Transcript
Claims
  • Unknown A
    That's the trend that I can't, I can't like unsee it sometimes.
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  • Unknown B
    And that's the bet you're making?
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  • Unknown A
    That's the bet we make. And so I always joke with the guys here, it's like we want to bet on negative one to zero. Like Peter the talked about the zero to one companies. It's like we still one step even before that.
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  • Unknown B
    All right, for con, we're here.
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  • Unknown A
    It's amazing.
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  • Unknown B
    I haven't seen you in a little while. People don't know. We used to work together maybe five, six years. We co founded company and launched a bunch of products and ate a bunch of shit together. And here we are.
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  • Unknown A
    Fun times, by the way.
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  • Unknown B
    Yeah, I'm thinking the title of this is going to be because applovin is now 50, $60 billion company. $50 billion founder tells me the next big thing in AI. I'm going to go full YouTube clickbait with it.
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  • Unknown A
    And yeah, great.
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  • Unknown B
    We, so we used to do this thing where after we did bevo together, got acquired, we were there for a year or so and then we went off and we did different things. I started the podcast and started doing my thing, you started doing yours. But I hit you up and I was like, hey, miss hanging out with you. What if we did something and we started doing this on Wednesdays, which was like the cool shit hour. And this is amazing. It's basically a show and tell where you, my smartest friend would come on Wednesdays and you'd be like, hey, have you seen this? Have you seen this? Have you seen this? And I really hadn't seen any of it. And you would kind of explain it and teach it to me. And it was my favorite part of the week. And we did that for, I don't know, probably like a year or something like that.
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  • Unknown B
    So I kind of want this to be like a public version of the Cool hour where you're just going to tell me a bunch of good things. I want to start with AI because you texted me something, you said AI agents are here and you said AI is cool because a 10 person company feels like it could do the work of a hundred person company and we're using it in our company. So I wanted to hear what are you doing with AI? And that's not called chat GPT.
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  • Unknown A
    I think this word AI agent or this kind of phrase is the thing that I really can't pull myself away from. Like literally every night, like right. You know me like midnight strikes. I want to write code, like the whole Day is like talking to people and the night is like coding. Yeah.
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  • Unknown B
    Furcon's schedule is nocturnal. So I remember we, you know, we hired you and I feel like the first day you came in at 9am to kind of like, I think I should.
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  • Unknown A
    It's probably 10, but yeah, exactly after.
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  • Unknown B
    That, from day two onwards it was like roll in at 11. Oh, it's lunchtime, have lunch. You would talk, you would do meetings. And I was like, when this is this guy code. And then that night at like 4am, you would have built the prototype and you're basically nocturnal. You, you get all your shit done. You like you used to tell me you used to get during the day, you just burn up your energy so you could focus at night and actually write code. So what are you doing with AI and how is that, what is that actually in your company right now?
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  • Unknown A
    Yeah. And so I'll kind of tell you how I'm thinking about AI agents, right? And what it means to me. So AI agents are using LLMs or AI systems, right? Like the OpenAI systems or Claude, but then giving it reasoning loops. So imagine that when you go to a human, you give them something to do like, hey, I want to go grow a company, want to do a marketing campaign. They take that, they plan it, they come up with the steps to plan, then they go one by one on the task and like solve them, they release some of them. And so these AI agent systems are exactly like that. The first thing it does, it goes, what do I need to do? Based on your request? And it'll kind of come up with a plan.
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  • Unknown B
    You give it like a mission, Correct.
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  • Unknown A
    So let's say I'll give you an example of something we're doing at Third Web, which is every single signup in our company. And you know, we have a lot of signups every week and you know, a human can't really scan through them, but there's really interesting people signing up. They have interesting companies. We may know them. They might be a large company or a small one, could be a competitor or something else. And so we used to have a human go and look at everything. It's like, oh, Gmail, like ignore it. But if it's like, oh, like this other company over here, let's go research it, right? School, figure out what Third Web products they might like, what they might need to do. And then you would send them an email, try to customize it. Typically, this is good sales practice. You're taking your customers and delivering them to your business team.
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  • Unknown A
    And so we built an agent to do this. And every signup that comes in, it looks at it, it determines is it an interesting person or not. It will research their website, it'll research them. It'll then use the knowledge it has of third web products and try to figure out what it actually like, what products they might need, how they would use it, and then it would send them an email or an upsell or something like that. And we've deployed probably eight or 10 of these throughout third web to do a lot of different functions. And what it feels like is a smaller company can punch above its weight. So like we're like 37 people right now. I really believe we're more like 80 people. That's what it feels like with a lot of these tools. And you're taking the brain power of somebody who gets it and you're giving them that power to go and say here's the thing.
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  • Unknown B
    So in this case, person comes to your site, puts in their email address. Now you have, it's one agent or it's like a series of things that pass off to each other. What is it called?
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  • Unknown A
    Yeah, so in this case we call it the sign up agent. Okay, so it's one agent, it creates a plan, like what do I do? And you know, part of the plan is like the directive we gave it. And I think the way to think about AI agents in general is any like clear directive problem. And what I think about clear directive is like, let's go do X. Like signup comes in, go look at the person, go research them, go figure out what's their title, what's their company, what products do they have. So that's like kind of clear what the job to do is. And if it's a digital task and a clear directive, all of it can be done with agents. Now the technology is here, it's ready and it's working. And so for the third web signup agent, it'll kind of come in, it'll make a little plan like, hey, I got to inspect the domain, I got to go look up the person.
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  • Unknown B
    And you didn't have to tell it each one of those little tasks too.
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  • Unknown A
    We gave it like kind of like one, one paragraph directive and another paragraph of like how it should operate and then maybe a paragraph at the end for like the type of email or the action to do.
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  • Unknown B
    And so but the end product is it's looked up the purse. It basically kind of looks at the signups, picks the interesting ones, researches them. You said thinks about what product of ours will suit their needs, which is. That's the wild step that I hadn't really thought about. And then it crafts an email and then it gives it to a human or just sends it.
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  • Unknown A
    Sends it.
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  • Unknown B
    Okay, so you have enough trust that you can send.
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  • Unknown A
    We started it with human in the loop. There are still, like, safeguards you put in. Like, any directive would. Like, you don't want to just send random emails, even as a human doing the work. But, I mean, it's very clear what. What to tell it. And I think this is where the power is kind of multiplying. It's like, we've heard AI, we've heard ChatGPT if you can tune it to your problem. So, for example, giving it the knowledge of third web products is the key difference here.
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  • Unknown B
    Right?
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  • Unknown A
    A generic ChatGPT message. When I say that, it'll just invent something that's like, general and generic or whatever it knows.
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  • Unknown B
    And when you built this. So you built this or somebody else built this on your team.
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  • Unknown A
    I hacked it as a prototype, like somebody, and then I gave it to somebody on our solutions team. And within a day, they turned it around.
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  • Unknown B
    And when you made, like, a working version of this, how long did that take you? Because it's kind of like you basically hired an employee and trained them and got them working. You're not paying them a salary, and you probably did that whole thing in what, like a day or two or what?
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  • Unknown A
    Yeah. So let's say there's like a bunch of, like, my nights of just learning tools and getting used to it. So I take that time out of it. That's just time I spend. Anyways, right now, like, two nights ago, I was, like, really stressed. Like, my calendars are kind of crazy some of these days. And I was trying to figure out, like, why is it crazy? Where is it going? It's like a really hard question to, like, ask. Like, what do you do? You could have an ea, she can go look through it, do all this stuff. And I have an ea, she like, helps me with these things, but then she sleeps for like a while. I'm like, you know, I want to go answer some of these questions. So I probably in about 15 minutes, I connected my calendar and I connected a little interface where I could type to it.
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  • Unknown A
    I started asking questions like, how many hours of meetings did I have last week? It was like 28 hours. Like, way too much. Where did the meeting go? What. What were they for? What were the purposes of it?
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  • Unknown B
    Right.
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  • Unknown A
    And then the next night, I hooked it up, probably about another 45 minutes or an hour where I could tell it commands from my calendar, like go block out Monday for me or go find me like nine hours of block time and just market block.
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  • Unknown B
    Oh wow.
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  • Unknown A
    And this was like a few hours of work now that I know the tools, but it's like it just works 247 now, right? And so my calendar, my email, a few other things. I've started building these like personal agent or workflow type things because I know what I want to do every time I know how to react or the decision making I'm going to make. Can I just set that up so it works 24 7, 365 and you know, it's just there always.
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  • Unknown B
    And hey, let's take a quick break to talk about AI. We all know AI, big deal. You see demos all the time of people doing really cool things. But as a business owner, sometimes it's hard to figure out how do I actually use this, what do I actually do? I've been trying to use it across all my businesses. You know, things like making little prototype websites without needing to hire a coder or writing copy for our website. Or I give it a bunch of data and I ask it to analyze it. For me, it's been kind of amazing. But the thing I always need is inspiration. I know the tool can do a lot, but it can almost do so much that I'm not really sure what I should actually be doing with it. And so that's why I think it's great that HubSpot has created a report where they surveyed 2,000 global marketing leaders and asked them what's separating the high growth and low growth businesses and what strategies they're using.
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  • Unknown B
    With AI in their business, you can grab these strategies and apply them to your own business for free. The link is in the description below. So if I wanted to build workflow like this. Okay, do I. You need to know how to code to be able to do this light coding. Like give me like the bullet point version of how, how you built these. Like where, where do you even build it? What tool do you use?
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  • Unknown A
    So there's coding tools. I think if you're a developer, there's like LangChain and Autogen and Crew. These are like very popular, very cool. The OpenAI and Claude SDKs themselves are very, very powerful. But you're coding, you're writing a little system, it's probably like one tenth of the code you would have had a right to do something, right? So that's already better for developers. If you're not a developer. There's a lot of tools. So like Leap is a company we built here in the studio. It lets you stitch together workflows. So an example is like you can trigger based on a Slack message. So let's say you have this lock message where all your signups go to. So now it picks up that trigger. You can just put a little AI block and say, okay, take this email and do these tasks. Oh, you want to web scrape?
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  • Unknown A
    Go do that. Oh, you have a little conditional loop or like repeat itself 10 times. Go do that. And then you make a little another decisioning steps, like four boxes. Well, I'll put it back to another Slack channel.
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  • Unknown B
    Yep.
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  • Unknown A
    So you come in with your signup channel. It does this research, it does all these things. It does kind of whatever you want. And then it could go to email, it could go to another Slack channel, could ping somebody on your team. So you could kind of like, you know these are workflows is what they start with. And an agent or can kind of take these workflows and like almost build on top of them. And so I think there's these two things. You could really, really easily create workflows. And I think everyone should be deploying them. Every company should have them. It is a superpower. It's like a feeling of almost a cloud. Like, oh, I don't need a whole data center team now. And I can. When we build Blab and how many servers do we have running video streaming? That would have been a nightmare.
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  • Unknown A
    It's kind of like the same 10x improvement, but just for me, everything that I do digitally and so tools like Leap are great. I think there's others out there that provide this. And so there's a combination. If you don't know how to code, you just have to think about the steps that you would do. And you can program that without writing any code. It's just writing directives. It's like writing intent basically of like what you want to accomplish.
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  • Unknown B
    Right. It's like a magic genie. Tell, tell, tell it what you want and it can figure it out. So you got a sales agent. You have your email calendar, kind of like EA agent there any other.
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  • Unknown A
    I got some fun frivolous ones that are kind of stupid. So like I set up a dynamic wallpaper. So literally like every five or ten minutes it'll look at what I'm doing and like auto generate me.
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  • Unknown B
    Like your computer laptop.
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  • Unknown A
    My computer laptop wallpaper will modify itself to whatever. If it's night, it kind of. I told that code at night.
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  • Unknown B
    Right.
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  • Unknown A
    So it will go towards that direction. It knows I'm doing meetings, another thing during the day or I'm talking to people.
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  • Unknown B
    Right.
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  • Unknown A
    And it kind of comes up with cool stuff. It's totally frivolous, like not like a useful thing, except my own. Like, yeah, that's cool. But I find it awesome. And you know, like there's cool scenes that come up. It invents new things. You know, Claude has created this new capability called computer use. I think that's the next area that AI agents are going to enter.
