. It's not future proofed. We're not able to you know, we don't even like, our provider doesn't even know what a gen to commerce is, and that's leading a lot of brands to to come to Shopify.
Speaker 8:The thing that we've I think, you know, we were around in 2010, and and so sort of at the tail end of the of of the global, financial crisis. Certainly, pandemic, obviously, was was was had a lot of changes too. What we try to do is not necessarily, you know, forecast what any any organization, any administration is going to do from a policy perspective, but rather figure out, okay. If if if any of these things happen, how do we set up merchants on Shopify so that they're better off than merchants that are not? So in the pandemic, for example, like, immediate we didn't know how long pandemic was was gonna last, but we immediately were like, okay.
Speaker 8:There's a bunch of these, like, restaurants, for example, that are now gonna have to do some sort of, like, delivery service. We're not we don't restaurants is not one of the core verticals that Shopify has ever been in, but, like, let's just make sure that we help them. And perhaps they end up going to accessories later on, and they'll eventually stay with Shopify. Or, you know, a bunch of physical retailers now have to move online very quickly. What can we do to actually help them do so at this incredible clip?
Speaker 8:So that's kinda how we look at these these these times of uncertainty, is just simply prepare merchants on Shopify. So maybe they don't wanna do a tariff calculator. Maybe they don't need to do a tariff calculator. But if they decide to do so and it's valuable to them, let's make sure it's embedded in the product and they can simply just just opt into it. So that's kind of the way we we we do that as opposed to, you know, you can read all you can read as much information.
Speaker 8:You can read every paper and and listen to every interview from the administration as possible. You still may not know what's happening. And so rather than do that, let's just anticipate all these things could happen. Let's just make sure our merchants are prepared.
Speaker 1:I'm not sure if I'm like over storytelling here but Burton, is that a full circle moment for the company? Tell me that. Tell me about the significance of that.
Speaker 8:The significance of it is that, you know Why did take him
Speaker 2:so long? What were they Oh,
Speaker 8:man. Okay. So Canada Goose, Danny, who's an I don't you know you guys know Canada Goose. Right?
Speaker 3:Yeah. Yeah.
Speaker 8:Okay. So Danny Reese, an incredible, incredible entrepreneur, one of the greatest retail entrepreneurs on the planet. He's a friend of mine. He's a Canadian guy. Canada Goose and Shopify are two Canadian, you know, stories, success stories, and and I've been trying to get them on for a while.
Speaker 8:They finally came on too. But Burden is really relevant because, the history of Shopify is that when Toby moved to Canada in 02/2004, he couldn't get a job because he was, you know, a new immigrant, and no one would hire him. So he ended up deciding to start a business, which is, you know, if you're an immigrant, that's okay. And he decided he would sell snowboards on the Internet because he was in Canada and he loved to snowboard, and he couldn't find any good software. And so he wrote, he wrote the software to sell these snowboards.
Speaker 8:The store was called Snow Devil, and that software that he wrote this for Snow Devil would become what is now Shopify. And so the fact that Bird, one of the most important snowboard companies in the planet, is now using Shopify is is really, really cool. And but I I love the I mean, I I I spend if you listen to the earnings calls, I spend quite a bit of time on these calls talking about some of the larger brands coming on. Part of it is that I'm very excited by these brands. Like, you know, I I love the fact that these it's weird, but, like, Hunter Douglas, Birkenstock, Mattel.
Speaker 8:These are brands. Hunter Douglas was created, I think, in 1919. Birkenstock was created in the seventeen hundreds, and and and I think yeah. So Mattel was created in 1945. I like that these very large iconic retailers are selecting Shopify.
Speaker 8:The other reason I like to talk about
Speaker 2:this And brand so it's significant too because there's some Certainly some people living under a rock, and early on Shopify was loved by small merchants that were just Exactly. Starting out. And I'm sure I'm sure you went through a bunch of calls with investors and things like that over the years, which was, yeah, it's great, but, like, you guys just have the, like, long tail of enterprise. You're never That's you're never gonna really dominate with the retailers That's right. That matter.
Speaker 2:And, like, clearly, that's that hasn't been true for a while, but you still kind of have to just like say it over and over and over and over and
Speaker 3:over.
Speaker 8:Yeah. So I'm just I'm just repeating it over and over again. The other thing that was that we announced today was that we now have 12% of e commerce market share in The US. So if
Speaker 9:you think about
Speaker 3:it from a
Speaker 8:checkout perspective, yeah, that's thank you.
Speaker 1:That's really good advice for entrepreneurs over there. Just go get 12% of the entire market. You're probably
Speaker 9:be good.
Speaker 2:A lot of people say, I just I just all I want is 1%.
Speaker 6:No. I'm good with
Speaker 2:1%.
Speaker 1:Little bit higher.
Speaker 2:Go go for is pretty good.
Speaker 6:Go for I
Speaker 8:think makes us the second largest checkout in in The US on the on the internet Fantastic. After Amazon.
Speaker 2:How do you how do you think about sales cycles? Because for someone like a Burton, I imagine the first conversations there, like that feels like this whale that like is just a natural fit for the product but it's not the kind of thing that was closed in like a quarter. So like how how do you how do you kind of even work with the team on that front to understand that like we're actually playing and you know, ideally we close all the customers we wanna close next quarter, but realistically sometimes great partnerships take time to come together. And you guys almost have the luxury of like you're 41 quarters in, you're probably thinking about, you know, you're you're thinking, you know, actually able to think, you know, long term. But
Speaker 8:In some cases, it's it's it's it's actually it's not necessarily based on size or like GMV band. But we have merchants on Shopify that are doing hundreds of millions of dollars of GMV, and they have like I'm not joking. Like, have like 12 employees. Wow. Amazing.
Speaker 3:And then
Speaker 8:we have merchants that have, you know, thousands of employees and are doing far less than GMV. So it's not necessarily about the size of merchant. It has to do, I think, with two things. One is complexity in terms of how much, you know, technical debt and baggage do they have, meaning how much duct tape do they have to undo to migrate over. And then the second part is, like, you know, what how motivated are they to move over?
Speaker 8:I remember, when when Emily Weiss left Glossier, Kyle Leahy replaced her. Kyle's an incredible CEO. Kyle came in to run Glossier, and Kyle called and said, you know, we're a cosmetics company. We have this incredibly, you know, complex technology stack. We have tons of people running ecommerce.
Speaker 8:Do we need this? And we looked at it we're like, no, we we can help you. And I think the glossier migration, again, was that was a that was a homegrown stack
Speaker 2:and we said that was an era where
Speaker 1:Sort of by the way.
Speaker 2:Well, yes but also investors at that time wanted to invest in consumer brands that had an insane CTO. You know, was like, it was a point, it was a badge of honor to be like, no, we're not using off the shelf software That's like we have we're running on our own tech stack. We're a technology company Yeah. Give us a technology multiple.
Speaker 8:Well, and and exactly, you got it. I mean, you said it. Right? It's a technology multiple. They're like, well, we're not really this, we're this other thing as well.
Speaker 2:You're like, sorry, Charlie. I can't switch because if we don't have our own tech stack like my multiple is gonna get
Speaker 1:cut. I talked to one CTO at a d to c company that they didn't just build their own ecommerce stack. They built their own Salesforce. They built their own CRM
Speaker 2:email CRM. Email management. And and the good thing good thing is that everybody realized that you can build your own tech stack, you're still not gonna get a a software Yeah. Tech multiple.
Speaker 1:No way. And and
Speaker 8:your cost is And your exactly. And just just not your cost. Just talk about your efficiency.
Speaker 6:I mean Oh, totally.
Speaker 8:You know, back back to the 12% market share at ecommerce. Yep. There is no checkout that is more performant than Shopify's checkout simply because we have more data in which to make better decisions with. So even if you do have the most technical team building the most incredible technology stack, you still don't have the economy of scale that you can get by being part of it. That that's the weird part that people miss about about Shopify.
Speaker 8:That's the reason why the 12% number is is, I think, valuable. If you sort of put together if you were to assume for a second that we were one single retailer instead of millions of of individual stores, We would be the second largest online retailer in America.
Speaker 1:Yeah.
Speaker 8:As part of that, you get you are entitled to incredible economies of scale. Yeah. So even if you can do it yourself, even if you can do it in a cost effective way, you're still missing out on, like, you you know, we we announced the agentic stuff, which we should talk about yesterday. You you can go do your own deals with every single, you know, agent, like, that's available, or we can just do it for you. We're already doing it for millions of others, might as well throw in with us.
