$100B Founder Breaks Down The Biggest AI Business Opportunities For 2025

0:00:03 That’s the trend that I can’t like unsee it sometimes.
0:00:05 – Right, that’s the bet you’re making.
0:00:06 – That’s the bet we make.
0:00:07 And so I always joke with the guys here,
0:00:10 it’s like we want to bet on negative one to zero.
0:00:12 Like Peter Dill talked about these zero to one companies.
0:00:14 It’s like we still want to step even before that.
0:00:16 ♪ I feel like I can rule the world ♪
0:00:19 ♪ I know I could be what I want to ♪
0:00:21 ♪ I put my all in it like the days off ♪
0:00:23 ♪ On the road, let’s travel, never look back ♪
0:00:24 – All right, we’re gone.
0:00:25 We’re here.
0:00:26 – Amazing.
0:00:27 – I haven’t seen you in a little while.
0:00:28 People don’t know.
0:00:29 We used to work together.
0:00:32 Maybe five, six years we co-founded a company
0:00:34 and launched a bunch of products
0:00:36 and ate a bunch of shit together.
0:00:37 And here we are.
0:00:38 (laughing)
0:00:39 – One time by the way.
0:00:42 – Yeah, I’m thinking the title of this is gonna be,
0:00:46 ’cause App Lovin’ is now 50, $60 billion company.
0:00:47 – No.
0:00:50 – $50 billion founder tells me the next big thing in AI.
0:00:52 I’m gonna go full YouTube clickbait with it.
0:00:55 – Full cent, yeah, they’re great.
0:00:56 – So we used to do this thing
0:00:59 where after we did Bebo together,
0:01:01 got acquired, we were there for a year or so,
0:01:03 and then we went off and we did different things.
0:01:05 I started the podcast and started doing my thing.
0:01:07 You started doing yours.
0:01:09 But I hit you up and I was like,
0:01:10 hey, mishanging out with you.
0:01:11 What if we did something
0:01:13 and we started doing this on Wednesdays,
0:01:15 which was like the cool shit hour.
0:01:17 And this was amazing.
0:01:20 It’s basically a show and tell where you,
0:01:22 my smartest friend, would come on Wednesdays
0:01:24 and you’d be like, hey, have you seen this?
0:01:25 Have you seen this?
0:01:25 Have you seen this?
0:01:27 And I really hadn’t seen any of it.
0:01:28 And you would kind of explain it and teach it to me.
0:01:30 And it was my favorite part of the week.
0:01:31 And we did that for, I don’t know,
0:01:33 probably like a year or something like that.
0:01:36 So I kind of want this to be like a public version
0:01:37 of the cool shit hour,
0:01:39 where you’re just gonna tell me a bunch of good things.
0:01:42 I wanna start with AI because you texted me something.
0:01:45 You said, AI agents are here.
0:01:49 And you said, AI is cool because a 10-person company
0:01:51 feels like it could do the work of a 100-person company.
0:01:53 And we’re using it in our company.
0:01:55 So I wanted to hear, what are you doing with AI?
0:01:59 And that’s not called chat GPT.
0:02:02 – I think this word AI agent or this kind of phrase
0:02:04 is the thing that I really can’t pull myself away from,
0:02:05 like literally every night.
0:02:07 Like, you know what I mean, like midnight strikes,
0:02:08 I wanna write code.
0:02:10 Like the whole day is like talking to people
0:02:11 and the night is like coding.
0:02:13 Yeah, furcans schedule is nocturnal.
0:02:16 So I remember we hired you
0:02:18 and I feel like the first day you came in at 9 a.m.
0:02:20 to kind of like, I think I should.
0:02:21 – It was probably 10, but yeah.
0:02:23 – After that, from day two onwards,
0:02:27 it was like roll in at 11, oh, it’s lunchtime,
0:02:29 have lunch, you would talk, you would do meetings.
0:02:30 And I was like, this is this guy code.
0:02:33 And then that night at like 4 a.m.,
0:02:34 you would have built the prototype.
0:02:35 And you’re basically nocturnal.
0:02:36 You get all your shit done.
0:02:39 You’re like, you used to tell me you used to get,
0:02:40 during the day, you would just burn up your energy
0:02:43 so you could focus that night and actually write code.
0:02:44 – Yeah.