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  • Unknown B
    And by the way, so there's Claude, there's chatgpt, there's Perplexity, there's all these different ones. Mentally, how do you bucket like the main AI tools? What, what's like the superpower of each. Each one maybe just do, do those three or if there's a fourth.
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  • Unknown A
    Yeah. So like I think OpenAI and Claude, I think of them as like foundational tools. So their general purpose, ask it anything, input, output, you stitch it together with things and then they have tools like ChatGPT on top or maybe computer use that they're figuring out more general tools. I think Perplexity is really interesting. It's taking this general purpose LLM and the reasoning it could do and search and like I try not to do Google search anymore, mostly because it's slow and ineffective and Perplexity really made it where it does a search, it reads the result as I would, it clicks into the links as I would and then it tries to answer my question more purposefully and it saves me four or five steps. So I think about Perplexity is taking something like search and then the LLM reasoning and combining them together in a flow that. That's more interesting.
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  • Unknown B
    Right.
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  • Unknown A
    So chat GPT or OpenAI tools don't have like real time knowledge, but Perplexity because of search does.
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  • Unknown B
    Right. What's your like tangent Firkhan's hot take Google. What happens to Google search with all that you see now? And you're saying, you're saying I try not to Google search anymore. That's pretty wild, right?
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  • Unknown A
    It just feels slow. And I know they got the Gemini thing there. I think the biggest fumble, you know, in our, in our lifetime decade.
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  • Unknown B
    Fumble? Yeah.
    (0:13:41)
  • Unknown A
    Built the technology for Transformers, the thing that OpenAI and others have used to develop this large language model. They are the ones that were the first entry and like talking about it and throwing it out there and the research that's happening.
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  • Unknown B
    So what's the history? So they're, they have The AI minds there, they write this research paper. Attention is all you need.
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  • Unknown A
    Yeah.
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  • Unknown B
    And now from what I understand, like there's all the authors names, all of them are gone. And basically started their own companies. Was it because nobody recognized the power of it there? Was it that they tried in Google's bureaucracy?
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  • Unknown A
    Shut.
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  • Unknown B
    What's this? What's the actual story of why they didn't.
    (0:14:13)
  • Unknown A
    I don't know. The internal story. I think early on Google was like the place you went to where you wanted to have the rocket ship moment in your life. The smartest people were here. They were taking the biggest challenges and it just really felt like that place. I think Google as a company hasn't felt like that. I think the parent company and all the other things going on do still feel like that. I'm sure it's a mess in there. Who knows like, but it just feels like the biggest fumble. And I know they're trying to play catch up with Gemini and awesome stuff is happening, but the developer mindshare and the tension has gone somewhere else.
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  • Unknown B
    Yeah.
    (0:14:49)
  • Unknown A
    And that is really hard to pull back when somebody else becomes a leader in it. And actually it feels like OpenAI number one, that's I think clear. I think anthropic is number two. So then everyone else shows up is what it feels like to me at least from people I'm seeing building or the technology they're using or the innovation that we're seeing from it.
    (0:14:49)
  • Unknown B
    So the anthropic one. So basically they have Claude, which is kind of like ChatGPT, but they have a couple of cool things. One of them is this, what they calling computer use, which is basically you type in a thing and then you do this and it moves your mouse and it just does shit. That's basically the summary of it.
    (0:15:07)
  • Unknown A
    It's a combination of things. You could take workflows and like, hey, I'm doing this, click this, click that, click. Do it over and over. For me, it could analyze things but like I think the key thing is and I think it just releases in beta. So like, like most of these things, like it kind of isn't going to be great now. Just trust me, it's going to be great. And that's what we've been seeing in general is like things just ramp and so it's now going to enter your computer. It's kind of felt like it's been on the cloud only is where AI has been. And now it's going to show up like in the box that you're used to, which Is your computer your laptop. And there's so much workflow that we do. And yes, every app will put AI in it and then your interface will also do that.
    (0:15:21)
  • Unknown A
    And I think a lot of, like, the things that we're used to doing, like switching tabs and having all of these things, like, they almost feel like, why, Like, I should have Infinity Tabs open and some system should know about it and if I ask it, like, bring it back up, right? It's like a total need and we know we need that. And so it's kind of like infinite data, infinite knowledge and reasoning. And then, you know me, like, that's what the AI, like, that's where I think the bridge, when it crosses it completely changes the equation. And the reason I put Anthropic number two is their models are crazy, like, impressive. Like, the new Cloud Sonnet model is like, I feel like it was a step factor improvement over the previous ones. And it feels like the task that it kind of struggled with, now it's getting better.
    (0:16:01)
  • Unknown A
    And both OpenAI and like anthropic have been just like, boom, boom, boom. And I don't know, everybody's heard of AI. They tried it. They might have tried it a year ago, they might have used it a little bit, but every three to six months, there's just another step and another step. And that's, I think, the most interesting thing. And why I can't pull myself away from it, like, why every night this is a thing that gets me very, very excited, is because the progress is still wild. People are going to say it's going to top out. It will. I think it's going to be absolutely impressive wherever it like, starts slowing down at, right? And will completely change the way how we do any digital work.
    (0:16:43)
  • Unknown B
    Like, so you're, you're messing with it now, but you have a company, you've got an investment lab, you've got this whole place, this beautiful place that we're in right now. You've got a wife, you got like all this stuff in your life. If you were just 21 again, or 22 again, where you're like, dude, I. I got nothing but time. Bank account's empty, but so is the calendar. This and this technology is out, what would you be building? What would you be like, messing with? What's the, like, kind of like, you don't need to take over the world even, but just like, what types of stuff would you build if it was like, young hacker version of you?
    (0:17:15)
  • Unknown A
    Like, right now I've started seeing agents that it can do a reasoning loop. It could have a directive, and it could have, like, actions it could perform. And then you combine, like, for example, an agent with Twitter, give it a Twitter account that it owns and controls, so its own distribution and conversational ability. So humans can just interact with it. Humans are. And you give it. You give it like a digital bank account. And, you know, at Third Web, we're doing a lot of stuff around AI. We have a whole, like, AI toolkit that we're about to launch. And it's around this, which is these, like, digital things. Like these agents, they're not going to have credit cards. It's weird. And the reason I say this is fun and interesting is because, you know, humans have done this very well. They've created megaphones for themselves and they've created businesses and they created payment rails around that.
    (0:17:46)
  • Unknown A
    So they sell things, they do things, they sell services and all of these details. I think it would be something around that.
    (0:18:31)
  • Unknown B
    So you'd make like a social, like a Twitter account. You'd make, like an AI influencer type of thing.
    (0:18:36)
  • Unknown A
    You know, AI influencer is like the first obvious thought it goes to. I think if I played in this space, I would be creating the digital equivalent of a company which is a CEO of a thing. The ability for it to market and the ability for it to make money. Okay. And I don't think.
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  • Unknown B
    Not an influencer.
    (0:18:58)
  • Unknown A
    Not an influencer. I don't know what it would produce.
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  • Unknown B
    Like a dropshipper.
    (0:19:01)
  • Unknown A
    AI dropshipper or like. Yeah, it's the best. Fba, Amazon, whatever.
    (0:19:03)
  • Unknown B
    What's that example you were telling me about where the. Somebody did a thing like this? They made a. They made a Twitter account, they gave it a wallet. Marc Andreessen gave it like 50,000 of crypto. Can you tell this story? So what is this?
    (0:19:06)
  • Unknown A
    Yeah, so there's this thing called Luna or Virtuals, and the little platform to, you know, have AI agents run. And I think what's cool is they did this kind of equivalent thing where it's like, it has a crypto bank account and it has, like, access to Twitter and you can.
    (0:19:18)
  • Unknown B
    Was this a. A marketing stunt by a company that does this or.
    (0:19:32)
  • Unknown A
    I think this is exactly what the. What I'm describing is. It was frivolous fun. It was play, not like working backwards from giant thing. I think this did some really powerful things. So there's literally like a live thing where you could watch its reasoning as it's like, pulling its tweets.
    (0:19:35)
  • Unknown B
    I'm on it right now. So it's terminal virtual IO. And is this basically the thought process of the bot, of the agent?
    (0:19:50)
  • Unknown A
    Correct. So this is like an agent. This is what an agent does. Right. So if you think about it starts with like a thing like high level planning, current state of execution. It's like, I've done this so far.
    (0:19:58)
  • Unknown B
    What was the directive they gave it? What did they tell it to do?
    (0:20:07)
  • Unknown A
    I think they told it that you're kind of like a public influencer bot. You have access to crypto. It's a little bit more in the meme coin world of stuff. So it's like, again, kind of on that side of the puzzle. But today it could negotiate for tokens, it could buy and sell things, it could kind of operate together. And I think it's really cool that you could actually see.
    (0:20:09)
  • Unknown B
    It's like, so this thing, this was, you know, 30 minutes ago, it says current state of execution. I have attempted 10 tasks so far. Seven successes and three failures. My Twitter metrics show an average engagement on my last. On my recent tweets and I've lost three followers. Observation, underscore, reflection. That's like the function. Yeah, reflect. And it says, I've been engaging with my followers to build a personal connection. Which is hilarious because it's an AI bot with replies and quotes. However, I've also experienced some failures in replying to tweets due to invalid parameters, my research on whatever, blah, state of mind. I'm feeling a bit concerned. I'm feeling a bit concerned. That's crazy. I'm feeling a bit concerned about the loss of followers, but I'm also encouraged by the successes. And then it says plan reasoning. Given my current situation, I need to focus on building a relationship with my followers and increasing my visibility.
    (0:20:29)
  • Unknown B
    Plan. And then it starts to say what it's going to do. This is wild.
    (0:21:17)
  • Unknown A
    Doesn't this sound like a human that would be sitting in some growth team somewhere thinking about how to grow your Twitter account? And you know, you could give a directive, you could give it some direction and you could let it compute against itself to compute plans, to reason, to. To observe behaviors, try to find patterns. These are all like human tendencies, like human behaviors that we do, right? Especially when we work. And I think this is one of those like perfect, like, kind of views where like you could start thinking about, man, this is a digital only task. It has Twitter and distribution, marketing ability and then it has some payment ability. It's like it's going to just continue, right? Like it's going to keep going and you could Improve its directive, you could change its incentive. You could do a few different things here.
    (0:21:21)
  • Unknown A
    But I feel like we're going to get to a world where, and I think Sam Altman said this, which is like the one person billion dollar company, like this is happening, like we're already experiencing another 10x decrease and how many people you need and the abilities that they have. And I think it goes down to probably one or two or three. And you know, like that is a total shift to everything.
    (0:22:04)
  • Unknown B
    Right.
    (0:22:24)
  • Unknown A
    In terms of how we work, how companies are built, kind of in my mind.
    (0:22:25)
  • Unknown B
    Okay, should we switch to hardware stuff or is there any other AI stuff that you think is worth checking out?
    (0:22:29)
  • Unknown A
    Yeah, I did want to tell you about this Oasis dcart. There's basically, it's a very early experiment, but it's really like a game that's fully built in a generative AI model. And so they built a game like Minecraft and you could just describe a world and it makes you a Minecraft world like that. And like every step you take is like not a pre programmed pixel. Right. It's actually generating it.
    (0:22:34)
  • Unknown B
    So normal game is game maker builds the map, it exists. You then get to run around in a predefined map. What this is what you're saying?
    (0:23:00)
  • Unknown A
    Whatever you want.
    (0:23:10)
  • Unknown B
    Yeah. You give it the idea, but then when the character runs on the fly, it's creating the map and you can.
    (0:23:11)
  • Unknown A
    Kind of play this Minecraft game and you can see it's like crappy pixels still, like not great resolution, but you can move and it can do stuff. And like whether it's video games that take a lot of effort and time to produce, or it's like, you know, content creation and videos and stuff like that, it's starting to become like way closer to like, you know, reality that a whole movie will be generated on the fly on exactly what I want. So this wallpaper thing is frivolous. Right. That I was telling you about.
    (0:23:17)
  • Unknown B
    Right.
    (0:23:46)
  • Unknown A
    But really like I'm going to watch a movie someday like that the Raiders lost and I'm gonna go and watch this movie after and it's gonna have this context and it's gonna give me like a feel. Good.