Speaker 8:Your point, though, on the multiple is interesting. Something shifted, I think. At some point, I don't know what year it happened, but at some point, the flex of, oh, I built my own ecommerce stack stopped being a flex and started to look like, why did you do that? I mean Yeah.
Speaker 1:Why '16, junior level write downs.
Speaker 2:That's what You basically start looking at it and it's like, wait, you're spending $3,000,000 a year on this like technology team and that is like cutting that could be cutting, I don't know, safely, like, million dollars off your,
Speaker 1:like, I was running an e commerce company in that era, and I went around, and I and I went and I did I I looked at all the different companies, all the leading d to c companies, looked at their head count on LinkedIn, how many people do have in their technical organization, what's the average comp, and I found out the amount of money that they were spending as a function of revenue. Some of the companies were spending 10% of revenue on just building ecommerce software. And I was like and and so at that time, I was like, oh, I you know, we were on Shopify Plus, and I was like benchmarking. Was like, okay. So we're like an order of magnitude more efficient, but we could be even more efficient.
Speaker 1:We need even less people. Like, it it was just like, we could we should be focusing on the marketing. We should be focusing on the brand. Yeah.
Speaker 8:And and Yeah. There's this great PE firm. You guys probably know it called El Catterton.
Speaker 1:Oh, yeah. Yeah.
Speaker 8:Yes. El Catterton's amazing. Michael Chu runs it. It's like Michael Chu and and the Arnaud family. Bernard Arnaud is involved there too.
Speaker 8:And Michael is an incredible investor. But he's, you know, he's acquired a bunch of merchants, some on Shopify, some on not. And one of the things he's recently told me is that in some of those meetings where he's about to you know, where where where he brings in sort of their first meeting once they've been acquired, by by by them, he says, okay. Well, now when are you migrating over to Shopify? Like, at point, it flipped from being, oh, I can I I have all this opportunity because I can build everything myself too?
Speaker 8:I actually think you should be, like, do what you do best which is you're an incredible cosmetics brand. Go do that really well.
Speaker 2:Yep. Totally. Did Stables come up on the earnings call at all? Any any questions?
Speaker 8:I brought them up a lot many times. Yeah.
Speaker 2:What what's your updated thinking? How do they fit into the kind of Shopify ecosystem in the near term long term?
Speaker 8:Sorry. You said Staples or Stablecoin?
Speaker 2:Sorry. Sorry. Stablecoins.
Speaker 8:Oh, Staples. Staples is a on Shopify.
Speaker 1:Oh, yeah. Okay.
Speaker 5:That's
Speaker 2:Yeah. Yeah. So so, you know, the big crumb
Speaker 1:feels like we're we're in the They're not legal. They're legal. There's a public company. They're out there. But when are we gonna see people paying for it?
Speaker 1:I'm sure that there's integrations. I mean, a decade ago, could pay for a shop you could do a shop on a checkout with with Bitcoin with the Coinbase integration and
Speaker 3:a couple
Speaker 8:of Since '2 since 02/2012.
Speaker 1:You're be talking about remember. Because that was he was when when when Coinbase started in YC. Exactly. And so
Speaker 8:Fifty Cent had had SMS by 50. Fifty Cent was trying to compete
Speaker 1:No
Speaker 8:way. With Beats by Dre. No way.
Speaker 9:Was like
Speaker 8:it was a big battle. Anyways, we had both I think and 50¢ actually
Speaker 1:You had a payment award?
Speaker 3:You know,
Speaker 8:I think one of the first merchants to actually accept Bitcoin. I I don't know if anyone did it but but look Yeah. Think in in that era, it was really that was really about speculation not about Sure.
Speaker 1:Sure. Sure.
Speaker 8:The way that we think about stablecoins in general, and I'll get into USCC in particular, is that anything that we can do that can bring more flexibility to commerce is a very good thing. I think stablecoins, US USCC in particular, it just gives merchants more choices, more security, and it offers much faster settlement. Now, the other thing it it solves, which is not getting discussed, but it's important, is that it solves, like, a real problem, which is cross border. Cross border is now becoming this. It's not becoming a feature of of of modern retail.
Speaker 8:Like, this like, default global is how most modern the the best merchants, the best companies I know are default global. They they don't necessarily look at these geographic physical bounds as as different markets. It's like, well, if you sell to The US, why wouldn't you also sell to Canada? It's effect you know, it's it's the same continent. And so I think with stablecoins, this idea of offering a payment method that combines, like, the transparency with a a blockchain with the speed and and a price stability of a major currency is really, really valuable.
Speaker 8:And then in terms of, like, you know, doing it with with, with a trusted partner for with us, was Coinbase, which we we love. It means that you can actually bring all these, like, you know, very familiar commerce features like auth authorization and refunds, but you don't actually need a new wallet. They're like, part of what I think is is scary about this type of stablecoin is, like, well, do I have to now, you know, create a new account? And, like, what is the friction involved? And I think this the way that we're looking at it is that merchants get paid in dollars.
Speaker 8:There's no new wallet created. There's no added friction, but it's a seamless, flexible, safe transaction.
Speaker 2:Yep.
Speaker 8:So I again, it it it is not about it's not a speculation. It's more about utility. I think once I I I think it'll be a a slow sort of increase in penetration. And then eventually, there'll be a cohort of of consumers and a cohort of merchants that are just like, this is the this is so much better.
Speaker 1:Can we shift to AI? I know that you have some stuff that we should review. I also wanna ask about shopping in LLMs and then how that flows through. There's the potential of ads and there's potential of the checkout happening, you know, or or, you know, I I send my agent out to purchase it. Just give me the updated thinking on how AI has changed or how AI is changing commerce.
Speaker 8:So if you think about if you think about it from a from a sort of a model perspective, think about Shopify as being the hub in the middle. This is like retail operating system where you have your your inventory, you have your analytics, you fulfill orders from there, you have your customer data, everything is sorted at this hub. And you sort of think about, like, the main spoke off that hub is has been ecommerce for us. Mhmm. And then a second spoke, obviously, was, like, point of sale at physical retail, which is one of our largest growing segments.
Speaker 8:And then you can sort of think about new spokes. Another spoke, for example, is, like, social commerce. We integrate with, like, Instagram. We integrate with YouTube. We have a Roblox integration, a Spotify integration.
Speaker 8:So one of the things that we think a lot about is the future of retail is not gonna be this weird binary online versus offline. It's going to be where every surface area where consumers spend their time. And for most merchants most of the time, you know, the Roblox integration is not going to be the main thing. Although, you know, Fenty Beauty, one of our brands, is doing really well with this Roblox integration. They've they've figured out that their consumers are spending time.
Speaker 8:And there's actually a physical they have a sorry. Like, it looks like a physical store inside of of the Roblox universe. Roblox, by way, has, hundreds of millions of of monthly actives. It's
Speaker 1:earlier. It's model
Speaker 8:I up. So
Speaker 2:think it's we we talked about it earlier, 20 plus million DAUs in The US and
Speaker 8:It's that's unbelievable. Under 18?
Speaker 1:Under 18? It's like all every everyone.
Speaker 8:Okay. So, like, think about it from, like, you know, the perspective of of a direct to consumer cosmetics brand Yeah. Where their core demographic is that age group. Yeah. Now, it's a new place and there's no competition no like, one else is like Fenty created a store inside of Roblox.
Speaker 8:You look next door unlike their store in Soho, there's nobody Yeah. We think about this idea of like these different sort of spokes being different channels.
Speaker 6:Yep.
Speaker 8:We think that Agenta Commerce is is very likely going to be a new one of those spokes. And so in the last twelve months or so, we began to build infrastructure that allows these AI conversation basically, to bring native shopping inside of these AI conversations. So we we we launched three things, and I'll go through all three because you guys are technical, and you have a technical crowd. So the first one is catalog. We launched it in in this past quarter.
Speaker 8:So Catalog effectively helps agents to search and and to sort of surface exactly what customers want in seconds. It looks across all of Shopify's products, every SKU on Shopify, and then it uses large language models to, like, categorize them based on, like, you know, meta metadata and and and and and the types of products they are. It also creates sort of this, like, standard product data, at these massive volumes, and then we package it in these, like, basically search APIs. So if you are if you have an agent, you simply can ingest the search API and have the entire catalog of Shopify merchants.
Speaker 1:And is this tech buying an MCP server or is this Yes. An API that's just accessible?
Speaker 8:So you can do an MCP server We
Speaker 1:do both.
Speaker 8:With, like, UI components or you can do it through an API.