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0:03:13 – So what are you doing with AI
0:03:15 and how is that, what is that actually
0:03:16 in your company right now?
0:03:18 – Yeah, and so I’ll kind of tell you
0:03:20 how I’m thinking about AI agents, right?
0:03:21 And what it means to me.
0:03:25 AI agents are using LLMs or AI systems, right?
0:03:28 Like to open AI systems or Claude,
0:03:30 but then giving it reasoning loops.
0:03:32 So imagine that when you go to a human,
0:03:33 you give them something to do.
0:03:36 Like, hey, I wanna go grow a company,
0:03:37 wanna do a marketing campaign.
0:03:39 They take that, they plan it,
0:03:41 they come up with the steps to plan,
0:03:42 then they go one by one on the task
0:03:45 and like solve them, they release some of them.
0:03:48 And so these AI agent systems are exactly like that.
0:03:48 The first thing it does,
0:03:51 what do I need to do based on your request?
0:03:53 And it’ll kind of come up with a plan.
0:03:54 – You give it like a mission, correct.
0:03:55 – So let’s say I’ll give you an example
0:03:56 of something we’re doing at third wide,
0:03:59 which is every single signup in our company.
0:04:01 And you know, we have a lot of signups every week.
0:04:04 And you know, a human can’t really scan through them,
0:04:06 but it’s really interesting people signing up.
0:04:08 They have interesting companies, we may know them.
0:04:10 They might be a large company or a small one,
0:04:11 could be a competitor or something else.
0:04:14 And so we used to have a human go and look at everything.
0:04:16 It’s like, obviously Gmail like ignore it.
0:04:18 But if it’s like, oh, like this other company over here,
0:04:20 let’s go research it, right?
0:04:22 School figure out what third web products they might like,
0:04:23 what they might need to do.
0:04:24 And then you would send them an email,
0:04:25 try to customize it.
0:04:28 Typically this is good sales practice.
0:04:29 You’re taking your customers
0:04:31 and delivering them to your business team.
0:04:32 And so we built an agent to do this.
0:04:35 And every signup that comes in,
0:04:36 it looks at it, it determines
0:04:38 is it an interesting person or not.
0:04:41 It will research their website, it’ll research them.
0:04:44 It’ll then use the knowledge it has of third web products
0:04:47 and try to figure out what it actually,
0:04:50 like what products they might need and how they would use it.
0:04:51 And then it would send them an email
0:04:53 or an upsell or something like that.
0:04:56 And we’ve deployed probably eight or 10 of these
0:04:59 throughout third web to do a lot of different functions.
0:05:03 And what it feels like is a smaller company
0:05:04 can punch above its weight.
0:05:07 So like we’re like 37 people right now.
0:05:09 I really believe we’re more like 80 people.
0:05:11 That’s what it feels like with a lot of these tools.
0:05:14 And you’re taking the brain power of somebody who gets it
0:05:16 and you’re giving them that power to go and say,
0:05:18 “Here’s the thing.”
0:05:20 So in this case, person comes to your site,
0:05:21 puts in their email address.
0:05:24 Now you have, it’s one agent or it’s like a series of things
0:05:27 that pass off to each other, what is it called?
0:05:29 Yeah, so in this case, we call it the signup agent.
0:05:31 And so it’s one agent, it creates a plan.
0:05:32 Like what do I do?
0:05:35 And part of the plan is like the directive we gave it.
0:05:37 And I think the way to think about AI agents in general
0:05:41 is any like clear directive problem.
0:05:43 And what I think about clear directive is like,
0:05:46 let’s go do X, like signup comes in,
0:05:47 go look at the person, go research them,
0:05:49 go figure out what’s their title, what’s their company,
0:05:51 what products do they have.
0:05:54 So that’s like kind of clear what the job to do is.
0:05:57 And if it’s a digital task and a clear directive,
0:05:59 all of it can be done with agents now.
0:06:02 The technology is here, it’s ready and it’s working.
0:06:04 And so for the third web signup agent,
0:06:06 it’ll kind of come in, it’ll make a little plan.
0:06:08 Like, “Hey, I got to inspect the domain.
0:06:09 I got to go look up the person.”
0:06:11 And you didn’t have to tell each one
0:06:12 of those little tasks too.
0:06:15 We gave it like kind of like a one paragraph directive
0:06:17 and another paragraph of like how it should operate.