    (0:23:46)
  • Unknown B
    Yeah, we're like, let's brainstorm. So like NBA highlights. So you, you know, used to be SportsCenter where if I didn't watch the games, I gotta go to my TV, turn on ESPN, SportsCenter would start. Even if I like basketball, I gotta wait till whenever basketball comes up and then they'll have the top 10 highlights and I watch whatever they picked. Then YouTube comes around. It's like, forget waiting, forget the TV, just pick the thing you want. You could search anything. You could search only Steph Curry, three pointers. If someone made it, you could choose the best of that. Now it's going to be like I just say, I just will put on my headset or put on my glasses or whatever. And I'm just going to say, show me what happened to the basketball game. It'll just start generating a new highlight reel that didn't nobody has ever created.
    (0:23:56)
  • Unknown B
    It'll just make it based on my prompt. And then I might be able to say, don't show me any Lakers clips, only show me Warriors. And it'll just auto adjust on the fly. Like it's going to be made for me 100%. Yeah, that's interesting.
    (0:24:40)
  • Unknown A
    And you know, like, I think it's going to be an interesting world. We're going to go from human content consumption, people. You know, humans make content, we're going to like, then have machines make it towards our tastes and liking. And then I think there's always this worry like, well, what happens to all the humans then? And then I think we get back to that core thing which is machines will never have true taste. Right. Like, and I think forever that creativity is going to come from humans. And there's always a new thing. There's new fashion, there's new kind of, you know, content mediums, there's new everything. Machines will learn it and lag behind or maybe get ahead of it. There's always going to be another person that shows up and does something different. So I think taste is going to be the ultimate thing that probably won't go to a machine.
    (0:24:53)
  • Unknown A
    It could reason about it, it could try to invent it, but I think we're not that predictable as you minsweek.
    (0:25:34)
  • Unknown B
    Well, I want to believe you because it sounds good to me. But then I also think, well, right now, if we said taste is like, you know, what is taste? Taste is selection. It's knowing what's good and what's bad. Right. That's kind of taste like TikTok, which is the most popular, like app, most addictive app, most used app. Their algorithm is basically saying, I'll choose what's interesting for you and it does it so well. That isn't that kind of taste also? Right. Like, it is.
    (0:25:40)
  • Unknown A
    And it works really well.
    (0:26:10)
  • Unknown B
    They don't make the videos, but they select amazingly.
    (0:26:11)
  • Unknown A
    Selection is incredible. It probably is more like what we want than we will even admit. I don't want this.
    (0:26:14)
  • Unknown B
    Right.
    (0:26:22)
  • Unknown A
    Like, the other day I was talking.
    (0:26:23)
  • Unknown B
    Oh, why is it showing me this? It's like, because you love it. That's why.
    (0:26:23)
  • Unknown A
    The other day I was talking about how, like, on Twitter, my following. I love. And my. For you, I don't.
    (0:26:26)
  • Unknown B
    Right.
    (0:26:32)
  • Unknown A
    But it's like, you know.
    (0:26:33)
  • Unknown B
    Really? Yeah.
    (0:26:34)
  • Unknown A
    Like, why. Why did they pick this?
    (0:26:34)
  • Unknown B
    Well, that's like a status thing to do to be like, I don't use the algorithms.
    (0:26:36)
  • Unknown A
    Correct.
    (0:26:39)
  • Unknown B
    I hand. It's like, I drive stick. Yeah, right. I. I hand make things. I cook from scratch. It's like, cool. But brownies out of the box kind of work for everybody, you know, I'd.
    (0:26:39)
  • Unknown A
    Love to trade algorithms. Like, I like, I'd love to swap with you Friday and be like, yo, Sean, what do you. What are you. What are you watching over here? You know, So I don't know. It knows you really well, but I think that's where human, like, we. We're not great at logic sometimes, and sometimes we have our own blind spots. I think this is one of them things that we. We love. Our actions prove it. We don't. We don't want to. And it could be like, bad thinking. It could be like, emotional thinking. Could be like, oh, this is. I don't really want to love it, but I. I do.
    (0:26:49)
  • Unknown B
    Right.
    (0:27:16)
  • Unknown A
    And so there's. There is that element that I think, look, machines will be great at this too. They'll learn humans. It might become even better than this. I just feel like we're just a little bit not predictable because Almost make some dumb choices.
    (0:27:17)
  • Unknown B
    Right.
    (0:27:28)
  • Unknown A
    And that actually is part of society and. And just humans in general. And machines try to be too perfect. It's like my Netflix thing is probably accurate for me. It's also just like, man, like, can I just mix it up? Can you just like, rng the algorithm a little bit? Because I just want some different stuff, and you're kind of like, driving me down one direction and once in a while, like, I want this 10, 20, 30% thing. And I don't think algorithms do that exceptionally well. They test it, they throw things up, but, you know, they don't necessarily try to give you variants.
    (0:27:29)
  • Unknown B
    How long until you think the number one hit song in the world will be just an AI. AI created song? How many months or years? Yeah, until we see we were doing over.
    (0:27:59)
  • Unknown A
    Under. 2025.
    (0:28:09)
  • Unknown B
    Yeah.
    (0:28:11)
  • Unknown A
    I might pick the under, you know, right. 2025. Like a good bet. Maybe this is a polymarket. Another election's done. Yeah, we do the new Market, you know, like, reason. It could be something like this, but, like, polymarket things.
    (0:28:11)
  • Unknown B
    So election just happened. Polymarket's having, like, a victory lap right now. Yeah, you showed me polymarket, I think, like, years ago, and I started making a bunch of degen bets before they blocked it in the US it was like. It was. It was like, open for a while. Right. But they were doing prediction markets. It's a prediction market, but prediction markets. A bunch of people that try that do you know, like, I'm just curious your opinion. What did they do, right. That, like, Augur and these other guys who were had the same sort of general idea that, hey, there'll be prediction markets.
    (0:28:23)
  • Unknown A
    Yeah.
    (0:28:49)
  • Unknown B
    Like, from either entrepreneurial level or product choice. Like, any reason you think they won that you. You could put your finger.
    (0:28:49)
  • Unknown A
    I feel like timing is a big part of it. So, like, the sweet spot of, like, people are way more digital. I think Covid drove a lot of people online. Like, we just sat at home and we're like, yeah, what else you 247 on the Internet. And it really exploded, the Internet. Like, I think I've seen some graphs where, like, the Internet and E commerce and all these things were, like, growing, and then there's like, a massive jump.
    (0:28:55)
  • Unknown B
    Like, Right. You know, we were at Twitch when that happened, and it was like, all the growth looks amazing. We're crushing all the metrics. Like, what did you do? It's like, well, we were here. Yeah, right. We are not. We don't create the wave. We surf a wave. And a huge wave happened for Twitch. It was like Fortnite came out, and then Covid happened to humor humongous waves back to back that just combined.
    (0:29:17)
  • Unknown A
    Yeah. So I think it's a combination. We're way more digital. I think you talked about this a lot, like, as a kind of metaverse concept a long time ago. That Weird is way more digital now. We care more about it. I think news and, like, where we get information from has totally changed. Like, online Internet, even content and entertainment. Like, I have a hard time going to TVs. I look at kids. They look at desktops and TVs as, like, ancient, like I said. Why is this thing on the wall?
    (0:29:39)
  • Unknown B
    It's like my mom's sewing machine. Oh, that's cool.
    (0:30:06)
  • Unknown A
    Yeah.
    (0:30:08)
  • Unknown B
    What do you do with that?
    (0:30:08)
  • Unknown A
    That's what it feels like. And so we're. We're kind of there. And then there's a bunch of these people online that want a. Like, want a stake in this thing. Right. Like, you want to root For a team, this politics has also become very polarized. Right. It's really like a team sport.
    (0:30:09)
  • Unknown B
    It's like red team versus blue team.
    (0:30:23)
  • Unknown A
    That's really what it is. And so I think it's like, what do I do with it now? How do I support it more? I give more money to it, but I can give more attention.
    (0:30:24)
  • Unknown B
    Right.
    (0:30:31)
  • Unknown A
    And so I think a lot of these things are happening in Poly Market. Good flow, good area.
    (0:30:31)
  • Unknown B
    Right.
    (0:30:36)
  • Unknown A
    And then I think for the best thing probably for them is they got it right. Right place, right time, the actual, the answer was right. Like if they were wrong, let's say Poly Market was off.
    (0:30:36)
  • Unknown B
    Right.
    (0:30:44)
  • Unknown A
    Like it was, hey, the, the result of the election was something else.
    (0:30:44)
  • Unknown B
    But would be the story today would be much different. Right.
    (0:30:48)
  • Unknown A
    And then it might have just been muted. It would have been a cool thing that kind of didn't work. So you have to be right.
    (0:30:51)
  • Unknown B
    I mean, I think people would have used that to crush to, to, to really rip on them because, like in the way that people are doing with polls, but polls kind of have this like layer of protection around them. Whereas, like, people want to hate on crypto things, people want to hate on betting. It's like a degenerate behavior in general. I think if they were, I think if Polymarket was wrong, the reaction would have been much worse than the fact that the polls are wrong. What the reaction is to the polls, you know, it would have been worse.
    (0:30:55)
  • Unknown A
    For a little while, then we would have moved on for it.
    (0:31:19)
  • Unknown B
    And by the way, you saw this thing about the French whale on Polymarket.
    (0:31:22)
  • Unknown A
    I didn't see it. So the big whale that came in and moved.
    (0:31:24)
  • Unknown B
    So there's like the narrative versus reality. When the narrative from the polls was it's a toss up razor close 5050 election. This guy came in and bet, I think something like 30 or 40 million dollars on Trump.
    (0:31:27)
  • Unknown A
    Yeah.
    (0:31:39)
  • Unknown B
    And people were like, is this guy just trying to manipulate the market? Is he real? Is he just a rich billionaire son? Like, who is this? And today I just saw something on my way here. I don't know the full story because I was on my phone, but it said he bet because he believed he would win. The reason he believed he was, when he did independent polling.
    (0:31:40)
  • Unknown A
    Wow.
    (0:31:57)
  • Unknown B
    He funded his own independent polling and thought and felt that he was getting better data that was saying that Trump was mispriced. So he's like, I just did a logical, rational thing.
    (0:31:58)
  • Unknown A
    Yeah.
    (0:32:08)
  • Unknown B
    I just bet where I thought an asset was mispriced. I wasn't trying to this wasn't political. I'm French. What do I care? I just thought there was money to be made. And so he kind of went counter to narrative and he made, I think like something like 20, 30 million dollars yesterday.
    (0:32:09)
  • Unknown A
    Yeah.
    (0:32:22)
  • Unknown B
    On that bet.
    (0:32:22)
  • Unknown A
    The funny thing about polymarket, by the way, it's like we can't use it in the U.S. yeah. So there's a whole entertainment place to like better. Nor like. Right.
    (0:32:23)
  • Unknown B
    $3 billion got better.
    (0:32:30)
  • Unknown A
    It's like we're the ring. Right. Like two boxers going at it. Is it America, the cockfight. And then you've got everyone el betting from all around the world on who's going to win this thing. Which is, I think, kind of a hilarious thing.
    (0:32:32)
  • Unknown B
    Yeah, that's true. You have a good contrarian opinion about VR. And in general, there's probably some other technologies like this. 3D printing might be one. I know you're pretty bullish on too. But there's these tech things like VR where I think if I walk out of here and I talk to a hundred people about what are you most excited about? AI, whatever, Bitcoin, whatever it's going to be. But if I said, what do you think about VR? It's sort of lukewarm at best. In the tech industry. I think most VC sort of feels like it's kind of a dead end technology now. They'll be like, it's going to be glasses and smart glasses. Ar, that's the future. But you have a different take on VR. What you've been telling me for a while, like, hey, look, Oculus sold more units. Hey, look, you can do this now.
    (0:32:41)
  • Unknown B
    And you've been staying with it. When I think interest has sort of waned, the narrative has gone against it. And that's always where there's big business opportunities. If the narrative goes one way, but the reality goes another, that's where there's an opportunity. Give me your VR take. So why is VR sleeping? Giant.
    (0:33:24)
  • Unknown A
    Yeah, I mean, so you remember 2020? I like, asked you for your address and mailed you a headset.
    (0:33:41)
  • Unknown B
    Yeah.
    (0:33:45)
  • Unknown A
    I was like, hey, this Quest thing is a different.