Speaker 3:Okay. Got it. Yeah.
Speaker 1:Makes
Speaker 8:sense. Second piece is Universal Cart. This is new. So it's part of what we call CheckoutKit, which I'll get into in second. But effectively, it holds items from multiple stores in one single spot.
Speaker 8:So as you're sort of having a conversation with your agent, let's say you're going on a camping trip, for example, you may want a tent, but you may want a sleeping bag. Those are different stores. You may not be ready to check out immediately, but you also you wanna hold all these things in in one single cart.
Speaker 1:Mhmm.
Speaker 8:And then that that all feeds back in the checkout kit, which we launched last year, which lets partners embed merchants checkout directly in their agents. And it has Shop Pay built into it, but it it it you know, it's the best converting checkout on the Internet, which is ours, and now we're effectively giving it to these agents. What we announced yesterday was that now partners, any any agent, can actually, theme the checkout kit so that it matches the application's look and feel. So it doesn't feel like some weird, you know, iframe that pops out that looks like it's a third party. So it actually looks natively integrated, and then, you know, merchants get the tools that they need.
Speaker 8:They'll get our address verification. They get fulfillment. So and and and, actually, in the case of CheckoutKit, Microsoft Copilot is is already using it. So the benefit is sort of threefold. The first is for consumers, now they can get these, like, personalized conversational shopping experiences.
Speaker 8:From the merchant perspective, merchants on Shopify are now going to have a new place to get discovered across all these AI platforms. But from the partner perspective, which I think is the most interesting, is that they don't have to build the complex parts of of commerce. They get access to millions of these merchants through the this MCP catalog, and they also get the best converting checkout. And, we think if this does become a place that is a predominant or or a a popular surface area for commerce, it it it means that merchants on Shopify will be very well positioned. And what's neat about it is if you think about how a lot of those, you know, like, if you were if you if you were trying to go on a on a camping trip now, you'd probably do it in some sort of search, Google or something like that.
Speaker 8:The the products you're going to find are likely going to be based on, like a lot of them at least, may be sponsored where where the more you pay, the more likely you are to show up. Whereas in sort of the agent world and sort of a Gen2 Commerce world, it's actually more of a relevancy. Like, it has all this history of everything you've ever talked to it and said to it. It knows that you're price sensitive for certain things, but maybe not for other things. So it may it may turn out to be a really new sort of vector for commerce and and and we want to be at the center of it.
Speaker 2:How do you how what's your kind of looking out into the future commerce within LLMs? Are you bullish on on paid placements? Are you bullish on referrals? Was Mhmm. Obviously, like in the same same thing as, you know, in the influencer world, consumers deserve to know what's an ad and what's kind of an organic mention and all that kind of thing.
Speaker 2:There had been a debate recently around, you know, should ads be banned entirely from LLMs? And I, you know, generally don't agree with that just because I think, you know, these tools should be broadly accessible and and ads are potentially a way to do that. But the other thing would be ultimately like do LLMs, would LLMs at some point earn referral fees from merchants? I mean, all this stuff is like extremely complicated and Yeah. Can have, you know, positive effects, negative effects, but what's your framework?
Speaker 8:It's that that that I think is a $64 question. I I I I'm not sure. I don't know Because part of the reason that I think agentic shopping is so interesting to so many people is because it feels more democratized. Yep. It feels more based on it has a great understanding of who you are.
Speaker 8:Therefore, you know, you guys started the show with me today saying, like, I'm gonna have my agent go and buy me a bunch of stuff. I want my agent to go if that is if that is how I am purchasing in the future, I want my agent to go buy things that I actually really like, not the thing that my agent is getting paid for.
Speaker 2:Yeah. Yeah. When I when I think about the use case here is, like, I have certain brands and I only buy their t shirts. If And I could just be in an LLM and say like Yes. Hey, I wanna get some new t shirts.
Speaker 2:Can you like And they're like, cool. Here's the t shirts you normally buy. Would you like? And I'll be like, I'll take five white t shirts and five black t shirts. Then it's just done.
Speaker 2:That's Yeah. Amazing. Because I don't wanna be navigating around and, you know, it's just like removing that friction which is kind of the I mean, has been the history of Shopify. So all these new products.
Speaker 8:If you if you think about, you know, I think Toby told me this that like if you wanna look at you look out to where technology is going, look at what, like, rich people currently do, and then everyone else will able to get that feature. So you go back to this idea of, like, personal shoppers. If your personal shopper is constantly selling you the thing or trying to sell you the thing that they make the most commission on, it may work once or twice. Eventually, you'll stop going to that store. You're gonna look
Speaker 2:the mirror. You're gonna look in the mirror.
Speaker 8:You're like, dude, this is like this is like some gold chain or something. Like, I wear a black T shirt.
Speaker 1:Like, don't
Speaker 8:you know, like, I know you're getting paid more for this gold T shirt. I wear a James Purse black T shirt every day of my life, and James Purse is a great shop by merchant and a great entrepreneur himself.
Speaker 1:Oh, there we go.
Speaker 8:Never he's advertised. Doesn't advertise.
Speaker 3:So He
Speaker 8:doesn't advertise. Like, he's so, like, he's not gonna participate in that, but if it knows that I really love James Purse black t shirts, it has to be highly contextualized. So that that is a really good question. I think the way that we look at it is is like this. There is a there is a there is a decent chance that agentic shopping will become very relevant for some segment of the market.
Speaker 8:Therefore, if we wanna qualify and requalify to be the merchant, the retail operating system for all these incredible brands, we have to be there in the same way that we have to be in social commerce. And social commerce, you know, for some people, it is a really, really important channel for them. You know, my mom is I don't think my mom has ever bought something on social commerce. She still goes into a physical store. So we we're not going to predict like Our our our job is to make it so that wherever you wanna sell, you should be able to do so really easily.
Speaker 2:It's going to be absolutely wild when you think about, I mean, this this experience where you're chatting with a model
Speaker 3:and Yeah.
Speaker 2:It services you a product and you can ask it, well, what do people like me think about it?
Speaker 3:And it
Speaker 2:like automatically pulls, you know, reviews from It relevant pulls what your favorite influencer thought about the product. It it surfaces other brands like it it's gonna be incredibly powerful and I think at at best, it's like a personal shopper that's aligned with you, not, you know, trying to maximize every purchase. Or a great sales rep who's, if you're working with, you know, a a sales rep at at at a retail store, they're not fixated on like, how do I maximize this, the value of this cart. Right? They're thinking about this sort of long term relationship with the customer.
Speaker 2:So very exciting. I'm excited to see what people build.
Speaker 1:Well, congratulations. Thank you so much for hopping on and chatting with us. Always fun to be here. Always so much fun.
Speaker 2:Fantastic work.
Speaker 8:You guys are the best. I love your show. Love what you guys are doing and I I like that this is becoming new routine that I've
Speaker 2:We'll
Speaker 1:talk to you soon. Up next, we have Anton from Lovable coming in the studio. Get that gong Jordy what?
Speaker 2:Shopify. Oh. What? Up 20%. 20%.
Speaker 1:Yeah. I was trying to tell him that on the stream because I wanted the eyebrow raise like the you know from the Brian Chesky when the IPO and they and Emily Chang tells him how much the stock is of and he goes It's like one of the most iconic moments in tech history. Anyway, we got Anton from Lovable. How you doing?
Speaker 2:What's happening?
Speaker 10:Great. Great to meet you finally.
Speaker 1:Yeah. Yeah. Great to meet you too. We were going back and forth with with folks in and around your orbit. Every time we talked, there was a new massive number.
Speaker 1:There was, you know, a certain amount of people on the platform, certain amount of websites. Give me the latest headline number that's shocking. Isn't it like some insane number of websites on the internet are generated every day?
Speaker 10:That is true. What are you holding?
Speaker 1:I'm holding a gong. A mallet to celebrate.
Speaker 10:I I just learned today we have 100,000 new projects built every single day.
Speaker 1:Congratulations. That's fantastic How'd you do it? What's the key to success? What are people using Lovable for more than anything else? There's when you think about just a web page can be anything.
Speaker 1:It can be everything from from Facebook, a billion users, a trillion dollar company to, you know, a little homepage for my, you know, my my, like, my resume. What are people using it for?
Speaker 10:Yeah. Look look, Lovable is is the fastest way to go from an idea to a production ready application.
Speaker 1:Mhmm.