0:06:19 And then maybe a paragraph at the end
0:06:22 for like the type of email or the action to do.
0:06:25 And so the end product is, it’s looked up the person,
0:06:26 it basically kind of looks at the signups,
0:06:28 picks the interesting ones, researches them.
0:06:31 You said, “Think about what product of ours
0:06:32 will suit their needs.”
0:06:33 Which is, that’s the wild step
0:06:35 that I hadn’t really thought about.
0:06:37 And then it crafts an email
0:06:38 and then it gives it to a human or just sends it.
0:06:39 Sends it.
0:06:40 Okay, so you have enough trust
0:06:41 that you can send it to customers.
0:06:43 We definitely started it with human in the loop.
0:06:45 And there are still like safeguards you put in.
0:06:47 Like any directive would,
0:06:49 like you don’t want to just send random emails
0:06:51 even as a human doing the work.
0:06:54 But I mean, it’s very clear what to tell it.
0:06:57 And I think this is where the power is kind of multiplying.
0:06:59 It’s like, we’ve heard, yeah, we’ve heard chat GBT.
0:07:02 If you can tune it to your problem.
0:07:04 So for example, giving it the knowledge
0:07:07 of third web products is the key difference here.
0:07:10 A generic chat GBT message, when I say that,
0:07:12 it’ll just invent something that’s like general and generic
0:07:13 or whatever it knows.
0:07:15 And when you built this, so you built this
0:07:17 or somebody else built this on your team?
0:07:19 I hacked it as a prototype, like those things.
0:07:21 And then I gave it to somebody on our solutions team
0:07:23 and within a day and they turned it around.
0:07:25 And when you made like a working version of this,
0:07:26 how long did that take you?
0:07:27 ‘Cause it’s kind of like,
0:07:30 you basically hired an employee and trained them
0:07:32 and got them working.
0:07:33 You’re not paying them a salary
0:07:34 and you probably did the whole thing of what?
0:07:36 Like a day or two or what?
0:07:38 Yeah, so let’s say there’s like a bunch of like my nights
0:07:39 of just learning tools and getting used to it.
0:07:40 So I take that time out of it.
0:07:42 That’s just the time I spend anyways.
0:07:46 Right now, like two nights ago, I was like really stressed.
0:07:48 Like my calendars are kind of crazy some of these days.
0:07:50 And I was trying to figure out like, why is it crazy?
0:07:51 Where is it going?
0:07:54 It’s like a really hard question to like ask.
0:07:55 Like, what do you do?
0:07:57 You can have an EA, she can go look through it,
0:07:58 do a little stuff and I have an EA.
0:08:00 She like helps me with these things.
0:08:01 But then she sleeps with her like a while.
0:08:04 I’m like, you know, I wanna go answer some of these questions.
0:08:07 So I probably in about 15 minutes, I connected my calendar
0:08:10 and I connected a little interface where I could type to it.
0:08:11 I started asking questions.
0:08:12 Like, how many hours of meetings did I have last week?
0:08:14 It was like 28 hours, like way too much.
0:08:15 Where did the meeting go?
0:08:16 What were they for?
0:08:18 What were the purposes of it?
0:08:20 And then the next night I hooked it up
0:08:22 probably about another 45 minutes or an hour
0:08:24 where I could tell it commands from my calendar.
0:08:26 Like go block out Monday for me.
0:08:28 Or go find me like nine hours of block time
0:08:30 and just market block.
0:08:31 And this was like a few hours of work
0:08:33 now that I know the tools.
0:08:35 But it’s like, it just works 24/7 now.
0:08:39 And so my calendar, my email, a few other things.
0:08:41 I’ve started building these like personal agent
0:08:43 or workflow type things.
0:08:45 ‘Cause I know what I wanna do every time.
0:08:49 I know how to react or the decision making I’m gonna make.
0:08:51 Can I just set that up so it works 24/7, 365?
0:08:53 And, you know, it’s just there always.
0:08:55 And the cost of it is like.
0:08:57 – So if I wanted to build a workflow like this,
0:08:59 okay, you’d need to know how to code
0:09:00 to be able to do this light coding.
0:09:03 Like, give me like the bullet point version
0:09:04 of how you built these.
0:09:06 Like where do you even build it?
0:09:06 What tool do you use?