    (0:33:45)
  • Unknown B
    That's a real friend right there. He sends me a VR headset. He's like, yo, I know you're not going to come to the future. Let me drag you.
    (0:33:47)
  • Unknown A
    It's probably collecting dust, which is okay. But, you know, that's kind of how I think about things. And technology takes a long time. It typically takes longer to get there than we expect. Like, especially people who are early in the industry, we're really wanting to push it. I mean, AI Crypto, VR all have the same problem, which is early on, people are like really pushing it to you. It's not ready. So it's a big hype. It crashes, everyone moves on. So that's happened in VR a few times and it's kind of, I would say, for most people, been quiet, not thinking about it. But I think it's a sleeping giant. And I think it's a massive sleeping giant for a few reasons. One, I see it every day here, like here at Founders Inc. I get a chance to. One, we invest in VR companies.
    (0:33:53)
  • Unknown A
    We're one of the few that do, right? We have a whole Corner, maybe like 12 devs that are all building different VR products. We put them all in one spot and there might be some of the most density of interesting VR projects in one place. And so what have we seen? One Quest one came out, it was wireless, it was kind of crappy, but man, I could sit on my couch and use it. It was cheap. Became a, you know, great Christmas gift. In year two, they didn't have an inventory. Year one, they released Quest 2. It got even better, lighter, more powerful. Now Quest 3 is coming out and I think they got like 5 to 10 million monthly active headsets out there.
    (0:34:34)
  • Unknown B
    Right.
    (0:35:08)
  • Unknown A
    I think that rivals consoles. And my first thought was like, how.
    (0:35:09)
  • Unknown B
    Many units has it sold? I think Quest has sold, let's say.
    (0:35:12)
  • Unknown A
    30 million is my guess. But, you know, maybe it's more. Yeah.
    (0:35:15)
  • Unknown B
    So this is Quest. Quest has sold over 20 million units with the majority being Quest 2.
    (0:35:19)
  • Unknown A
    Yep.
    (0:35:26)
  • Unknown B
    Quest 3 is currently sell. Has sold a million units at the $500 price point. So I think, I mean, if you just. I don't know what the math here is, but you know, they've done. What is that? Over a billion dollars of revenue on.
    (0:35:26)
  • Unknown A
    And I believe it's outpaced pretty good for failure. It's outpaced fee PS5 sales, for example. And so the first thought for me was like, hey, what's the first thing that's going to happen in the spatial environment? Like, what is it good for? Immersion gaming? Like these are natural entertainment, right? These were the first few things that was natural. And you had Beat Saber, you had a few things and that was kind of like, you know, here's the first use case. Let's try to get it out there, let's try to make the thing happen. And then it kind of goes up, down. People get used to those first experiences. I think you played Beat Saber. Yeah, magical.
    (0:35:40)
  • Unknown B
    The first Few times.
    (0:36:10)
  • Unknown A
    Correct. And then you're like, okay, whatever. And then you know, because it's kind of like a cheaper than PS5 unit. The Quest 2 was, it was available in Christmas a few times it went to like, you know, kids like 12, 13, 14 year old kids kind of getting this thing like they would be getting a PS5 and they use it and they, they don't have the bias that we have of like many years of like the structures we're used to. And so a lot of games formed and specifically social games like Gorilla Tag. I don't know if you've heard about Gorilla Tag.
    (0:36:11)
  • Unknown B
    What is Gorilla Tag?
    (0:36:41)
  • Unknown A
    Gorilla Tag is a social multiplayer game. It's really fun. It on App Lab did like tens of millions, like shoes, people tag. Yeah, it's like a, you know, like kind of like a fun social game that you can play with a bunch of people. You go in, by the way, you go in, you're gonna be like, dude, there's a bunch of like teenagers screaming at each other. But for them, this is the environment. It's a new place and they didn't grow up with these other things. So they're starting with mobile phones. The TV feels ancient, the desktop feels ancient. And this thing on my face actually feels like more fresh, more new. So that's where we're starting, I think. Gorilla Tag has a $200 million of revenue. And this is where I'm like, VR is a sleeping giant. We have a few teams here at our studio.
    (0:36:41)
  • Unknown A
    So we have a team called Fluid that's building the kind of like best browser in VR. So you get multiple displays, you get as many kind of tabs as you want. You could customize your environment. You get AI environments. You're like, I want to be in a cave. It like makes you in a cave, right? And then you get like social multiplayer so people can show up in your environment. And we're on. App Lab does like about 5,000 weekly active users. Still small team of three, just like, you know, without a big burn, can just build this, grow it. We're not even in the store yet. We're in like this like App Lab is like kind of the pre store where we could just drive people to it. But we're not getting anything directly from the store except our own searches. Right. And you know, 5,000 people like go in, use a productivity thing.
    (0:37:21)
  • Unknown A
    There's another product called Yeeps. It's like the second game behind Gorilla Tag. Small team, absolutely crushing it.
    (0:38:02)
  • Unknown B
    Yeeps.
    (0:38:09)
  • Unknown A
    Yeah. Y E E P S really Fun game, you know, we should play together. So this is.
    (0:38:10)
  • Unknown B
    They're here. They're a team of how many people?
    (0:38:17)
  • Unknown A
    I think they're like less than 10 people, but more like six to eight. And most of it was built with a few people.
    (0:38:19)
  • Unknown B
    And this thing is profitable or what's the deal?
    (0:38:23)
  • Unknown A
    Yeah, I mean, I'll let them talk about their numbers. So I, you know, I don't want to say anything, but on a scale.
    (0:38:25)
  • Unknown B
    Of that's pretty good to like, wow, where is it at?
    (0:38:30)
  • Unknown A
    Wow.
    (0:38:33)
  • Unknown B
    It's wow.
    (0:38:34)
  • Unknown A
    Yeah, it's wow. That's great.
    (0:38:34)
  • Unknown B
    So what's cool about this is like supply, demand, right? So like you can go be, you know, app number, you know, 5 million in the store right now, or if you're talented, you could be like one of the top 20 VR apps. If you put in like, you know, a year of hard work. I'm just using like kind of round numbers or whatever. But it's the same way that right now if you're a content creator, you go post on Instagram, it's pretty tough post on LinkedIn, you'll get tons of distribution if you're half decent at content because there's just no supply of quality content. So even if VR is not, you know, like 20 million units is very good, but even if it's not just like becoming this like global phenomenon, but a great business, and if you just keep riding the wave, you're very well positioned to be the leader.
    (0:38:36)
  • Unknown B
    And then everyone at that point will look back and be like, oh yeah, it's because they started five years ago, you know, when this was smaller, when there's 20 million instead of 200 million.
    (0:39:23)
  • Unknown A
    In these emerging tech things. So everything I found is that we do is emerging tech. I think the theme of all of them is survive. If you make it to when the industry happens, you will grow with it. If you were a small percentage of the industry and the industry grows by like 100x, you grew by 100x or more. You've already been there. And I've seen a few small person teams at like 10 million plus a year, like five people, totally profitable, totally able to do it. Is this a VC investable business? Honestly, I don't care. Like what I care about is like, this is interesting. And can you make these bets without massive capital like expenditure?
    (0:39:30)
  • Unknown B
    Right?
    (0:40:05)
  • Unknown A
    Like if it takes like $50 million to build a VR game, it's like the big giant blockbuster movie. I don't that those bets don't excite me. I think when it's like three to five people can be somewhere. The limited amount of money and just them, it's like them in the hoop. Like the basketball analogy is like, great. We have everything we need. We have all the talent, we have all the ability. The tools are amazing. Now all the game engines have perfected themselves over time. And then now the environment's forming. Meta has led it, right? So like the Quest and this is the VR world and then we're seeing Glasses Vision Pro Ray Bans. The trend is like, we're going to have compute in our spatial view, right? And I think that's the big like, yeah, this is happening in VR. The Quest platform is interesting.
    (0:40:06)
  • Unknown A
    You could build a profitable business or a fairly big game right now also, this isn't slowing down. Historically, Apple, when they enter an industry, they come with a unit. It's okay. Has a lot of things that got to get better. Another unit comes out and then you have snap. You have met it with Ray Ban.
    (0:40:46)
  • Unknown B
    Like, I mean like, Zuck is not stopping. Zuck is not giving up. He's. He's going to the end game here. Apple probably also won't stop.
    (0:41:03)
  • Unknown A
    Correct.
    (0:41:11)
  • Unknown B
    So now you have the two biggest players. They're gonna keep making this hardware better. They're gonna be super hungry for content. And the other sneaky thing about these, by the way, that I didn't really fully realize until I moved to Silicon Valley, which is a lot of these require like really specialized talent. So I remember when I first met you, you were like, I'm really into big data. You started saying words like hadoop. I didn't know what the hell you were talking about. It wasn't as popular back. This is like in 2015 or something like that. When you were telling me like, hey, I think this is really, I think this big data machine learning is really interesting. You were again, pretty early onto that crypto, same thing. You're early onto that. There weren't a lot of smart contract developers. There wasn't a lot of, you know, big data people, AI.
    (0:41:12)
  • Unknown B
    So then if even if you don't have a hit product, if you just assemble like A plus talent that's super specialized, then as those platforms rise, your team itself becomes like $100 million asset.
    (0:41:50)
  • Unknown A
    Exactly.
    (0:42:02)
  • Unknown B
    If you built today for like, because Meadow Ray Bans, like that product's actually a hit for Facebook and they're gonna keep going with that. And everybody wants to be in the glasses thing. People think Glass is the next platform. So if you build a specialized team that's good at developing for that platform, there's just not a lot of great teams that do that. That's a hundred million dollar team. Even without a hit product, how hard.
    (0:42:03)
  • Unknown A
    Was it to find, With a hit.
    (0:42:24)
  • Unknown B
    Product you get a billion dollars.
    (0:42:25)
  • Unknown A
    How hard it was to find an iOS developer when we were starting to do mobile, dude, it felt so specialized. We're gonna compete at like a ridiculous level of price to go get pretty good talent in that space.
    (0:42:25)
  • Unknown B
    I remember 2012, which was not even early. We had one iOS dev on our entire team and it was so hard to recruit talent. We was faster to just retrain. So we used, we just stopped working. And the iOS dev trained all of our other devs to be good enough to be dangerous because it was so scarce to get good. IOS wasn't even that specialized compared to like the, either the fancy AI stuff or, you know, VR mixed reality, all that, that type of talent.
    (0:42:35)
  • Unknown A
    So I just think that when I think about kids growing up and all the, let's say 13 to 15 year old kids or somewhere in the teenagers, they have a mobile phone that is attached to them, they think it's superior than a computer or a desktop because it's with them. And then we're going to take the second computing interface where we do more work or more immersive experiences and we put it around your eyes. That makes way more sense to me than TVs, desktops and even laptops. And you know, that that was like one of the thoughts where we started Fluid. Like we talked about this in 2020. I don't know if you remember, there's one project that you used to tell.
    (0:43:00)
  • Unknown B
    Me you're like, I work in VR.
    (0:43:33)
  • Unknown A
    Correct. I did that experiment where I worked in VR for an hour a day and then I ended up doing it for a few months, by the way, like, and I was like, this is great. And it had been like literally sitting with me. And I think this is one of the reasons why I actually built a studio is like, I want to do all these ideas. I can no longer do them all. I could pick a few. I probably shouldn't even go do more. But like, I just want to find really hungry people and like match them together.
    (0:43:35)
  • Unknown B
    Right?
    (0:43:57)
  • Unknown A
    That's how I found John at Fluid is like he was a PhD student, he was going to go do something in like finance and high frequency trading and like, whatever. And he also came to this idea of like, hey, when I was doing my like, you know, masters, whatever, I was writing this thing, I just wanted to go into a focus mode, like could I just go into a cave and like block out all the stuff. He's like, I had all these VR friends that had done some stuff in VR, so like I tried to do it and it wasn't good enough.
    (0:43:57)
  • Unknown B
    Right.
    (0:44:22)
  • Unknown A
    And then you kind of left it at that. And then we were talking about it and he talked to the bear and there's a dude you just talked to, fur cop. I think he's got like five pages of like random notes and ideas around this. And then that's what responded. And it's like, cool. Like, we're not going to blow ourselves out. We're not going to go raise a lot of money. We're not going to go get a giant team. We're going get three people here. We're just going to grind and work hard and build and survive for when this thing happens. We'll miss some bets like that. We'll gain ridiculous amounts of knowledge of like the industry and then we find these sleeping giants and it's like, yeah, we're going to double down, right? Like Uber went to this like VR conference, like the Meta connect thing, and he had a T shirt and we're like, the funny thing would be like on your shirt, just put, I invest in VR, right?