Speaker 10:And a lot of people make that into real business. And that's something we that's in our mission to empower much more people to do. But apart from the entrepreneurs, the solopreneurs, like building for the first time or building for the nth time without but by themselves, you have a lot of people in larger companies now. And we're seeing that use case growing very, very fast, like, percentage wise, much faster. And then they they go from, like, I have this idea.
Speaker 10:My engineers should build it, but they don't understand me. So I need to create a a full working version of it, and then they're gonna be like, okay. I get it. It looks great. Let let's build it.
Speaker 10:And how
Speaker 3:are you
Speaker 1:how are you thinking about tool use right now? I I I feel like there's so much open source software there. LLMs are incredible. They could probably rewrite Linux from scratch. They could rewrite a database from scratch, but you wanna be provisioning and standing on the shoulders of giants.
Speaker 1:But how often are you focused on allowing the, like, the like, to grab different open source projects and tools? Like, if you wanna build an ecommerce software, you probably don't need to rewrite a catalog from scratch. There's probably a tool for that.
Speaker 10:Yep. No. How we think about making the product as good as possible, and we thought about it for a long long time is, like, we have an agent Mhmm. That can do things. He can browse the web, generate images, but specifically create applications and the website personal website for you or whatever.
Speaker 10:We are making giving that this agent more capabilities. We're adding new things. Okay? So for ecommerce specifically, we're taking the best of breed to build ecommerce as a tool. Mhmm.
Speaker 10:And more to I'm I'm spoiling some I'm teasing some things there on on the ecommerce side, actually.
Speaker 6:Yeah.
Speaker 10:I'm giving it more tools, and then we're making the agent itself smarter. And so those are the two things we're doing. Giving more tools, making it smarter.
Speaker 1:What's the key to high retention? I feel like there's a world where you you, you know, use a tool, lovable. You build something, and then you're like, okay. We're ready to go and stand up a whole team of engineers to actually build this thing and take it to the next level. How how are you, you know, fighting that urge to just use this as a prototyping tool?
Speaker 10:Yeah. Like, if you have a high performing engineering team with a large existing system, then there's always this balance of, like, do I take this thing I built in Lovable
Speaker 1:Yep.
Speaker 10:And I connect it to my system? Many people do that. Or do I just use it as a design? And then I, like, know exactly how to build it, so it's gonna be super fast with my engineers. Both are fine.
Speaker 10:Or do you do I even edit the code as an engineering level, also popular? I I think regardless of all of those, you can have very, very high retention. Because if you want to just prototype in Lovable, it's the easiest way to do it. You just open the browser and then boom, you have you have your prototype. And it has access to your design philosophy.
Speaker 10:It has access to, like, integrations and different tools that you might wanna want to use. There's a high retention. There's a lot of high retention on that use case. But how I think about it going forward is that we want to just build a platform where you never want to leave this platform because it provides you so much value. And what large language models have done now is that they, like, they generate code really well.
Speaker 10:And but that's just one tiny part of the entire life cycle of building and maintaining and operating and the product and growing a growing a business on top of that. Yeah. So I'm not sure if know Elena on her team. She's like, I've been doing growth for twenty years, and now I'm so excited to not have to do, like, the boring growth and just do the innovative growth, and AI is going to handle all the growth, like, all the growth things. So so so that that's on the horizon.
Speaker 10:And when when you have a platform like that
Speaker 1:Yep.
Speaker 10:You should be getting so much value that you never want to lose.
Speaker 1:That makes sense.
Speaker 2:How do you what do you what do you think is the future state of, you know, what do you think the average startups website will look like five, ten years from today? I feel like right now, we're in this era where AI is changing everything. It's changing workflows. It's changed the way changing the way we work with software and yet startups, you know, still buy, they try to buy their 1word.com domain and the the typical website is like incredibly, you know, static and and tries to reach a broad audience and I
Speaker 9:can
Speaker 2:imagine I can imagine a world in the future where where websites are being almost generated in real time depending Mhmm. On the user and and the type of customer they are.
Speaker 1:More We're getting more
Speaker 2:Yeah. Yeah. Knowing knowing the the the trend to date, it will be more of that. But I'm curious, you know Yeah. Kind of if
Speaker 6:you have
Speaker 10:I think the websites of the future are going to be better at hacking the human brain and, like, it's addicting the nature add addictive nature and so on. What that means exactly, I don't know. We were like, they will let the algorithms figure out partly.
Speaker 2:But, no, I think Anton is gonna hack your brain, everybody.
Speaker 1:Yeah. I mean, do you think that starts with like a b testing because you can generate more pages quicker that you're just kind of optimizing for retention or conversion and then because you're just generating the entire site instead of just, you know, testing two different headlines. You're testing the entire concept of what the website is.
Speaker 10:I I yeah. I think the algorithm like, there's going to move more and more of the algorithms to figure out how how things should be optimized for us. And then I I think what, like, what you're also seeing now already is some some a bit of counterculture to that with a human coming in and being like, no. I want it to be much more minimalist, like, a new type of
Speaker 3:Yeah.
Speaker 1:This is the Matt Friedman style that Mark Zuckerberg recently Exactly.
Speaker 10:Exactly. Times to
Speaker 1:run, raw HTML. There's a time and a place for both. Time
Speaker 10:and a place for both. I guess we're seeing, some complex evolution of the of of different different ways of doing things. And, generally, I think the few like, the future has always been more and more diverse. There's, like, many different websites and applications, and we could I think that trend is going to continue. It's not like it will converge to just Yeah.
Speaker 10:Just one way of doing things.
Speaker 1:Last question from my side. What what's what's next on the horizon? Are you focused on taking the product that you have? You clearly have product market fit. Are you focused on sales, marketing, ramping up, expanding what you have, or or or expanding the portfolio to different areas and different markets, different products?
Speaker 10:Yeah. I'll answer it like this. So in the order of, like, the size of the use cases, founders are taking their ideas and they're building real businesses, soft software businesses. Sure. Designers and product managers and others in in companies, they're taking their ideas and building concepts to communicate with a team up and, like, 100 times faster than building out the concept in the past.
Speaker 10:And then everyone else is building, like, their personal or business websites in much, much faster. And we're doing all all of these things. Lovable does all of these things at the same time, and it, like, becomes as you use it, it becomes better and better at helping you. Cool. So that then that's what we're going for.
Speaker 1:Amazing. Well, congratulations on all the fantastic growth. Truly staggering day
Speaker 2:Barely a week goes by without a big lovable number hitting the timeline.
Speaker 1:Yeah. Another another lovable number has hit the timeline. Congratulations. Thank you so much for stopping by. We'll talk to you soon.
Speaker 1:Have a great rest of your day. And up next, we're shifting over to, Thomas from GitHub. Another little post earnings breakdown. Get the update from Microsoft and GitHub. Nat Friedman was running the organization.
Speaker 1:Thomas has taken over and they've been on absolute tear. To follow. Just to 20 the million users. It's growth serving 90% of the Fortune 100. Congratulations.
Speaker 1:Kick us off with an introduction.
Speaker 9:Thank you so much for having me on the show. To be here.
Speaker 1:Thanks so much for joining.
Speaker 9:And, yeah, I'm I'm Thomas and I have been running GitHub for the last four years. I've been with GitHub for seven years since we acquired it in 2018 and it's been a tremendous run that GitHub had as part of Microsoft.
Speaker 1:Is it fair to describe the run as as growth in overall users or growth in GitHub Copilot revenue or, you know, this 90% of the Fortune 100 is using the product now. Has that been the win case? Has it been a
Speaker 2:little
Speaker 1:What's bit of whole
Speaker 2:the other 10% doing? Well,
Speaker 3:the other 10%
Speaker 8:is not
Speaker 9:gonna get software, I think. Yeah. They want business software. That's why they are.
Speaker 1:That's why is the principle. The last 10% is gonna take you 10 times as long to
Speaker 2:we gotta figure out the 10% and short them. I mean but seriously if you're a fortune one five hundred company and you're not building some software in your organization There
Speaker 1:are companies that provide similar services that do well. You know, we're not gonna talk too much trash about the competitors, but, you know, we are we are big fans. But, yeah, what what, over your tenure, what have been the big initiatives that you've shipped and then maybe opened bottle of Dom Perignon champagne or or just had a pizza with the team to celebrate?
Speaker 9:You know, always keep pushing further, so there isn't Yeah. There's celebrations every now and then, what's really like about what's next, what's next, what's next. If look back to 2018 when we did the deal, we really had three principles. Put developers first, and I think we nailed that one. GitHub is still GitHub.