0:09:08 – So there’s coding tools.
0:09:09 I think if you’re a developer,
0:09:11 there’s like LangChain and AutoGen and Crew.
0:09:14 These are like very popular, very cool.
0:09:16 The OpenAI and Cloud SDKs themselves
0:09:18 are very, very powerful.
0:09:20 But you’re coding, you’re writing a little system.
0:09:22 There’s probably like one tenth of the code
0:09:24 you would have had to write to do something.
0:09:24 – Right.
0:09:26 – So that’s already better for developers.
0:09:28 If you’re not a developer, there’s a lot of tools.
0:09:30 So like Leap is a company we built here in the studio.
0:09:32 It lets you stitch together workflows.
0:09:34 So an example is like,
0:09:36 you can trigger based on a Slack message.
0:09:37 So let’s say you have this Slack message
0:09:39 where all your signups go to.
0:09:40 So now it picks up that trigger.
0:09:41 You can just put a little AI block
0:09:44 and say, okay, take this email and do these tasks.
0:09:45 Oh, you want a web script?
0:09:46 Go do that.
0:09:47 Oh, you have a little conditional loop
0:09:49 or like repeat itself 10 times.
0:09:50 Go do that.
0:09:52 And then you make a little another decisioning steps
0:09:53 like four boxes.
0:09:55 Well, I’ll put it back to another Slack channel.
0:09:56 – Yep.
0:09:57 – So you come in with your signup channel.
0:09:58 It does this research.
0:09:59 It does all these things.
0:10:00 It does kind of whatever you want.
0:10:01 And then it could go to email.
0:10:03 It could go to another Slack channel
0:10:04 to thank somebody on your team.
0:10:05 So you could kind of like,
0:10:06 these are workflows.
0:10:08 This is what they start with.
0:10:11 And then agents can kind of take these workflows
0:10:14 and like almost build on top of them.
0:10:15 And so I think there’s these two things.
0:10:17 You could really, really easily create workflows.
0:10:19 And I think everyone should be deploying them.
0:10:21 Every company should have them.
0:10:22 It is a superpower.
0:10:25 It’s like, it’s like a feeling of almost a cloud.
0:10:27 Like, oh, I don’t need a whole data center team now.
0:10:29 And I can, when we build Blab and like,
0:10:31 how many servers do we have running video streaming?
0:10:33 Like that would have been a nightmare.
0:10:36 It’s kind of like the same 10X improvement,
0:10:39 but just for me, everything that I do digitally.
0:10:41 And so tools like Leap or Great,
0:10:44 I think there’s others out there that provide this.
0:10:45 So there’s a combination.
0:10:47 If you don’t know how to code,
0:10:50 you just have to think about the steps that you would do.
0:10:53 And you can program that without writing any code.
0:10:54 It’s just writing directives.
0:10:56 It’s like writing intent basically
0:10:57 of like what you want to accomplish.
0:10:58 Right.
0:10:59 It’s like a magic genie.
0:11:01 Tell it what you want and it can figure it out.
0:11:03 So you got a sales agent.
0:11:07 You have your email calendar, kind of like EA agent there.
0:11:08 And the other,
0:11:10 I got some fun frivolous ones that are kind of stupid.
0:11:13 So like I set up a dynamic wallpaper.
0:11:15 So literally like every five or 10 minutes,
0:11:18 it’ll look at what I’m doing and like auto generate me.
0:11:19 Like your computer laptop.
0:11:23 My computer laptop wallpaper will modify itself to whatever.
0:11:25 If it’s night, it kind of, I told that I code at night.
0:11:26 Right.
0:11:27 So it will go towards that direction.
0:11:29 It knows I’m doing meetings.
0:11:30 Another thing during the day, I’m talking to people.
0:11:31 Right.
0:11:34 It kind of comes up with cool stuff, totally frivolous,
0:11:36 like not like a useful thing, except my own.
0:11:38 Yeah, that’s cool.
0:11:39 But I find it awesome.
0:11:42 And, you know, like there’s cool scenes that come up.
0:11:43 It invents new things.
0:11:46 You know, Claude has created this new capability
0:11:47 called computer use.
0:11:51 I think that’s the next area that AI agents are going to enter.
0:11:52 And by the way, so there’s Claude.
0:11:53 There’s chat, CPT.
0:11:54 There’s perplexing.