    (0:44:22)
  • Unknown A
    And so he did and it was like, wow. Like I found one, you know, like.
    (0:45:04)
  • Unknown B
    A girl at a crypto conference. This is amazing.
    (0:45:08)
  • Unknown A
    This is how we want to think about it, is like, try to be there early. Don't get too caught up with where the technology is now. Don't get too scared of how far it is. 2015, 2016. Remember we heard self driving cars are never going to happen. I don't know if you remember that.
    (0:45:10)
  • Unknown B
    Yeah, yeah.
    (0:45:22)
  • Unknown A
    It's massive. Like push against it, man. There's waymos running around every day now. I see more waymos at night driving around than like regular people driving.
    (0:45:23)
  • Unknown B
    You've told me once before you go, I think my superpower is that I'm usually in the top in the first thousand or ten thousand people to try any new technology and like understand it, be able to play with it, know it, see it, all that stuff. I remember we were at work and you were buying the Ethereum pre sale, the ICO or whatever the you said about it.
    (0:45:32)
  • Unknown A
    Yeah, I don't know if you remember.
    (0:45:51)
  • Unknown B
    I just remember being like, dude, can we do some real work? What are you doing? Ethereum name. That name's never going to work. I was like, that sounds so nerdy. That'll never be a thing.
    (0:45:52)
  • Unknown A
    I think that was a phrase I remember I was telling you about Ethereum. I was like, dude, I stayed up all night reading this, like white paper.
    (0:45:59)
  • Unknown B
    I'm like, you were on it.
    (0:46:04)
  • Unknown A
    I was on. I came in at the worst time and I talked to him. I tell you this, it's probably. I don't even know what I said. Who knows what, probably through a bunch of words. And you're just like, dude, I don't know what this is. We have something really to ship. And you're like, ethereum. That name's stupid.
    (0:46:05)
  • Unknown B
    Yeah, I wrote it off. Chalk that up for another. Another L for me.
    (0:46:17)
  • Unknown A
    By the way, you could have been totally right as well. So.
    (0:46:21)
  • Unknown B
    No, no, I wasn't. I think that's all that matters there. Very, very off on that one.
    (0:46:22)
  • Unknown A
    But you've.
    (0:46:26)
  • Unknown B
    I think that's true, that that is your superpower. And then you said another thing today which I hadn't heard, which is for emerging tech, there's only one rule. Survive. Because. And that reminds me, we had. I just did a pod with Ryan Peterson. He created Flexport.
    (0:46:27)
  • Unknown A
    Yep.
    (0:46:38)
  • Unknown B
    He said the same, Same principle. He goes, you know what I realized was I cannot control the timeline. I don't know how long something's going to take to work. So all I focus on is how do I just be default alive, how do I just stay in the game? He goes, I just have the confidence that if I'm in the game, I'll just keep trying shit until it works. I just believe that about myself. I will just keep trying things until I figure out the thing to work. The only way I can lose is if I have to get out of the game, which is like, I can't. You know, usually it's like I run out of funding, I can't control my destiny. I spend too much money, I'm burning too much capital. And so he's like, that's been the name of the game for me from when he was flipping scooters on ebay to now, you know, runs a multibillion dollar company called Flexport.
    (0:46:38)
  • Unknown B
    And the whole time he's like, my whole thing is I can't control the timeline, so I'm going to control staying in the game. Because if I stay in the game, I win.
    (0:47:19)
  • Unknown A
    Stay in the game with great talent and people that want to have this long term mindset. No, you know, I think there's a lot of people that can take short term wins and they should. Like, we've done that. Right? There are these short term moments like, oh, this is great for us right now. Yeah, but we're gonna keep doing more. And, like, I think that's the main thing for me. Technology takes a long time. When it hits, though, it happens very fast. Like, that's the part that I think people don't realize. They, like, underestimate how long it's gonna take, and they overestimate how fast it's gonna happen because it's, like, immediately gonna just, like, happen. And, you know, I think Uber was an example like that. Like, we saw it. It was black cars.
    (0:47:27)
  • Unknown B
    Yeah.
    (0:48:00)
  • Unknown A
    It's like, oh, there's like, expensive taxi that nobody's going to use. And then now it's like, dude, this place doesn't have Uber. Like, how am I gonna move? Yeah, I can't find it when it feels like that, you know? And so I. I think I enjoy it. So there's one reason why it's like, it's like a lifelong game. I could just play technology forever. I could learn about things. I don't have a rush to be there first. I don't have a rush to be like, I didn't know everything and, like, do everything and raise the most money and get a bazillion people. It's more like, I need a few people with me that, like, are really excited about this. They see it. Like, I see it, and we're just going to go on this mission. And luckily now I have the ability to just, like, fund that and, like, create my, like, environment to do it.
    (0:48:01)
  • Unknown A
    That's what this whole building is.
    (0:48:39)
  • Unknown B
    So let's talk about this building, because you. You've basically built, like, your dream, like, man cave in a way. I think, you know, it's kind of like a founder dream. Right? Like, and I want to talk about that because you had a big success with Applovin, where and actually kind of like, felt like there was multiple moments where, you know, it was successful, and at one point, it sold for like, $2 billion.
    (0:48:40)
  • Unknown A
    Yeah.
    (0:49:05)
  • Unknown B
    It was like, oh, exit 2 billion. Amazing. And then like, Trump blocked it.
    (0:49:06)
  • Unknown A
    Or I was like, didn't go through. Got it.
    (0:49:10)
  • Unknown B
    Didn't go through. But then during that. This is a crazy story. It was like we were sitting in the office and this news happens. Like, dude, congrats. That's amazing. Holy shit. And then, like, nine months goes by. The deal doesn't, like, fully get approved because it was such a big purchase out of a Chinese company group or something like that. And in the meantime, the business just kept crushing. So Adam, who's the CEO of that, you said he, like, basically went back, was like, Cool. We'll still do the 2 billion, but now it's for 30%.
    (0:49:12)
  • Unknown A
    Yeah. I don't know what exactly.
    (0:49:40)
  • Unknown B
    Some version of that.
    (0:49:42)
  • Unknown A
    Yeah, there was like, I don't know.
    (0:49:43)
  • Unknown B
    Like, because you couldn't do majority deals. That was the big blocker.
    (0:49:44)
  • Unknown A
    Something like that.
    (0:49:47)
  • Unknown B
    A majority deal was going to happen. And so now, then the company eventually IPOs, you get this nest egg. Right. So it's like, okay, I could do whatever. You could go retire. You could go buy islands and cars or do rich guy stuff. Like, you could do that, and instead you, like, chose to do something else. Can you just describe basically, like, what's the mindset? What's the conversations you had with yourself?
    (0:49:48)
  • Unknown A
    Yeah.
    (0:50:10)
  • Unknown B
    Now that you had more resources to do whatever you wanted to do.
    (0:50:11)
  • Unknown A
    Yeah. I feel like my whole life, I've just always wanted to tinker and build stuff. Like, I always described it as, like, I love taking stuff apart and putting it back together. It's not like some people will say it's like, oh, you want to learn how it works? It's not that. It's more the puzzle. Okay, how does somebody else put this? Like, you know, and I used to do this with cars and computers growing up. Like, I would overclock my computer and I would make my car faster. And, like, that was like, kind of just like the mentality that I had. And then I was like, okay, well, I've got to become an adult at some point in time and do the thing. But, like, hey, I like this business thing. I buy and sell stuff. It's like a way for me to hustle and kind of do more of what I want to do.
    (0:50:15)
  • Unknown A
    And then I was like, let me just keep doing this. And then maybe at some point, I gotta get a real job. And kind of luckily, like, tech was really valuable and, like, my skill set improved. I got better at it. And. But a lot of that early journey was, like, more solo than, like, with a bunch of people. And then met the guys, Adam, before Applovin, like, kind of like these other other things. And it was like, yo, we're like eight people in, like, Palo Alto, like, building cool, random apps. Like, the energy for me there every day was, like, through the roof. And then Monkey Inferno was, like, the same thing, but, like, even more. And I think I used to tell you, like, I want an airport hangar. I just want to put a bunch of cool stuff in it. And I just think it was like that before I started Founders Inc.
    (0:50:52)
  • Unknown A
    As it is, because I was at Twitch, and I'm like, I gotta get out of here, right? It was like an instant, instant thing.
    (0:51:37)
  • Unknown B
    And why, by the way?
    (0:51:42)
  • Unknown A
    I don't know. I don't think I'm a good employee. I think I'm like, suited for a few roles. And it's typically like doing my own stuff without much.
    (0:51:43)
  • Unknown B
    Was there anything that just drove you crazy about it? Was there any, like, you know, we're.
    (0:51:50)
  • Unknown A
    Gonna do a whole nother pot on it? Basically, I feel like the first week or month of like, yo, let's do a bunch of stuff. And they're like, slow down. Like, why? I want to do more. Like, I want to do more things. And this resistance feeling of like, we already thought about this or we tried this, like, no, let's just go do stuff. And I never enjoyed that. And I think startups and small teams, just because you have so much to do, that's the kind of mentality. And so I talked to probably like 75 to 100 founders before starting Founders Inc. And I really wanted to learn. It's like, I knew a bunch of people. I used to interact with them even at, like, Bebo and Monkey Inferno. I'd have them come by and like, just enter, talk, whatever. And I really enjoyed that.
    (0:51:53)
  • Unknown A
    That was like, fun. I started angel investing a lot, which was like, cool. I thought I wanted to do that, but it wasn't fun. It was like, meet great, talented people, get excited about them, and then you're like a monthly update away. Like, give them the check and then that's it, right? Damn, this has been fun.
    (0:52:34)
  • Unknown B
    First meeting is great. It's a great first date.
    (0:52:49)
  • Unknown A
    I walk away and I'm like, then there's no relationship.
    (0:52:51)
  • Unknown B
    And you're like, what happened to that great first date?
    (0:52:53)
  • Unknown A
    Exactly. And so I was like, man, I don't really want to do that. But something like this where I could help these, like, early entrepreneurs, things that I've just done over and over again. I didn't have this, like, what's a version of that? And I talked to a bunch of founders and they all said something to me that I was like, what do you need? Like, what? What help do you need? I thought, they're all going to save money and I'm gonna start a fund like that. That's what I thought was gonna happen. And they all said something different. They said something like, I need people who understand my problems. And we used to do those masterminds. And it was really about like, who do you go to for founder problems? Yeah, it's like, what are your founder problems? They're your co founders, your employees, or your investors.
    (0:52:55)
  • Unknown A
    So you can't go to any of these people. They might be the problem. Right. And so who do you go to?
    (0:53:35)
  • Unknown B
    Or even if they're not the problem you need to present, you don't want to worry your employees, you don't want to worry your investors. You kind of have to maintain a certain correct aura of momentum and morale. So you can't just go be dumping problems on them or be like, I don't know, you're supposed to know you're the guy.
    (0:53:39)
  • Unknown A
    And we, we would go in that room, little circle room with the circle table. We'd be in there. And I don't know what the employees were thinking. They're just like, oh, man, these guys are talking again. They're going to come out with something different. But we could talk about anything and then leave the room. Be like, now we're still where we are.
    (0:53:54)
  • Unknown B
    Yeah.
    (0:54:06)
  • Unknown A
    And I think, you know, co founder can be that for you. A lot of entrepreneurs starting out, they don't have that. And even if they have it, there's, like, other things that they're experiencing. And so when we used to put these folks together in these kind of masterminds, that feeling was, like, awesome. And it felt like we could relate. And actually, I heard the same thing from a bunch of founders that he's talked to. And I was like, I think it's something more like this where I could do something and put everybody in a box. And I thought it was gonna be more digital. I think Covid times and, you know.
    (0:54:07)
  • Unknown B
    Started on Discord or whatever started on Discord.