Speaker 9:We are talking about developers, we are building for developers, are meeting with them all the time and we have preserved that spirit of what GitHub is all about. The second one was that Microsoft helps us accelerate. Microsoft, if you will, as an investor into GitHub. I think that's the 150,000,000 developers on the platform. Recently we hit over a billion repositories, both original repositories and Fox.
Speaker 9:Congratulations. You mentioned the 20,000,000 Copilot users. Microsoft's VIRTUDIO family, so Versus, IDE, and Versus Code together has 50,000,000 active users. So you can also see how much room there is still for Copilot to grow its market share. A year ago we passed 2,000,000,000 in ARR, annual revenue run rate.
Speaker 9:And I think all these metrics show that both the business itself is healthy and keeps growing the network effects that GitHub as a platform has. And then the third one was that Git helps to accelerate Microsoft. And the most obvious thing, obviously, is that Microsoft developers are using GitHub and are using Copilot. So Microsoft itself benefits from the same productivity gains that our customers benefit from. And then we're sharing a lot of the AI knowledge across Microsoft, you know, within the core AI division, Azure AI Foundry, and all these tools.
Speaker 1:I'm hearing glimpses of self improving artificial intelligence. Microsoft is using GitHub to improve GitHub. I'd love to see it. What where else are people using GitHub Copilot? Where are the what are what are the biggest, like, win conditions or win win use cases in those Fortune 100 companies?
Speaker 1:Where's the biggest value being derived right now?
Speaker 9:Believe it or not, I think the biggest value is still the core scenario, which is you have your IDE open Versus Code or JetBrains, even Apple Xcode and you're writing code. And instead of switching between the IDE the browser where you have all these tabs open and you watch this show and there's all distractions in your browser and you try to find the answer to the problem you're trying to solve, you just have it right there, a value building. So whether that's code completions that predicts to you something that you might not have even thought about in that moment or whether that's the ability to go into chat and ask question about that code and find a bug, or I was working on my blog on Sunday and I couldn't figure out how I couldn't remember the markdown syntax to embed an image. I was just like, give me that really quick. And then all the way to agentic scenarios, and I know you talked with Anton like before.
Speaker 9:It's this ability to give it a task and then watch it do these things and call tools and it figures out how to install this NPM package. Yeah. And then it looks at the error message and it sees that there's a test case missing. So I think this end to end spectrum where I'm still the pilot and I'm still in charge because I think and I strongly believe that the majority of developers actually want to build something. They don't want to offload their job to somebody else, like an agent or that set of agents.
Speaker 9:They want to use these agents to do what they love doing most.
Speaker 1:Yeah. Can you talk to me about where the boundaries of GitHub or Microsoft's agnosticism land? Like, you don't make everyone write c sharp. You don't make everyone use, Versus code. But, how are you thinking about integrating different models at Microsoft Build?
Speaker 1:Sachin Adela was talking about the importance of Azure being a place where you could get everything from GPT-four to DeepSeek to LAMA to it sounds like XAI is coming on as well. How are you thinking about integration with a broad suite of new tools as they come up?
Speaker 9:Choice is crucial for any developer tool to win the market. You can't can't be in in the space of of selling developer tools and and not offer developers choice. Mhmm. Because if you don't do that, they go somewhere else, and they will find the choice somewhere else. So since last year we're offering what we call multi model choice.
Speaker 9:So we're not only having the OpenAI models, which which are still great and and many people use as their default. We also have Anthropix models. We have Google's models. We actually have, you know, bring your own models so you can connect from Copilot to OpenRouter or OLAMA, and from there you can go to every model imaginable as long as it has an API and a key that you have access to. And so we think that is crucial, developers will not want us to tell them what model to use.
Speaker 9:That's just an intrusion in my personal freedom. They know better what's best for them in the same way that at GitHub we wouldn't tell you use this open source library or use this programming language. GitHub wouldn't be what it is today if it had only one ecosystem, let's say JavaScript all its libraries. Now obviously there's boundaries there because we have only so many people at GitHub at Microsoft that can integrate all these models and there's a new model every single day, sometimes multiple times a day.
Speaker 1:Yes. Yesterday there were two new models. Three I think if you counted two open source ones.
Speaker 9:And all these models need GPU capacity and and you know, responsible AI testing and and
Speaker 6:Yep.
Speaker 9:Red teaming and and all that. And so we believe it's a mix of we provide models out of the box and you bring your own model through OpenRouter or or Lama and and what have you.
Speaker 1:Fantastic. Jordan, last question.
Speaker 2:Last question. You have over a 100,000,000 developers on GitHub. Have you tried to estimate how many of them are not using any AI tools that are
Speaker 7:just Oh, yeah.
Speaker 2:That's hanging interesting. Back saying, I'll I'll I'll I'll make my code by hand, please. Handmade. None of that AI for me.
Speaker 9:It's over a 150,000,000. I think it's still, you know, less than 50% that use AI on a daily basis and that's just the nature of things. Right? If you look at these 150,000,000 developers, there's lots of students there where the professor may not allow the use of AI or they haven't made that step because they're really just trying to solve that task from their homework or from their test. But at the same time, we see more and more developers making their jump.
Speaker 9:Software development has always been a spectrum. Those that are still working on COBOL mainframes. In Germany, there are still companies I think the train system is looking for people that have Windows 95 experience in in 2025. Right? Like that's the like we
Speaker 2:always grads, now Windows 95 for when from when you were
Speaker 9:But believe it or not, even if you you know are new grad or post grad and and you and you join a company and you have to work on a cobalt project, as long as you can then also use GitHub and Copilot and AI tools, that might not be the worst job in the world, right, because you can combine modern technology and apply to that old stuff. But what I was going to say is that we have this huge spectrum between the people that are most ahead on the curve, you know, those watching your show and or or or talking on the show here, and then those that are still having to maintain the systems that power the world. And we our our mission at GitHub is to to cover all these developers and and enable them, you know, to collaborate between humans and humans and very soon between humans and agents and agents with each other. Right? That's where that's where the platform is going.
Speaker 1:Well, thank you for your service and congratulations on all the growth. It's been great chatting with you. We'll let
Speaker 2:you Super get back insightful.
Speaker 1:Have a great day. Thanks so
Speaker 9:much having me.
Speaker 1:Talk to you soon. Up next we have Alex Jacobson from one three seven ventures. We've had Christian Garrett on the show many times from one three seven ventures and we're excited to catch up with Alex.
Speaker 2:Of ours. I'm excited
Speaker 1:about great conversation with him a couple months ago. Excited to catch up and chat with him about everything in the one three seven ventures profile.
Speaker 3:How are
Speaker 1:you doing, Alex? Good to see you.
Speaker 6:Oh, good. You too.
Speaker 2:Sorry. Sorry we're running late.
Speaker 1:We we yeah. We ran a little late. We got a bunch of very yappy people. This guy Mark Andreessen came on. He was talking a lot.
Speaker 1:We were asking a lot of questions so we put us behind but good to catch up with you. How are you doing?
Speaker 6:Good. I was just watching but I was three minutes behind so I thought I was I had a bit more time. Sorry about that.
Speaker 1:It's interesting. Yeah. We're gonna figure out how to feed you the show so that as soon as you join the room, you're seeing it live instead of with the delay. But anyway, thank you so much for joining. What's new in your world?
Speaker 1:What's the biggest news in the one three seven ventures portfolio? I'd love to just get the general update.
Speaker 2:Oh. I'll start I'll start Christian Christian had like a screenshot of
Speaker 3:It was
Speaker 2:I know. But it was it basically had the one three seven portfolio up and it basically looked like the top 10 most in demand private companies. And I was like, oh, it looks like a pretty good portfolio to have. So you guys have been everywhere.
Speaker 6:Yeah. I I mean, we have we we're building this general concept of mag seven for private. And so we have the there's this idea of there's these companies that grow indefinitely in the public markets, and they've built themselves to do that in the public markets. The strategy for doing that in the private markets is different because you need to do different things in different ways. And so SpaceX has led the way on this because the they give employees equity, and they then also run tenders regularly so that that equity can become liquidity.
Speaker 6:Mhmm. And the important the important bit of that about that strategy is that the price at which they're providing liquidity is materially lower than what the market would pay in a fully liquid public market. And so you can say, oh, that's terrible. The employees aren't getting the right thing. But that's not fair.
Speaker 6:The actual thing that's happening is when employees are issued, equity when they get hired, they know it's gonna go up because SpaceX keeps growing. SpaceX is one of all these companies have the property of having a huge amount of power in their market and, a even larger TAM. And so you can that you can understand this indefinite growth, and you can talk about it for the public companies or the private companies, but the general thing that you're looking at is this combination of power and large TAM. And so in a private in a private market context, all these companies need to hire people to go capture that TAM. Mhmm.