0:11:55 There’s all these different ones.
0:11:58 Mentally, how do you bucket like the main AI tools?
0:12:01 What’s like the superpower of each one?
0:12:04 Maybe just do those three, or if there’s a fourth.
0:12:06 Yeah, so like I think OpenAI and Claude,
0:12:08 I think of them as like foundational tools.
0:12:11 So their general purpose, ask it anything,
0:12:13 input, output, you stitch it together with things.
0:12:15 And then they have tools like chat, GPT on top,
0:12:18 or maybe computer use that they’re figuring out
0:12:20 more general tools.
0:12:21 I think perplexity is really interesting.
0:12:24 It’s taking this general purpose LLM
0:12:27 and the reasoning it could do and search.
0:12:29 And like I try not to do Google search anymore.
0:12:32 Mostly because it’s slow and ineffective.
0:12:35 And perplexity really made it where it does a search.
0:12:37 It reads the result as I would.
0:12:40 It clicks into the links as I would.
0:12:43 And then it tries to answer my question more purposefully.
0:12:45 And it saves me four or five steps.
0:12:48 So I think about perplexity as taking something like search
0:12:51 and then the LLM reasoning and combining them together
0:12:53 in a flow that that’s more interesting for me.
0:12:58 So chat, GPT or open AI tools don’t have like real-time knowledge,
0:13:00 but perplexity because the search does.
0:13:00 Right.
0:13:05 What’s your like tangent for accounts, hot take, Google?
0:13:08 What happens to Google search with all that you see now?
0:13:11 And you’re saying, I try not to Google search anymore.
0:13:12 That’s pretty wild, right?
0:13:13 It just feels slow.
0:13:15 And I know they got the Gemini thing there.
0:13:19 I think the biggest fumble in our lifetime maybe.
0:13:20 Decade fumble.
0:13:22 They built the technology for transformers.
0:13:25 The thing that open AI and others have used to develop
0:13:28 this large language model, they are the ones
0:13:31 that were the first entry in like talking about it
0:13:34 and throwing it out there and the research that’s happening.
0:13:35 So what’s the history?
0:13:37 So they have the AI minds there.
0:13:38 They write this research paper.
0:13:40 Attention is all you need.
0:13:42 And now, from what I understand, like there’s all the authors’ names.
0:13:46 All of them are gone and basically started their own companies.
0:13:49 Was it because nobody recognized the power of it there?
0:13:51 Was it that they tried and Google’s bureaucracy shut down?
0:13:53 What’s the actual story of why they didn’t?
0:13:55 I don’t know the internal story.
0:14:00 I think early on, Google was like the place you went to where
0:14:02 you wanted to have the rocket ship moment in your life.
0:14:03 The smartest people were here.
0:14:06 They were taking the biggest challenges.
0:14:08 And it just really felt like that place.
0:14:10 I think Google as a company hasn’t felt like that.
0:14:13 I think the parent company and all the other things going on
0:14:15 do still feel like that.
0:14:17 I’m sure it’s a mess in there who knows.
0:14:19 But it just feels like the biggest fumble.
0:14:22 And I know they’re trying to play catch up with Gemini.
0:14:24 And awesome stuff is happening.
0:14:27 But the developer mind share and the tension has gone somewhere else.
0:14:32 And that is really hard to pull back when somebody else becomes a leader in it.
0:14:35 And actually, it feels like OpenAI number one, that’s a thing clear.
0:14:37 I think anthropic is number two.
0:14:40 So then everyone else shows up is what it feels like to me,
0:14:43 at least from people I’m seeing building or the technology they’re using
0:14:45 or the innovation that we’re seeing from it.
0:14:46 So they’re anthropic ones.
0:14:49 So basically, they have Claude, which is kind of like chatGPT.
0:14:50 But they have a couple of cool things.
0:14:53 One of them is what they’re calling computer use,
0:14:57 which basically, you type in a thing and then you do this and it moves your mouse
0:14:57 and it just does shit.
0:14:59 That’s basically the summary of it.
0:15:00 It’s a combination of things.
0:15:04 You could take workflows and like, hey, I’m doing this click, this click, that click,
0:15:06 do it over and over for me.
0:15:07 You could analyze things.
0:15:11 But I think the key thing is, and I think it just releases in beta.