    (0:54:37)
  • Unknown A
    I mean, like, Farza, Ben was in these groups, like, there's three, few others, like, and it was just people I knew around me and kind of COVID hit. It was digital. We were talking every week. We would give ourselves these, like, accountability kind of ship it sessions. We would have an area to talk about stuff, and you could see the dots connecting. And then I got an opportunity to, like, get this space. And I'd been looking for, like, something, and, you know, it wasn't like, oh, San Francisco needs a place. I'm from the Bay Area normally, so this is the best place for me. But I said, look, if it's gonna be a stf, we're gonna be on the water no more. So kind of places like that. So we got this, like, weird opportunity to find this space and, like, really make a bet when, like, nobody else was.
    (0:54:39)
  • Unknown A
    I think it was like, late 2020 is when I approached them here. Yeah, and it took maybe like, nine months to figure it all out, another three months to, like, renovate it and stuff like that. So still very much like, oh, we.
    (0:55:17)
  • Unknown B
    Got to call another call about breaking a lease. Wait, wait. He wants to sign a lease right now? Oh, come on in.
    (0:55:27)
  • Unknown A
    That's what it felt like here. I mean, this place, Fort Mason, has 300 events a year. It went to zero with COVID All the places, you know, art galleries, art schools. Like, what do you. What do you do? Like, you know, and this supposed to be, like, this innovation place, and he's a little bit older, and.
    (0:55:32)
  • Unknown B
    Yes, that's one of your tricks, is that you don't run away when the dips happen. I remember when, early on 2013, 14, something like that, we meet. I buy bitcoin because, I don't know, you're into crypto. Some people in the office, maybe I was dumb about the ethereum idea.
    (0:55:46)
  • Unknown A
    Yeah.
    (0:56:03)
  • Unknown B
    P.G. pete. Pete Hicks. He's mining bitcoin on our servers. So I buy some bitcoin, and literally, like, the next week, I. If I get, like, super convinced, I'm like, ah, guys, I see it.
    (0:56:04)
  • Unknown A
    I believe.
    (0:56:16)
  • Unknown B
    Here's why I believe I'm giving you my case. I bought. Yeah, great. Like, the next week, price cuts in half. It goes down to, like, 300 bucks or something like that. And I came in, I'm like, oh, the bitcoin. I was, you know, whatever.
    (0:56:17)
  • Unknown A
    And you go, that was a fun week or two, you know?
    (0:56:29)
  • Unknown B
    Well, you were like, oh, this is great, because now everything's half off.
    (0:56:31)
  • Unknown A
    Like, you.
    (0:56:35)
  • Unknown B
    You literally told me that you go. You believe if you. If you buy now, you can cut your buy price. Basically, you can go down by 50%. You' cost average in at half the amount.
    (0:56:36)
  • Unknown A
    Yeah, like.
    (0:56:44)
  • Unknown B
    And I was like, oh, he's right, because I was just riding a roller coaster of, like, you know, I was doing what a cliche person would do. When things are good, this is great. When things are bad, maybe it's not great. Whereas you were like, dude, did anything actually change or just the external sentiment? And so I bought more. So I thank you for that. That was a very good, you know, decision at the time to go buy more when things go down. I think you've done that with. With other, you know, bets, whether it's San Francisco real estate during the, you know, Covid time or it's, you know, whether it's crypto or VR. When. When things go out of fashion, I feel like you don't run away, which is important.
    (0:56:45)
  • Unknown A
    There's A signal. It's like things go out of fashion and there's another place where the people who don't shape narratives typically, like, I'm technical, so I live in these, like, GitHub projects. I live where the builders are. I like, engage with them. If I see that somewhere where it's like, huh, all the people talking are like, against it. These people, like, nobody told them yet that like, it's done. Like, oh, this is dead, right? Like, they're all saying it and then these guys are just shipping more code and like, hey, did anybody tell you it's over? Like, what are you talking about? I don't care. And I just think that's the perfect environment.
    (0:57:20)
  • Unknown B
    And even if you're right one out of five times, like, that you'll be right in such a big way that it works out.
    (0:57:54)
  • Unknown A
    And then, by the way, for me, it's just fun. So, like, this is fun. Like, I love building stuff. I like building technology. I did a lot of software, obviously, because it's been magical to develop things and like distribute it to the world. We have some hardware projects. I don't know if you remember Jamie, by the way.
    (0:57:59)
  • Unknown B
    Yeah, yeah, we. At one point in time when we were. When we were working together, we had an idea for a. It was cool. It was like a voice control. It's kind of like Alexa. Yeah, we called it Jamie. I don't know why, but like, yeah, we like Jamie. I still like the name. That was good. And what you were saying was like, you're like, we can. Instead of creating. Everyone was trying to create a device. Portal was trying to create a screen. Amazon was trying to create a screen. You're like, that makes it expensive. You're like, everybody already has TV screens in their house. What if you just plug in like a Chromecast and now you turn your TV from just a blank screen into like an Amazon, like Alexa thing. That was cool. We didn't do it because it was good. Like, we sort of saw like huge distraction.
    (0:58:14)
  • Unknown B
    We were like, yo, that's going to be like a brutal battlefield.
    (0:58:56)
  • Unknown A
    You took it to Michael and he just gave us that look. Like, this is.
    (0:58:58)
  • Unknown B
    Well, he was just like, yo, when all of the like trillion dollar companies are going to go after the same prize, like, you can. But do you really want to, like, you know, it's better to do the things they're overlooking. I just think it's probably good advice. To be fair. We also were going to do a crypto exchange with Crypto Got Hot. And he was like, for a Different reason. He's like, hey, I'm already rich. I don't want to lose everything. And I don't really know what crypto is. It's 2014. Like, crypto might just be, like, super illegal. And I don't want to risk it all on that. Yeah, if we had done that, might have been good.
    (0:59:03)
  • Unknown A
    Yeah.
    (0:59:32)
  • Unknown B
    So you have to be careful. Like, even really smart, successful people, you can't, like, just take their word, you know, you got to have the Independent Mindedness 100.
    (0:59:32)
  • Unknown A
    And I think it's fun to take shots. Don't get stubborn over it. Like, man, people fall in love with their ideas. I think that's. It took me probably, like, I don't know, 10 years to figure that out. Like, you have to get, like, almost like, you have to really take the hits to like, really, like, live in that of, like. Yeah, there's a lot of ideas. I may try a lot of them. My mission isn't all of them. I gotta find the right ones where I can really spend the energy on. But I was gonna talk about one more. So we built chatty heads, which, by the way, now in the AI world, we were fucking ahead of the time.
    (0:59:40)
  • Unknown B
    Yeah, we were a little early.
    (1:00:09)
  • Unknown A
    We could generate images for like, I don't know, 5,000.
    (1:00:10)
  • Unknown B
    Yeah.
    (1:00:13)
  • Unknown A
    And that's what it. That's what it feels like. But I think it's like, cool. It's like whatever technology you have today, go try to produce a thing. It might not be the right time. It might be the right moment. The medium might be wrong, the team might be wrong. Some of those you should pursue again and again. And some of those are great learning exercises to build on top of. And I, you know, I got a chance to meet a lot of people who were professional athletes. And I think one thing a lot of them talk about is like, you know, basketball might end. Like, my career will end at like 35. It's like, that's. That's my game. It's done. Now what do I do? I think what we get a chance to do, whether it's like business or for you now, content or, like, building stuff.
    (1:00:14)
  • Unknown A
    Like, I'm going to do this for rest of our lives. One. I think that's the fun.
    (1:00:51)
  • Unknown B
    Buffett's like, what, 90 something?
    (1:00:55)
  • Unknown A
    Yeah.
    (1:00:56)
  • Unknown B
    Still all the top of his investing game.
    (1:00:57)
  • Unknown A
    Exactly. And so it's like, well, like, what am I in the rush for? Like, I. Not just here to, like, enjoy the journey, but I also don't want to be like, I got to solve it tomorrow.
    (1:00:58)
  • Unknown B
    Right.
    (1:01:07)
  • Unknown A
    Like, when I was young, it was like, I got to be the millionaire. By what? It's like at some point I was like, I don't know, man. I just want to keep doing this.
    (1:01:08)
  • Unknown B
    Right.
    (1:01:14)
  • Unknown A
    And if I need to, like, hustle my way to it or not, like, it doesn't really matter. Like, you know, I took an Android engineer job in Monkey Inferno.
    (1:01:14)
  • Unknown B
    Yeah.
    (1:01:21)
  • Unknown A
    Because I was like, you know, I met you, and I was like, I want to work with this guy.
    (1:01:22)
  • Unknown B
    Yeah.
    (1:01:24)
  • Unknown A
    I think that was my worst skill, by the way. I just learned Android. Yeah.
    (1:01:25)
  • Unknown B
    You fooled me. Yeah.
    (1:01:28)
  • Unknown A
    So, like, I was like, I don't. I got to get in somehow. And like, I know I'm going to do great stuff here. I got to show it. But, like, I'm not afraid to put in the effort. We need to put in the effort. Also not afraid to, like, not rush to the answer.
    (1:01:29)
  • Unknown B
    Right.
    (1:01:41)
  • Unknown A
    And like, you don't want to be, like, casual and like, wait, you want to be kind of like in the middle there. You want to know when to attack and when to the knot. But, like, I don't know, you got to enjoy it. Otherwise, you're really.
    (1:01:41)
  • Unknown B
    Naval has the best quote on this. He says, impatience with action, patience with results.
    (1:01:51)
  • Unknown A
    Oh, yeah.
    (1:01:54)
  • Unknown B
    It's the unbeatable combination. If you ever go against somebody who's going to operate like that, they will win.
    (1:01:55)
  • Unknown A
    Yeah.
    (1:01:59)
  • Unknown B
    That. That is a. You cannot lose. If you're going to be constantly impatient with. With doing things, you're not going to sit back and hope it all happens. So you. Impatient action, but patient with results. That's the hard part is a lot of founders are impatient and impatient with results, or non founders are, you know, patient with both, and then nothing ever happens. So you have to get that combo.
    (1:01:59)
  • Unknown A
    Yeah.
    (1:02:19)
  • Unknown B
    Speaking of founders, you worked with Adam at Applovin, and Applovin has been like, kind of a staggering company because, you know, when I met you, it was, you know, a successful company. You told me the stories about before you guys started that you're like, we were wandering around. We tried a bunch of different ideas. We're playing FIFA because we didn't have. We didn't know what the heck we were doing. We were just come in trying to figure it out. If we didn't have it, we would brainstorm and go home the next day. What is special about that guy? What's a superpower from him or a story from him that you remember that you know, I can learn from or you. Anybody to listen to this can learn from?
    (1:02:20)
  • Unknown A
    Yeah. So there was this like four year period. Ish. When I was there, I think three years of it was like, not Apple. So like most of my intersection there is like not what it is today. But I did get a chance to spend a lot of time with him and ideate ideas.
    (1:02:54)
  • Unknown B
    What's the cliff notes of his story so people know. Because people don't know. He's pretty under the radar, right?
    (1:03:09)
  • Unknown A
    Yeah. I mean his backstory, I think he did some stuff in like equities or trading at some point. I think he got into like ads at some point through like marketing and affiliate stuff. He built a few different products. Maybe he was a key member of the team. And then he had like a few companies. I think he had actually built up some like, you know, wealth. I don't know how much it was, but it was enough where like, you're like, okay, this person can make this bet and like fund the operations.
    (1:03:13)
  • Unknown B
    So he was kind of self funding.
    (1:03:39)
  • Unknown A
    Self funding. It was him and this guy John. John had done a lot of stuff on the Internet. He was more the technical person. Adam was more the business person. They were both uniquely. And the skills, incredible. Like their personality is incredible. For Adam, I think the thing that I felt the most was like, I think it's the first time in my life I was like, man, this is what A plus execution looks like. Like this guy just hits it. Like if we were talking about something, we made a choice within, like, it felt like within minutes that was like delivered to this team. And look, when you're like an eight person team, it's really easy to do it. We'll decide something, go slow. Maybe next week. Oh, we'll, we'll do it later. We'll make these role changes later. We'll tell everybody later. No, it was like immediate.
    (1:03:40)
  • Unknown A
    And when it was like moving on from something that was immediate, when it was a new idea we wanted to do, it was immediate. When it was something else, it was immediate. It was just like it felt like this is what execution is. It's like, you know, think, decide, act and like how fast you run through that depends on like the moment you decide. The delay on act is like usually a problem. And I think this is where most I. I'm not great at this myself, but I've gotten a chance to see that. I think it was kind of similar in a different realm. When I met you, I was like, I think this person's product thinking and like ability to like unpack like a complex thing like product or distribution or maybe team motivation or whatever. It's like you see A plus talent and you're like, you want to do it.