Speaker 6:And the value of these companies keeps going up, and the strategy is to give the employees certainty that the equity they've been issued will be worth a lot more in the future. That's harder to do in the public markets because everything's perfectly priced, and so you don't really know if the stock's gonna go up. You think so. You hope so, but it's harder to tell. In the private markets, the nice thing is you control your price, and you can if you're just if you run your process properly, you can have this very deterministic outcome for your employees, which I think is super powerful.
Speaker 1:We talked to Harley at Shopify about the benefits of being public. You have a liquid currency for acquisitions. It it it sets him up. He referred to it as being in the major leagues now. Give me the pitch for staying private as long as possible.
Speaker 6:I mean, I don't think SpaceX isn't Major League.
Speaker 1:Yes. I agree.
Speaker 6:So there's
Speaker 1:What are the benefits of staying private?
Speaker 6:The the I think the big one is hiring.
Speaker 3:Okay.
Speaker 6:This is I that's the thing that I think people underestimate which is that if you can issue people private company stock at your four zero nine a and then you and and you control the price, it keeps growing, then this is all a much more deterministic thing and it's super powerful to be in these companies because the nice thing about these companies, like, there's this funniness of, they're always underpriced, so there's always investor demand for them. Yeah. So as long as they as as long as it
Speaker 1:Yeah.
Speaker 6:So you just have this positive feedback loop of there's always investor demand for them, so the investors wanna buy more, and the stock price keeps going up, which means the employees can look at these companies and go, oh, this equity is really worth something because they know it's gonna go up. If you're getting public company stock, you don't get that.
Speaker 1:Yeah. Yeah. And there's not the volatility that comes with, I checked my portfolio today. I'm down a little bit just because, oh, there's some weird tariff thing going on in some foreign country and I how does that affect my business? Whereas, yeah, if you're in the private market, you don't have to deal with that.
Speaker 1:What about these new what what what's your take on some of these new initiatives to give retail investors access to private company shares or put private company shares on chain and create tokens and SPVs and all these like like different financial engineering efforts to bring to give retail traders access to private market company stocks. What's your take on all that?
Speaker 6:We've been seeing people trying to do this forever.
Speaker 1:Mhmm.
Speaker 6:It's an ongoing thing of, uh-oh, we find it inconvenient that these companies are private, so we're gonna try to do things to make them seem more like public companies. But the one of the big values of being a private company is controlling who your shareholders are
Speaker 1:Mhmm.
Speaker 6:And controlling your pricing. And so, if you're trying to stop that from happening, that's you know, maybe that's an opportunity, and maybe you can force one of these companies to be a de facto public, but that's not a service. If they wanna be public, you know, there's this mechanism called the public markets to do that.
Speaker 1:Yeah. What about a higher level of abstraction? Like, I I believe I believe
Speaker 2:I'm sorry. You know, certain private companies don't wanna be public because they don't wanna be on this sort of regular reporting cadence Yeah. Just don't feel like they're ready for it. But the idea of like taking private companies, putting them on chain, letting private company shares, putting them on chain and then just letting anybody in the world by by access, you know, by them, but not giving them any of the information that allow that that makes the the public market so beautiful which is like anybody can read this information and you can come up with a decision on your own and there's like rules and frameworks to make sure that people aren't insider trading Yep. Things like that.
Speaker 2:And so it's like who's benefiting here? It's like retail has a potential to get even more hoes and and then the companies are having to deal with shareholders that that now have an opinion about how they're operating the company but none of the real rice rights associated with with owning the shares.
Speaker 6:Let let me be charitable to these people. There's a real thing of the only people who get access to these private mag seven companies are institutional LPs who invest in our fund or funds like ours.
Speaker 1:Yeah.
Speaker 6:And, you know, we're not we're not we don't have retail investors in our fund. There's there's a sort of in the manager class, there's something we refer to as retail, which is there's a longer tail of of wealth that is now trying to play
Speaker 1:Mhmm.
Speaker 6:In and invest in these things. So there is some that is in some sense a longer tail, but there isn't the people who have who are public markets players. There aren't non institutional players in the game, really. Yeah. And there's something real about giving people access to the growth that these companies are going to have.
Speaker 6:There's and it's unfair in some general sense that that these retail investors don't have access to this growth. And I so I think there is some amount of institutional design around how do we give them access to this growth, but turning these private companies into public companies is not necessarily the way the way to do that.
Speaker 1:Yeah. It's almost like, like, what if, like, what if, the Yale endowment was publicly traded? It's like, then I'd have broad exposure to a bunch of venture capital firms, which have exposure to a bunch of private companies and, you know, it still just rolls up to just a few line items on the cap table. I'm not, you know, this random, like, retail trader doesn't isn't actually on
Speaker 2:the It's disingenuous to say that, like, everyday people don't benefit from private mag seven as you've described it because it, you know, a lot of venture capitalists raise from pension funds.
Speaker 1:Sure.
Speaker 2:It's teachers and firefighters and things like that who are are actually, you know, benefiting from the performance.
Speaker 6:I mean, I think there there's a pension we're definitely in the pension funds are definitely beneficiaries, and that's very But I I don't know how much of the like, there's definitely these, you know, those types of pension funds that are out there, but there's lots of people who aren't in these sorts of pension funds. I I think you're right. There's there's definitely that that sort of universe is taken care of, but I think there's plenty of people who aren't in that type of pension fund either.
Speaker 2:Yeah. And Totally.
Speaker 6:Generically, they're in the pension it's in a pension fund, they're not able to say, oh, I would like more exposure to privates. Yep. Right? So at at a at invest at the there's there I I understand the feeling of that there's these people are underserved in some way. It's not they're not my customers, but I get the feeling.
Speaker 6:Yeah. Is to about institutions
Speaker 10:for it.
Speaker 2:It is funny to think about if if if a bunch of Stripe shares were dropped on Solana. Like, what Stripe would actually trade at? Because I would guess that it would look like it would look like it would be like the most insane pop and then suddenly it's like, okay, if you wanna buy Stripe on chain, you gotta pay like 400 A million dollars trillion dollars. Something. Or a trillion dollars.
Speaker 2:Right? You could
Speaker 1:And for some of the even bigger like me like like potentially like me me private companies, it could be even crazier.
Speaker 6:Yeah. Right. I mean
Speaker 1:Yeah.
Speaker 6:There there's the whole Elon universe of companies.
Speaker 1:Yeah. You
Speaker 6:know, we we have a sample of one of them that's public.
Speaker 1:Yep. We know what happens there. Speaking of that, I mean, he was talking loosely about taking Tesla private at one point. That, you know, obviously didn't materialize. But is there a world where the private markets evolved to such a point and it becomes so elusive that you see a take private of a company specifically to get back on that track or or once you IPO, has the ship sailed and it's gone forever?
Speaker 6:I mean, I'm I live in the private markets. I like the private markets. I think there's a huge amount of value of being here in the private markets. And so I'm definitely talking my book. But Sure.
Speaker 6:The the the big thing that has changed over the past some number of years is how big the private markets now are.
Speaker 1:Yeah.
Speaker 6:Right? So we so the how much we can invest in SpaceX or Andorrell or Gusto or any of these companies has gotten to be large numbers. Yeah. And so, you know, there's this argument of when you're public, you have this currency that you didn't have because the public markets have more money, and I don't think that's as true anymore. I think that there's this real chance that you could decide, I just want more control.
Speaker 6:I don't wanna deal with this regulatory nonsense and be private. There is this they're both it's a it's a regulatory ritual, but it's not actually a different company, and you might wanna just have a different regulatory environment.
Speaker 1:Yeah. I'm thinking specifically about Snap. Snap had earnings. They're down 17% today. They live and die by the earnings call.
Speaker 1:Meanwhile, Apple's up 5%. Meta Platform's up 1%. Amazon's up 4%. And and it's only a $13,000,000,000 company. The the capital exists and there's always been this narrative, like, it's easier to turn the cruise ship when you're in the private markets.
Speaker 1:You go to just a few investors, you say, hey, we're gonna miss earnings really bad for a couple quarters but then we're gonna build something new. I don't know. It's a while.
Speaker 2:You could have three snaps or one perplexity.
Speaker 6:Wait. So I think next there at 20. Was that I mean, the the part of I mean, the hard part is these things are now priced. Yep. And so you're gonna take it private, and you now have to go resell this to the private capital markets
Speaker 3:Yep.