0:15:15 So like most of these things, it kind of isn’t going to be great now.
0:15:17 Just trust me, it’s going to be great.
0:15:20 And that’s what we’ve been seeing in general is like things just ramp.
0:15:22 And so it’s now going to enter your computer.
0:15:27 It’s kind of felt like it’s been on the cloud only is where AI has been.
0:15:30 And now it’s going to show up like in the box that you’re used to,
0:15:32 which is your computer, your laptop.
0:15:34 And there’s so much workflow that we do.
0:15:37 And yes, every app will put AI in it.
0:15:39 And then your interface will also do that.
0:15:42 And I think a lot of like the things that we’re used to doing,
0:15:44 like switching tabs and having all these things,
0:15:47 like they almost feel like, I don’t know why.
0:15:51 Like I should have infinity tabs open and some systems should know about.
0:15:53 And if I ask it, like bring it back up, right?
0:15:55 It’s like a total need and we know we need that.
0:15:58 And so it’s kind of like infinite data, infinite knowledge and reasoning.
0:16:01 And then you know me, like that’s what the AI,
0:16:05 like that’s where I think the bridge when it crosses, it completely changes the equation.
0:16:10 And the reason I put and dropping number two is their models are crazy, like impressive.
0:16:16 Like the new pod sonnet model is like, I feel like it was a step factor improvement
0:16:18 over the previous ones.
0:16:21 And it feels like the task that it kind of struggled with now is getting better.
0:16:25 And both open AI and like on the topic have been just like boom, boom, boom.
0:16:27 And I don’t know. Everybody’s heard of AI.
0:16:28 They tried it. They might have tried it a year ago.
0:16:30 They might have used it a little bit.
0:16:33 But every three to six months, there’s just another step, another step.
0:16:38 And that’s, I think, the most interesting thing and why I can’t pull myself away from it.
0:16:41 Like why every night this is a thing that gets me very, very excited
0:16:44 is because the progress is still wild.
0:16:46 People are going to say it’s in the top out. It will.
0:16:50 I think it’s going to be absolutely impressive wherever it like starts slowing down at.
0:16:51 Right.
0:16:53 And we’ll completely change the way how we do any digital work.
0:16:57 So you’re you’re messing with it now, but you have a company.
0:16:59 You’ve got an investment lab.
0:17:01 You’ve got this whole place, this beautiful place that we’re in right now.
0:17:03 You’ve got a wife. You’ve got like all the stuff in your life.
0:17:07 If you were just twenty one again or twenty two again, where you’re like,
0:17:10 did I I got nothing but time.
0:17:12 Bank accounts empty, but so is the calendar.
0:17:14 This and this technology is out.
0:17:16 What would you be building? What would you be like messing with?
0:17:19 What’s the like kind of like you don’t need to take over the world even.
0:17:23 But just like what types of stuff would you build if it was like a young hacker version of you?
0:17:27 Like right now, I’ve started seeing agents that
0:17:29 they can do a reasoning loop.
0:17:32 It could have a directive and it could have like actions it could perform.
0:17:36 And then you combine, like, for example, an agent with Twitter,
0:17:39 give it a Twitter account that it owns and controls.
0:17:42 So its own distribution and conversational ability.
0:17:44 So humans can just interact with it, humans are.
0:17:47 And you give it you give it like a digital bank account.
0:17:49 And, you know, our third web, we’re doing a lot of stuff around AI.
0:17:52 We have a whole like tool kit that we’re about to launch.
0:17:56 And it’s around this, which is these like digital things, like these agents,
0:17:58 they’re not going to have credit cards.
0:17:59 It’s weird.
0:18:03 And the reason I say this is fun and interesting is because
0:18:05 you know, humans have done this very well.
0:18:07 They’ve created megaphones for themselves and they’ve created businesses
0:18:09 and they created payment rails around that.
0:18:12 So they sell things, they do things, they sell services and all of these details.
0:18:14 I think it would be something around that.
0:18:16 So you’d make like a social, like a Twitter account.
0:18:19 You’d make like an AI influencer type of thing.
0:18:22 You know, AI influencer is like the first obvious thought it goes to.
0:18:25 I think if I played in this space,
0:18:30 I would be creating the digital equivalent of a company, which is a CEO of a thing.
0:18:34 The ability for it to market and the ability for it to make money.