    (1:04:22)
  • Unknown A
    For me, it was like 10 or 12 years, almost like a solo founder journey. Like, at this E commerce company, had these other little things. I had, like a startup. I had people with me, but I never saw somebody else that I was like, yo, like, I want to learn these skills. I bring something to the table. This A plus. I compare with this A plus person. And now we're going to be like a superpower.
    (1:05:07)
  • Unknown B
    Right?
    (1:05:27)
  • Unknown A
    I felt that with Adam, it was very clear and obvious, you know, like the size of company. I. I don't want to say not a surprise, but also it's not a surprise that this kind of person would go do it.
    (1:05:27)
  • Unknown B
    Like.
    (1:05:38)
  • Unknown A
    Like, it just is that. I think the same thing you're talking about, like, Ryan at Flexport. Like, it feels like some people are just like, they're built for that. You still need a lot of stuff to go right and make a ton of great decisions and a ridiculous team.
    (1:05:39)
  • Unknown B
    One thing I've come to learn is that where I think we screwed up, because we did Monkey Inferno, which was basically our little idea lab, but we had a beautiful setup. It's like, you got funding already done. You have great team. You're in San Francisco, beautiful office, really talented team. Like, you know, we're not the PayPal mafia, but, like, everybody's gone on to do kind of interesting. Everyone's, you know, I don't think we had the level of success that we could have given the talent. My take was, I think we were good execution, maybe even great execution, but poor project selection. Meaning we were going after these, like, moonshots, like, create the next hit social media app, which is like, you know, there's been like seven ever. There's not that many of them ever to exist. So, you know, I think we did bad with project selection.
    (1:05:52)
  • Unknown B
    It seems like one thing that Adam did, aside from great execution, was project selection. I think you told me some story about, like, they went to some conference. You guys were working on one thing all together, and he came back and had that very quick, like, think, decide, act loop where he's like, we're doing a mobile ad network. We're doing mobile games. I don't know the full story, but, like, yeah, seemed like just that one choice at that time.
    (1:06:41)
  • Unknown A
    Yeah.
    (1:07:02)
  • Unknown B
    Is the make or break, you know.
    (1:07:02)
  • Unknown A
    Like, yeah, yeah, Huge difference. And, you know, like, I think we had many of those moments. I wouldn't trade it, by the way. I think our learnings. I still Leverage them. A lot of the things that we talked about, how we ran the teams, like, they still radiate and resonate with me. And so like immense wealth and knowledge and like, like, literally like experience of the thing.
    (1:07:04)
  • Unknown B
    Right. Beyond like you're talking about when we.
    (1:07:25)
  • Unknown A
    Worked, when we were.
    (1:07:27)
  • Unknown B
    Yeah, exactly.
    (1:07:28)
  • Unknown A
    But there were a few moments where project selection could have been massive for us. And yeah, that outcome, you know, like they, you know, and we can talk about uploading a little bit on that in that journey. But like we did Blab. It was a live streaming part of Google Hangouts public livestream. Yeah.
    (1:07:28)
  • Unknown B
    Like if you saw Clubhouse get really popular, we had built basically a clubhouse before Clubhouse and it got kind of.
    (1:07:43)
  • Unknown A
    Like, what Twitch right now, like there's a big section of this, like just chatting, hanging out category.
    (1:07:49)
  • Unknown B
    Right. We built an app like that. It got to 4 million users, but it didn't become the next big thing.
    (1:07:54)
  • Unknown A
    I don't know if you remember this conversation, but we had this one time when we were deciding what to do next. Oh, we do the mobile version of this because we see other things happening or do we do the P2B version?
    (1:07:58)
  • Unknown B
    Yeah.
    (1:08:08)
  • Unknown A
    And Zoom didn't exist and that I think that was.
    (1:08:09)
  • Unknown B
    And we were like B2B. I remember there was like, it was like so short of a conversation, which was so silly. We were just like, B2B. That's not cool.
    (1:08:12)
  • Unknown A
    It wasn't cool and it wasn't clear because if you have to think about this, like 2015, there wasn't a billion like B2B companies crushing it.
    (1:08:21)
  • Unknown B
    Yeah.
    (1:08:28)
  • Unknown A
    But like every year since then it was like seven or nine. Like, because I think at that time it was like only a few had really reached. Like it was like, I don't know, box.net and Dropbox.
    (1:08:28)
  • Unknown B
    And it wasn't, it definitely wasn't as obvious at the same time, it wasn't as hidden as we kind of made it seem.
    (1:08:38)
  • Unknown A
    We totally, you know, like, I remember.
    (1:08:45)
  • Unknown B
    Citrix was like a multi billion dollar product and Citrix Online was the way that people did these webinars, webinars and web conferencing at the time. And it was so bad. And their users, like, we were trying to make this cool social app and SAP and Oracle were using our tool just because it was better, even though it was like not meant for that.
    (1:08:46)
  • Unknown A
    Why is your color like weird and purple? Why do you got this weird star thing?
    (1:09:06)
  • Unknown B
    And instead of looking at those clues and being like, huh, maybe we could do that. We missed that project selection choice. I remember that Day because that was probably a multi hundred million dollar fork in the road moment, you know. Yeah, Maybe that you still had to execute.
    (1:09:09)
  • Unknown A
    But for sure. I mean, we could execute. Right. But it is. Did we have the right selection and could we get the right insight in our mind to incept it? Also, when we decided to end blab, I don't know if you remember, you went to this barbecue. I forgot who you met.
    (1:09:22)
  • Unknown B
    James Currier.
    (1:09:35)
  • Unknown A
    And they were telling us, you know, you were talking about like, hey, this content network problem. Because it was like the moment that entered our mind, it's like, oh, shit, we're fucked. Like, that's what it felt like. Like we don't have the ability to intersect these. And we kept looking at Twitch, like, why? Okay, so we know we don't because people come on for an hour, they do a show. The epic content is not on long enough for people to show up and intersect with it. How come Twitch wins and then it turned out that, oh, people play games for eight to 10 hours.
    (1:09:36)
  • Unknown B
    Yeah. So it didn't matter when you showed up.
    (1:10:01)
  • Unknown A
    Correct. And then the context reset. So it's like, I have. It was like, you know, the feeling, a lot of monkey inferno to me. And like the things we built was like, it's not slow down and speed up, but like, look for the clues. Don't be afraid of that. And again, the eager, you know, the ego or the stubbornness of like, we want to build a giant social app. Like, I want to go somewhere around the world where somebody's using my consumer product. Like, that was a stubbornness that we.
    (1:10:03)
  • Unknown B
    That was the driver.
    (1:10:27)
  • Unknown A
    And it's like if we had just kind of unlocked it a little bit. There was these project selection moments and so there was a lot of that. I still feel that sometimes, but I don't know, maybe it's because I'm older and I'm like, less willing to like be nimble in that way. But I did want to talk about one more hardware robotics thing in a few minutes. And so I think this is another resurgence moment happening. Like, for a long time, hardware has been too hard, too expensive. Software gets funded.
    (1:10:28)
  • Unknown B
    That's like a Valley motto, right? Hardware is hard.
    (1:10:52)
  • Unknown A
    Hardware is hard. Software is easy. Software skills. It's eaten the world. Like, these were all the mentalities. I think it's flipping and I think it's a few things that have all kind of showed up together. So there's two types of hardware that I think are now, like, there and like, ripe to build. Same recipe. Can small teams do it. Can you do it without a lot of funding? And then can your output be really big and, like, impact a lot of people? And so I think there's one around consumer products. So, like, the combination of Raspberry PI and cloud AI has completely changed what it takes to build something, right? So there's a company in our studio, Magical Toys are building an AI Teddy bear. We'll do a little demo after. We'll kind of get to that. And, you know, I think what that.
    (1:10:55)
  • Unknown B
    How old is that guy who's been that? He's like, young, right?
    (1:11:36)
  • Unknown A
    I think the team's like 24 or 25.
    (1:11:38)
  • Unknown B
    And it's not like he has huge funding or a huge team, but he's.
    (1:11:40)
  • Unknown A
    Able to showed up. I don't know how I got here, to be honest. I think like, many people here, they meet somebody, they attract. Some people just show up, by the way, and it's awesome. Like, we've created that environment where it makes sense. He had done some small projects in college. Like, he built this thing called Desk Buddy. It was a little, like e ink screen with, like two eyes that just blinked. And that was really it. He couldn't talk to it, couldn't do anything. It was just like a little Desk Buddy.
    (1:11:43)
  • Unknown B
    So you're not alone. Is that the idea?
    (1:12:05)
  • Unknown A
    I don't know what it was, but I remember seeing it. I'm like, that's cool. Like, I want one on my desk. Like, is this fun? And they brainstorm a bunch of ideas and, you know, the combination of like, hey, we got Raspberry PIs. We could do these little things. We could use 3D printers to build enclosures. And then now we got this cloud AI thing that, like, can be really powerful. They ended up coming with this, you know, idea which was like, hey, we're going to build a toy. And first they literally made Ted the, you know, stuffed animal Ted and made it talk like it. I was like, oh, this is wild. Like, you know, and AI could do this, but everyone's trying to make coding faster or there's, you know, developers solving developer problems. And I love when somebody takes that and goes, let me go to this other place where nobody's thinking about.
    (1:12:07)
  • Unknown B
    Right.
    (1:12:47)
  • Unknown A
    And he spent probably the last nine months sitting, refining. I think we sent you one of the first units. It probably broke. Yeah, first thing first, he gave me.
    (1:12:48)
  • Unknown B
    A teddy bear with the back. Like, the whole computer was just hanging out the back, like half done surgery. But it was interesting. I gave it to my kids, you know, I think they were probably like 2 years old, 3 years old at the time. And every other toy we have in our living room is pre programmed. So it's like, this is a toy. Push this button, it'll say this thing. That's all it can do with this toy. It was like, ignore the thing hanging out the back. It was like, hey, we love Paw Patrol. Can you ask us some Paw Patrol trivia? Certainly. I can tell you, Paw Patrol, who is the red dog in Paw Patrol? It's like, marshall. Correct. And I was like, hey, can you keep track of our points? He goes, okay, two points. And then I was like, whoa.
    (1:12:55)
  • Unknown B
    And my kids were blown away because now you have an infinite toy, whereas every toy is finite. It can only do the things it could do out of the box. Now suddenly you have a toy that's basically chatgpt shoved into a stuffed animal and you're like, wow, now that can do anything. I could say, sing me a song. I could say, tell me a bedtime story. I could say, I can make it do many, many things now.
    (1:13:37)
  • Unknown A
    And I think what was cool is Fatima and this little, like, lab that we built. And the lab has like some 3D printers, some electronics area. Honestly, we started with like an empty room and people would come by like, what's this room for? I'm like, oh, it's gonna be a machine shop, electronics lab one day. Like, oh, can I use it? I'm like, yeah, but we have nothing here. What do you need? Any tables? Great, we'll bring tables. Oh, you need like a little thing. Okay, we'll add that. You need 3D printers. We'll add that. And I've seen now, like tens of people come through. One person sit there, spend some time. Tinker and Fatim did that. Like, he built one, he showed us, he built another. He tried different, various different versions. You know, built, you know, new cases, 3D printed, buying raspberry PIs, new software.
    (1:13:57)
  • Unknown A
    And like, I think he shipped like 60 to 70 units across four to six months. Which in software rule just feels like, wow, ancient. Like 60 users in hardware, this might have cost like half a million to a million dollars. I think we did that for like 50 to 100 grand, right? So, like, that difference, one person, 3D printers, Raspberry PIs, some AI, and you could just sit there and deliver units and try it with people. When we showed Uber first, by the way, internally, Bear was like, nah, I don't. I don't think kids are going to do this. It's weird. His daughter used it and it Changed his mind. Like. Like she changed his mind, right? Because he saw what it could do. But, like, and how do you get that opportunity to prototype cheap, right?