Speaker 6:Who have looked at this in public markets and gone, well, that didn't look right. Yep. And so I think there there's a hard sell of going to the private markets and selling, you know, selling Snap in the private markets. Yep. I think it's entirely possible that it could do better Yep.
Speaker 6:But, you know, the they have to go, they have to sell it.
Speaker 2:Yep.
Speaker 6:It has there's a founder led story. I mean, I think we can, like, sit here and script it and maybe we can make it work. But I think I'm just not easy.
Speaker 1:Story. I I think the best example is probably Dell, which, went through Take Private and then and then, later went back public at a much higher price. But I mean, these stories are extremely few and far between.
Speaker 2:Well, switching gears. I wanted we had Dan on from Armada earlier this week. Super exciting company. Know you guys have been involved from probably before the company was created. Wanted to get your view on on the opportunity and and what made you so bullish.
Speaker 6:Now or back then?
Speaker 2:I mean, both. I mean, we we got we got last time we talked, I think we got a good good overview, but it was kind of hearing the kind of landscape and and the initial catalyst was was interesting.
Speaker 6:I mean, the the the original version of this is if you think about what a data center is, a data center is a point source is is trying to maximize the value of a point source of connectivity and power. Right? That's, like, structurally what it is. And so, you know, power has is available at different prices at different places. Fiber is available at different play at different levels of reliability.
Speaker 6:How many fiber points do you have? Are they really one or two? Like, it's doing the underwriting of what it's actually a lot of work to make a data center. But the whole premise is that you have sufficiently reliable and large power and sufficiently reliable and large connectivity. SpaceX changes that.
Speaker 6:So SpaceX says, actually, there is no longer this concept of a point source of connectivity. It's available everywhere.
Speaker 3:Mhmm.
Speaker 6:And in any one point, it's not, you know, it's not as good as as fiber, but the world's pretty big, and so the aggregate bandwidth of Starlink is huge even if the avail the availability in the square foot you're in is not as big as holding a fiber in your hand. And so the insight is, okay. Well, SpaceX gives us opportunity this opportunity to rethink how we do connectivity. So does that mean we can think rethink how we think about power? And the interesting thing is if you're looser about connectivity, now you can look at power in a bunch of different places and you can say, hey, there's solar everywhere.
Speaker 6:So now you just simply put out a solar panel and a dish and you're live. And the and is the solar panel enough for the amount of compute you wanna do? Maybe, maybe not. But that but that's the beginning of the conversation. And then, you know, so in the original design for this, it I sketched out a, shipping container that unfolds solar panels on a roof, and I figured out that need a lot of solar panels to power a rack, but you can do it.
Speaker 6:But and so that's but that but, you know, the math on that actually worked. So it was like a 3% IRR when you did the model, and the 3% IRR isn't glorious, but it was just a model. And then you have the testing. So we say, oh, this is it's sufficiently interesting that it's worth testing. And then when we then we got Dan, and Dan is this phenomenal, has has phenomenal network, has phenomenal sales.
Speaker 6:And his solution wasn't, hey. Let's build it and sell sell cloud. His solution is calling people he knows and asking them, what do you think? Because that's how he works. And so we get on the phone with the CTO of Aramco, somewhat of a surprise to me.
Speaker 6:So I'm suddenly on the phone with this guy who is
Speaker 2:San Francisco San Francisco company. Right?
Speaker 1:Yeah. Founded in San Francisco. Right. West Coast tech wins again.
Speaker 6:Yes. And so I'm suddenly pitching this to this guy. And the insight is, well, there's this other problem. You know, the underlying story that I just told you is about stranded energy. There's stranded energy all over the place.
Speaker 6:Let's use stranded energy. But the thing that's happening on an oil platform is there's stranded data. Mhmm. And so these data these these oil platforms produce huge amounts of data that get effectively dropped on the floor. Mhmm.
Speaker 6:And they have some amount of compute that is in in a closet somewhere that some guy on the platform manages.
Speaker 1:Yeah.
Speaker 6:And Halliburton support and Halliburton sells them to software. It's like the the actual architecture of that market's crazy. Yeah. And so it's like, oh, wait. We could do better.
Speaker 6:Yep. And so if we if we provide a cloud at the at this locus of stranded data and stranded energy and and a global communications, we can create a lot of value.
Speaker 1:It's great.
Speaker 2:Very exciting. Well well, next time you join, we'll have you on for an hour.
Speaker 1:Yeah. Yeah. Can go so much deeper. Thank you so much for stopping by. We'll talk to you soon.
Speaker 2:Great to see you.
Speaker 6:Alright. Good seeing
Speaker 1:out soon. Bye. Cheers. Up next we have Nick from Rillet coming into the studio. I think we gotta get the mallet We gotta get the gong ready.
Speaker 1:Jordy you wanna take this one? You wanna hit this?
Speaker 2:I'll take this one happily.
Speaker 1:I think I hit the last one but let's bring him in. Let's play some music. Let's play some soundboard. Let's bring in Rilla. How you doing?
Speaker 1:Welcome to stream. Thanks for joining. Sorry we're a little bit late. How you doing?
Speaker 5:Hey, Check check. Do you hear me okay?
Speaker 1:Oh, yeah. You're great.
Speaker 2:We're live.
Speaker 1:It Nicholas? Is it roulette or relay?
Speaker 2:Roulette. Roulette.
Speaker 5:Roulette. So the American spelling.
Speaker 1:Yeah. There we go. Okay. I wasn't sure if it's French. Anyway, give me the update.
Speaker 1:Give me the news. Give me the overview of what you're building.
Speaker 5:Awesome. Yeah. Excited to be here, guys. Thanks for having you on. Thanks so much.
Speaker 5:Today, we're announcing our 70,000,000 led by Andreessen Horowitz and Iconic.
Speaker 1:Congrats. Oh, that was a
Speaker 3:good timing.
Speaker 1:Really good timing. Congratulations. Boom.
Speaker 8:Thank you.
Speaker 1:I give us a little prehistory on the company. When did it start? How's the growth been? And key customers, how you're building and how you're thinking about solving AI native ERP.
Speaker 5:Yeah. So we've so quick quick backstory also myself. So deeply accounting and finance Mhmm. Versed sort of a full background there. Started this company roughly three and a half or so years ago.
Speaker 5:Mhmm. Very much in stealth for a very long time. As you can imagine, a full on accounting system or ERP is not a small feat to build. It's a lot of surface area. These are very entrenched systems traditionally dominated by NetSuite, Oracle, SAP, these type of names.
Speaker 5:So we yeah. We're very fortunate to to have had a stellar team of accountants and engineers building and building. And then we came out of Stealth last summer, roughly a year ago, and things have gone vertical since then. So it's been an awesome journey. Race our series a here just a couple months ago, three months ago, twelve weeks back.
Speaker 5:And, yeah, back to back here with a b.
Speaker 2:What does it take to get a company to rip out their existing ERP and and bet on a new company? Company. Right? Right? Like, Like, that's that's the the real real challenge.
Speaker 2:Challenge.
Speaker 1:Like, I was this about to ask. Are people ripping out Oracle and SAP and NetSuite? Or is it, I'm upgrading from a spreadsheet?
Speaker 5:Yeah. Great question. So we are getting 70% of our customers today coming from softwares called QuickBooks and Xero.
Speaker 1:Sure. Makes sense.
Speaker 5:And then 30% of our customers coming from NetSuite and Sage Intact.
Speaker 1:Okay.
Speaker 5:So it's very much a mid market focused ERP software. That's good one. Key reasons why people use Relet or wanna buy Relet, despite us being newer to the market over a legacy player is, number one, we have super strong native integrations that really suck in all that key upstream information that you need for AI automation really seamlessly into our platform. And then our automations on top produce reporting that's just unmatched in the market. Yeah.
Speaker 5:And that would, yeah, leads us eventually to getting customers like Windsurf, one of the fastest growing AI companies in recent history, is mined.
Speaker 1:Wow.
Speaker 5:And and others to trust Rulet over their current systems.
Speaker 1:Rulet now used by Google and Cognition potentially. That's the best part about a zombie acquisition. You get potentially two new customers.
Speaker 2:Maybe.
Speaker 1:Anyway, I wanna know about, do you want to put a chat box in your product or do you want to use AI behind the scenes and not surface that to the customer? Whenever I I see tools like this, I think I love the idea that you're using AI, but I don't wanna open it up every day and prompt, hey, clean up my ERP. I want you just to do that. And then when I show up, I want it to look like a nice groomed garden.