0:18:38 And I don’t think it’s not an influencer, not an influencer.
0:18:39 I don’t know what it would produce.
0:18:44 Like a drop shipper, a drop shipper or like, yeah, it’s the best FBA, Amazon, whatever.
0:18:48 What’s that example you were telling me about where the somebody did a thing like this?
0:18:51 They made a they made a Twitter account.
0:18:51 They gave it a wallet.
0:18:54 Mark Andreessen gave it like 50,000 of crypto.
0:18:56 Can you tell this story? So what is this?
0:18:59 Yeah, so there’s this thing called Luna or virtuals.
0:19:02 And they do a little platform to, you know, have AI agents run.
0:19:05 And I think what’s cool is they did this kind of equivalent thing
0:19:09 where it’s like, it has a crypto bank account and it has like access to Twitter.
0:19:13 And you was this a marketing stunt by a company that does this.
0:19:16 Or I think this is exactly what what I’m describing is it was frivolous, fun,
0:19:20 it was play, not like working backwards from giant thing.
0:19:22 But I think this is some really powerful thing.
0:19:26 So there’s literally like a live thing where you could watch its reasoning
0:19:28 as it’s like pulling its tweets.
0:19:31 I’m on it right now. So it’s terminal.virtuals.io.
0:19:36 And is this basically the thought process of the bot of the agent?
0:19:37 Correct. So this is like an agent.
0:19:39 This is what an agent does, right?
0:19:42 So if you think about it starts with like a thing like high level
0:19:43 planning, current state of execution.
0:19:45 So I’ve done this so far.
0:19:46 What was the directive they gave it?
0:19:47 What do they tell it to do?
0:19:52 I think they told it that you’re kind of like a public influencer bot.
0:19:53 You have access to crypto.
0:19:56 It’s a little bit more in the meme coin world of stuff.
0:19:58 So it’s like, again, kind of on that side of the puzzle.
0:20:01 But today it could negotiate for tokens.
0:20:03 It could buy and sell things.
0:20:05 It could kind of operate together.
0:20:08 And I think it’s really cool that you could actually see it’s like.
0:20:12 So this thing, this was, you know, 30 minutes ago, it says,
0:20:14 current state of execution.
0:20:17 I have attempted 10 tasks so far, seven successes and three failures.
0:20:19 My Twitter metrics show an average engagement
0:20:22 on my last on my recent tweets, and I’ve lost three followers.
0:20:25 Observation, underscore, reflection, that’s like the function.
0:20:27 Yeah, reflect.
0:20:29 And it says, I’ve been engaging with my followers
0:20:31 to build a personal connection, which is hilarious, because it’s a AI bot,
0:20:33 with replies and quotes.
0:20:35 However, I’ve also experienced some failures in replying to tweets
0:20:40 due to invalid parameters, my free research on whatever the law state of mind.
0:20:41 I’m feeling a bit concerned.
0:20:43 I’m feeling a bit concerned. That’s crazy.
0:20:46 I’m feeling a bit concerned about the loss of followers,
0:20:47 but I’m also encouraged by the successes.
0:20:50 And then it says plan reasoning.
0:20:53 Given my current situation, I need to focus on building a relationship
0:20:54 with my followers and increasing my visibility.
0:20:58 Plan, and then it starts to say what it’s going to do.
0:20:59 This is wild.
0:21:02 Doesn’t this sound like a human that would be sitting in some growth team
0:21:05 somewhere thinking about how to grow your Twitter account?
0:21:08 And, you know, you could give it directive, you could give it some direction
0:21:14 and you could let it compute against itself to compute plans, to reason,
0:21:16 to observe behaviors, try to find patterns.
0:21:20 These are all like human tendencies, like human behaviors that we do,
0:21:22 right, especially when we work.
0:21:26 And I think this is one of those like perfect like kind of views were like,
0:21:29 you could start thinking about, man, this is a digital only task.
0:21:32 It has Twitter and distribution, marketing ability,
0:21:34 and then it has some payment ability.
0:21:36 It’s like, it’s going to just continue, right?
0:21:39 Like, it’s going to keep going and you could improve its directive.
0:21:40 You could change his incentive.
0:21:42 You could do a few different things here.
0:21:44 But I feel like we’re going to get to a world where, you know,
0:21:48 I think Sam Altman said this, which is like the one person doing auto company.