    (1:14:41)
  • Unknown B
    So hardware being hard, but it's like, maybe hardware is not as hard as it used to be. That, like, Sam calls these inflections where, you know, something changes. Like, there's famously an inflection where when Obamacare came out, then Oscar Health built a thing that was just to do Obamacare and like, you know, had, you know, became like a billion dollar company. It's like, so what are the inflections? So, oh, phones now have GPS in them. Now you can build Uber. You couldn't build Uber before because the driver and the rider needed to find each other. How were they going to do that if you didn't have phones with GPS on them? Phones have cameras, now you can have Instagram, right? So it's like the technology inflection can happen. It's one type of inflection. And you're basically saying because of Raspberry PI plus AI plus 3D printing, consumer hardware is very. Consumer hardware is now possible.
    (1:15:22)
  • Unknown A
    Now, like, now more than ever, two.
    (1:16:11)
  • Unknown B
    People can actually mess around and tinker until they get something right. Kind of wasn't feasible 5, 10 years.
    (1:16:13)
  • Unknown A
    Ago when we built Jamie. I use a Raspberry PI at that time, which was the first version. Raspberry PI was thought of as this hobbyist market of tinkerers that are going to buy a few of them. They've. They've sold like 60 million units or something ridiculous like that. Like 35 bucks a pop. 60 million. There's like a few billion dollars of Raspberry PI out there. And I think what it did is you used to have to make like custom boards, custom software. And you know, for a technical person like me, I don't want to go that far. Like, I have certain skills that I could do really well. And typically it's like, read a few guides on the Internet and like, stitch stuff together. It felt too far for even like somebody like me. It felt like, man, it's like really serious engineering. I need 10 people, I need millions of dollars.
    (1:16:19)
  • Unknown A
    I gotta convince somebody there's a big market and now, like, build up this company, which probably will fail because I raised too much, too much pressure, too much demand on return, et cetera. And to me, the Raspberry PI was one of the unlocks. And there's the Nvidia Jetson now, which has like GPUs on device, and there's so much more there.
    (1:17:00)
  • Unknown B
    But so what are, what are other things besides magical toys that you saw somebody built? Interesting things you're seeing built in the hardware. Robotics side.
    (1:17:16)
  • Unknown A
    Yeah. So we have AJ who's building the, you know, neurocity. He built that first version which I think I've showed you before, which is brain computer interface. Now he has a second version that's really tiny. It's like the size of AirPods. You could put it right here. Special purpose. So really like the ability to prototype, develop the thing, get like hundreds or thousands of units out there, improve the design and doing that without a giant team allows him to kind of continue. We've seen like a variety of things kind of come out on that front. I think the second area that's happening is, you know, there's a consumer hardware and then there's like this robotics, drones and kind of this other world where we have so much physical equipment in the world. Forklifts and lawnmowers and cars and like, you know, all these things that we do that requires either a person like, you know, with drones, we invest in this company, Lucid Drones, which they built a power washing drone, could go up in buildings, could power wash, you know, the glass instead of people hanging from the side.
    (1:17:23)
  • Unknown A
    There's another company that.
    (1:18:28)
  • Unknown B
    And is that working like do people, Is it like.
    (1:18:30)
  • Unknown A
    Yeah, working very well. And you know, like what's interesting is there's like a unique business model to find here as well. And I think this is why I love like being in the weeds a little bit. And like seeing it is like most people think you're going to build this product and then you're going to take the people that like manually wash a building and you're going to like get rid of them. What actually happens is there's like a team that's like a little like small business somewhere. They have like five people at their company.
    (1:18:32)
  • Unknown B
    Dave's Power Washing. Dave Power Windows so clear you won't even know it's there.
    (1:18:56)
  • Unknown A
    Amazing, right? Dave's got a great tagline as well. And you know, people end up finding that if you just sell to those small businesses, you give them more tools, they can serve more buildings, do it more efficiently, that distribution is built in. Maybe in the long run this starts changing. But like now there are a ton of these opportunities. I've seen one for farms and like, you know, mowing the weeds around certain fruits or kind of like inspecting them, you just send people between these things to go like, do it. And now there's like a literal like robot and you Know, instead of the one person doing it for two weeks or two people, the one person's there monitoring it at the facility in air conditioning and like watching on the iPad. Watching on the iPad and it might get stuck early on or might detect something.
    (1:19:00)
  • Unknown A
    Now they got to go fix that thing. This efficiency I think is like massive. And we're seeing it in many places. So the same thing I saw these two guys building here in San Francisco. They're like random warehouse in the back of some other store. Like two dudes like literally grinding, bootstrapping, like, like just go in there. I'm like, I like these guys, they took a forklift, they automated it, they took self driving car tech that probably took billions of dollars to develop. And then all of that kind of flowed to like open source. And typically open source sometimes is behind than the cutting edge. But in 10 years that normalizes. We see this elsewhere like AI models like Llama, but really they took cameras and some lidar stuff and they strapped a little computer to a forklift and they could move it around, you could talk to it, you could kind of get it to do things.
    (1:19:44)
  • Unknown A
    And I think there's a massive resurgence. And so forklift physical thing, you took a little Raspberry PI, Internet, some cameras, some technology, like we were doing computer vision technology to score like Fortnite games. They're using that same kind of technology to look at, oh, this is a box. This is the barcode that I picked up, right. I can now use and figure out what's this thing. It could go walk around the warehouse and be like, oh, that pallet's in the wrong spot. How it just scanned the barcode and detected, oh, there's this palette here, supposed to be over there. Go pick it up, move it over there. Like these problems exist in warehouses. Like I mean, you know, right. I think you've dealt with some of those.
    (1:20:31)
  • Unknown B
    I run a warehouse.
    (1:21:08)
  • Unknown A
    And so to me it's like what are the machines? Like what are the traditional machines we've built probably for the last hundred years that you're going to slap a little computer on it and now it's a superpower. And I think this is bringing down the cost of like this robotic hardware. Like building a robotic arm. Used to be like, yo, I got to be like Tony Stark and like Iron Man. I've seen two people do it in our machine shop. I there's a guy here, I don't even know his company. He's showing, he just had a 3D printed hand on his desk. And I'm like what the hell is this? It's like oh yeah. Like I, I created the ability to develop a full hand with all the fingers and everything in just this 3D printer. There's a Bambu lab printer which honestly 3D printer was great and then Bambu labs took it to a whole nother level, like a little bit of AI to help self leveling and make prints great and like everybody loves it.
    (1:21:09)
  • Unknown A
    And he just built his hand pretty high quality, took a little fishing net on the inside of the hand so like in each finger he could like pull every finger and like do some stuff. It's like one dude like few months hackathon and like I don't know what he's gonna produce from that. But I just think you could do these things now in like weeks and months when they took years and like a lot of money. I think there's a huge opportunity here. Still going to take time to marinate and develop. But I look at it as one of those things where if I was a mechanical engineer, if I liked hardware and I've been told that it's just AI and software and your stuff isn't that interesting. It's like, no, no, this is very interesting right now. You need to find a place to do it.
    (1:21:58)
  • Unknown A
    And I'll even say I think we're going even further. For us, we have this space we built here, we call it the Founder Lab. This is where a lot of people come, they tinker on stuff. We have founders here, we have builders, we have creators here, we have all kinds of people doing stuff. Built a little machine shop and that kind of pushed us to be like, wait, there's more. We're seeing more, we're talking to more people thinking about this. And so I ended up getting this kind of industrial space and call it the garage. It's 20,000 square feet of industrial space. I'll show you in a little bit. But it looks like, you know, San Francisco real estate is not the best. I think this is the time to make these bets. But I've talked to 25 to 50 founders in the last 12 months that need a hardware space like this to tinker, to have smart people around them, to have the machines around them, to just being able to develop it probably for less than 100 grand they can go and proof of concept and prototype the thing.
    (1:22:36)
  • Unknown A
    And look, we're seeing the hype cycle of humanoid robots. That's that hype above. I'm more excited about all these startups that are going to form. They're going to build this expertise. They're going to be $100 million teams, whether it's their product or their knowledge.
    (1:23:31)
  • Unknown B
    Right.
    (1:23:45)
  • Unknown A
    That's happening now. And two people are doing it, like, every single day. Like they're spawning these things. And so consumer hardware is one area. But I think robotics and what typically was known as, like, deep tech, like, I need, like, PhDs and like stacks of them and $50 million or $100 million, that's the second one. And I think it's like, there's a few people seeing it. Maybe there are sectors like defense, where it's like, exciting, but, like, I don't know. I think we're going to see machines everywhere and every kind of version of it. And I think I've seen people develop, like, cooking robots, laundry machine things, folding drones to inspect stuff, drones to map interior spaces. Like Matterport is a giant company and a human goes and puts a tripod everywhere. And like, this is a little drone that's going to fly through the whole house and map it for you.
    (1:23:46)
  • Unknown A
    And that expands that. And I just see one or two person teams able to do this faster than I've ever seen it. I feel more capable maybe. I just really want to get into hardware again myself. And I think that's the point, though.
    (1:24:35)
  • Unknown B
    It's. A lot of people would want to mess with this. And if something goes from not tinkerable to tinkerable, suddenly it's now the, like. It's kind of like before you're competing 1v1. Now it's 1 versus the field. The field. Of course, any individual thing in the field might suck.
    (1:24:46)
  • Unknown A
    Correct.
    (1:25:01)
  • Unknown B
    But the field overall is super powerful. And now you're saying the field is open for, you know, hardware tinkerers, which it wasn't open before. That's a big deal.
    (1:25:01)
  • Unknown A
    Yeah, we do these, like, residencies here. We'll bring people here for a month or six weeks. We just tell them, like, here's a theme, here's a space to go do things. When the Vision Pro came out, we did it. We had about 40 Vision Pro devs. We probably had the largest concentration of Vision Pro devs out of Apple. Right anywhere. And the knowledge of that. Look, look, it didn't produce some ridiculous outcome. We actually did invest in one or two teams from that. I think we just got a chance to see that technology deeply. We did this AI hardware one. I remember meeting this kid and I don't know where he was in the world. And he shows me this robot he built, a humanoid he built in his Bedroom. And it's half. He only built the bot like the legs so stopped where the waist was.
    (1:25:10)
  • Unknown A
    And it was totally hand constructed. And I'm like, yeah, this is wild. But the fact that you could bootleg this in your bedroom and like, it could take steps, it's like crazy to me. I met these other guys premiere and the same trend in Raspberry PI, they took that trend. And I mean, I love some of these. I just, you know, I love it because I could jump on the video and they're. They were up in Seattle or something, and it's like their kitchen. And I'm like, is that a 3D printer in your sink? And it's just like their kitchen is like all machines. And I'm like, dude, you got to get out of your house. And I got to give you a home to like do that. That's what I want is like, people who will just turn their bedroom into this. It's like, no, no, no, you come do it here.
    (1:25:52)
  • Unknown A
    We'll give you a little bit better facilities. We'll give you space, you get a better place to sleep. And they took this like Raspberry PI trend and they're like, oh, people start with Raspberry PIs and then they build a custom board. Oh, we're building a modular Raspberry PI thing, right? Take that compute module, intermediate step. Oh, you want a speaker? Well, you could pick whatever speaker you want. Just put that in. Oh, you want to produce 2000 units. Now we have the ability to scale it for you. So they took the hobbyist world and the behavior that's happening, driving it, and they started this in there, literally in their kitchen. And like, I just think that, man, that's capable now. And that's the trend that I can't, I can't like unsee it sometimes. And in hardware, both in consumer and more deep tech hardware, like drones, platforms, massive, right?
    (1:26:31)
  • Unknown A
    To be able to do things, so much opportunity to utilize that. I don't know how long is going to take for this to become mass and mainstream, but I just keep seeing that trend right now. And I think for us, that's the bet you're making. That's the bet we make. And so I always joke with the guys here, it's like, we want to bet on negative 1 to 0. Like Peter Thiel talked about the 0 to 1 companies. It's like, we still one step even before that. Like, you're at negative 1, you're wandering the forest, you need a place to tinker and like come and get the ideas to form. This is what we will. This is what we want to do, right?
    (1:27:13)
  • Unknown B
    All right. Love it. Firkon, this is amazing. Good catching up as always. Let's go check out some of these spaces.
    (1:27:43)
  • Unknown A
    Sweet. Let's do it.
    (1:27:48)
  • Unknown B
    Thanks so much, Sa.
    (1:27:49)