Speaker 5:Yeah. Love it. Hopefully, a bit of both actually. So for very important for our controllers, accountants, and CFOs, having a human in the loop on some of their AI processes is actually really important and a positive. So, yes, these are background processes, but always with a human in the loop for the most critical ones Sure.
Speaker 5:There. And then for you, as a business owner specifically or a strategic CFO or investor, you want none of that detail. Right? You wanna go in in a clean box, ask a question, get the information you need, move on. So we're building both to both ends of these spectrums, and you really need both to be successful here.
Speaker 1:As far question is a lot of people wanna go a lot of CFOs, lot of investors wanna go into the ERP, the accounting suite, and get information. But I feel like 99% of the time they're asking for the same thing. They want a really clean balance sheet, a really clean income statement, a really clean cash flow statement. And they don't wanna think of a prompt like, oh, I want let me describe to you what a balance sheet it's like, I want a balance sheet. I just want it to be accurate, and I want everything to be tagged correctly.
Speaker 1:I my prompt is don't make mistakes. So talking to me about the trade off there.
Speaker 5:Yeah. Yeah. Great question. So definitely, there are these pre canned reports. You don't wanna be teaching an AI to rebuild your income statement every single fucking sorry.
Speaker 5:I swear. Every single time every single time the same way. And so I 100% agree there. There are a lot of more custom analyses though that you want if you're a professional, like specific for your business. Maybe track also some non GAAP metrics and and and non accounting metrics on the financial side that is really handy to just describe it in natural language and get what
Speaker 3:you need.
Speaker 1:Yeah. And then the other question is, like, I feel like one shot prompting in this context is even less relevant because if I if I'm if I'm designing a new non GAAP metric, I probably wanna say like, set up a workflow so we produce this every month and that it's just on
Speaker 2:Like vibe adjusted EBITDA?
Speaker 1:Exactly. I want to I want to vibe code an adjusted EBITDA but then I want it to be the same every month because when I've reported non GAAP metrics in the past, like churn, I mean, even DAOMAO, that's a non GAAP metric. But, like, you want it to be accurate and you want it to be classified the same way because there's often these times where you change one underlying thing in your in your product, and then that flows to a complete change in the non GAAP metric. And then you're you're going, hey. It was a non GAAP the whole time.
Speaker 1:Don't worry. Don't get mad at me, investors. I know you thought that that was never gonna change, but the metric changed, and and it's actually not that different for the we're just looking at the business in a different way now. But talk to me about, like, how AI can improve the development and ongoing maintenance of non GAAP metrics.
Speaker 5:Yeah. Great question. So there is definitely an element of, like, repetitive adjustments, certain things that can even be codified outside of AI in terms of certain customizations of your non GAAP metrics. ARR is a very prominent one for soft AI businesses, recurring revenue businesses, for example. Yep.
Speaker 5:And so there, yes, it is definitely something you can do basically in the UI, customize your metrics the way you want it in a repeatable fashion. But there is definitely also an element of certain workflows, I always call it openness to human interpretation, where you need need these more like LLM driven workflows that help interpret maybe look at each chart of accounts, look at historical transactions, what happened there, and try and make sense of things. And that's where AI today is very powerful. But, again, you do need usually a human in the loop to do these, repeatedly and reliably, just given the mission criticality of their workflows.
Speaker 1:What's next? What's more important for you? You're in the mid market. Do you wanna go downward, upward? Do you wanna expand and offer go multiproduct?
Speaker 1:What what what's most interesting to you? Yeah.
Speaker 5:Yeah. So for us, more of the same. The opportunity that we have in the mid market is insane. Yes. The amount of customer love we're getting and product quality that we have with the reviews that we have, combined with, like, really entrenched and, frankly, universally disliked ERP systems, you'll be hard pressed to find someone that truly enjoys using their accounting system or ERP.
Speaker 5:That creates a huge influx of just demand on on the product and and the company. So what we're gonna do with the money that we're raising is double down on product, build more of the same additional features, go up market from here Mhmm. With the money that we've raised. We have a stronger balance sheet to, like, catch capture even bigger names and logos that can work with us. And then the other piece is just in investing heavily into our customer success and onboarding motions.
Speaker 5:We're just like, we work with very talented accountants in these teams to help onboard help onboard their plat the Relip platform into their systems, and we're massively expanding these teams to just absorb the demand that we have.
Speaker 1:It's awesome. What a what an opportunity. It's great. Yep. Congratulations and good Many
Speaker 2:people have have tried and Yeah. And failed to rebuild the to build the new ERP but
Speaker 1:There was a gap in the pre AI era where there were a lot of people that took a run-in it and it was it was a little rough. Finally.
Speaker 5:Yeah. The mind share is there. The opportunity is here. It's it's really exciting.
Speaker 1:Amazing. Congratulations. Congratulations. We'll talk to you soon. Have a
Speaker 2:good day. Cheers.
Speaker 5:Thanks for having us. Bye.
Speaker 1:Round of applause for cover ARP. I didn't like the way he was talking about NetSuite. I would die for NetSuite. I would die I for love I love all systems equally like my children. I like them all equally.
Speaker 1:Anyway, Perplexity, you mentioned it briefly. It's now worth almost 15 times JetBlue. They raised another $200,000,000.
Speaker 2:1 and a
Speaker 3:half 20,000,000,000.
Speaker 1:A little under. Yeah. I think SNAP's at 13. But Perplexity is now at $20,000,000,000. It's unreported but it's been leaked by Arfur Rock.
Speaker 1:Who knows if it's true? But he usually gets it right. So we're chatting about it here. A 138,000 people saw the news. I'm sure Arvind will comment if it's fake news.
Speaker 1:But in other news, what else do we have? We wanted to send our regards to the Doge staffer who was assaulted or or gotten a dust up with someone who was attacked. He stepped in and fortunately we saw another picture that he has been cleaned up and healed and seems like he is on the mend and so sending our best to Mr. Rough.
Speaker 2:But sounds like he acted with
Speaker 1:Courage and bravery.
Speaker 2:As this coacher would say bravery and courage.
Speaker 1:Yes. And back at it. That's pretty much everything, Jordy. I don't know if there's anything else you wanna cover. That's good
Speaker 2:place to send it.
Speaker 1:Maybe leave us five stars on Apple Podcasts and Spotify. Maybe Thank you to if you've been in the chat today. Like this post from Aidan Beltsky says, timeline not in turmoil. John and Jordi pulled off some s tier handshakes during the Figma IPO
Speaker 2:livestream. Stakes.
Speaker 1:This is what it's all about boys. Keep it up. Thank you from the chat. That's on the x chat. And Mark is
Speaker 2:Live handshakes.
Speaker 1:He's laughing. Stakes. We've seen viral botched handshake slash dap ups. You gotta have a shared language. Stick to the default handshake.
Speaker 1:It's Lindy. It's not going anywhere.
Speaker 2:Do you think it's better to look at the person's eyes or the hand coming in? Because I think it might be more about like a like kind of you don't actually You wanna keep the
Speaker 1:I think it's kind of coming in. It's kind of like a a game of rock paper scissors. And so
Speaker 2:It's a high stakes
Speaker 1:game of rock paper scissors. But optimal the optimal strategy is to just stick with the handshake and never deviate, never never never doubt yourself.
Speaker 2:I'm with one of these.
Speaker 1:Make it very clear from early on you're coming in with the handshake and you're not blinking. It's a game of chicken. So, you come in with doesn't matter if you come in with knocks or you come in with with the I'm gonna hit you here. It doesn't matter. As long as you stay here forever, they will see that you're not backing down.
Speaker 1:They'll conform. Yeah. And you'll assert your dominance.
Speaker 2:Yeah. So, go out into the world and practice Yes. Practice live.
Speaker 1:Yeah. I mean, it's tough because I hit people with all sorts of different things. Every time I go to the bathroom, Ben hits me with the knuckles on the way back. It pumps me up, gets me back on the stream.
Speaker 2:Back in the game.
Speaker 1:Alright, Thank you to John Exley for moderating the chat. Fantastic work today. Thank you to Gabe for chiming in with hilarious comments all stream. Thank you for Mark for watching and enjoying the stream. We will see
Speaker 2:you tomorrow. Tomorrow's gonna be an absolutely insane day. We can't say why but it's gonna be insane.
Speaker 1:Something's gonna happen tomorrow.
Speaker 2:And I cannot wait.
Speaker 1:I'm pumped. It's a stacked lineup. We will announce it soon. See you Bye. Cheers.