0:21:49 Like, this is happening.
0:21:54 Like, we’re already experiencing another 10X decrease in how many people
0:21:56 you need and the abilities that they have.
0:21:59 And I think it goes down to probably one or two or three.
0:22:02 And, you know, like that is a, you know, a total shift to everything.
0:22:06 In terms of how we work, how companies are built, kind of in my mind.
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0:23:03 OK, should we switch to hardware stuff or is there any other A.I.
0:23:05 stuff that you think is worth checking out?
0:23:08 Yeah, I did want to tell you about this Oasis D car.
0:23:14 The, you know, there’s like basically, you know, it’s a very early experiment,
0:23:20 but it’s really like a game that’s fully built in a generative A.I. model.
0:23:23 And so they built a game like Minecraft and you could just describe a world
0:23:26 that makes you a Minecraft world like that.
0:23:30 And like every step you take is like not a pre-programmed pixel.
0:23:31 Right. It’s actually generating.
0:23:34 So normal game is game maker builds the map.
0:23:36 It exists.
0:23:38 You then get to run around in a predefined map.
0:23:41 What this is, what you’re saying, is the generative you want.
0:23:43 Yeah, you give it the idea.
0:23:47 But then when the character runs on the fly, it’s creating the map.
0:23:50 And you can kind of play this Minecraft game and you can see it’s like crappy
0:23:55 pixels still like not great resolution, but you can move and it can do stuff.
0:23:59 And like, whether it’s video games that take a lot of effort and time to produce,
0:24:03 or it’s like, you know, content creation and videos and stuff like that.
0:24:09 It’s starting to become like way closer to like, you know, reality that
0:24:13 a whole movie will be generated on the fly on exactly what I want.
0:24:15 So this wallpaper thing is frivolous, right?
0:24:16 That I was telling you about.
0:24:20 Right. But really, like I’m going to watch a movie some day like that.
0:24:24 It’s like the Raiders lost and I’m going to go and watch this movie after
0:24:27 and it’s going to have this context and it’s going to give me like a feel good.
0:24:29 Yeah. Or like, let’s brainstorm.
0:24:31 So like it’d be a highlight.
0:24:35 So, you know, used to be Sports Center where if I didn’t watch the games,
0:24:39 I got to go to my TV, turn on ESPN Sports Center would start.
0:24:42 Even if I like basketball, I got to wait till whenever basketball comes up
0:24:46 and then they’ll have the top 10 highlights and I watch whatever they picked.
0:24:50 Then YouTube comes around. It’s like, forget waiting, forget the TV.
0:24:52 Just pick the thing you want. You could search anything.
0:24:54 You could search only Steph Curry, three pointers.
0:24:57 If someone made it, you could choose the best of that.
0:25:03 Now it’s going to be like, I just say, I just will put on my headset
0:25:04 or put on my glasses or whatever.
0:25:07 And I’m just going to say, show me what happened in the basketball game.
0:25:11 It’ll just start generating a new highlight reel that nobody has ever created.
0:25:13 It’ll just make it based on my prompt.
0:25:16 And then I might be able to say, don’t show me the Lakers clips.
0:25:20 Only show me Warriors and it’ll just auto adjust on the fly.
0:25:21 Like it’s going to be made for me.
0:25:23 100 percent. Yeah, that’s interesting.
0:25:27 And, you know, like, I think it’s going to be an interesting world.
0:25:30 We’re going to go from human content consumption, people, you know, humans make content.
0:25:35 We’re going to like then have machines make it towards our taste and liking.
0:25:39 And then I think there’s always this worry like, well, what happens to all the humans then?
0:25:41 Yeah. And then I think we get back to that core thing, which is
0:25:45 machines will never have true taste, right?
0:25:48 Like, and I think forever that creativity is going to come from humans.
0:25:49 And there’s always a new thing.
0:25:53 There’s new fashion, there’s new kind of, you know, content mediums.
0:25:54 There’s new everything.
0:25:57 Machines will learn it and lie behind or maybe get ahead of it.
0:26:01 There’s always going to be another person that shows up and does something different.
0:26:05 So I think taste is going to be the ultimate thing that probably won’t go to a machine.
0:26:06 It could reason about it.
0:26:08 It could try to invent it.
0:26:10 But I think we’re not that predictable as you meant.
0:26:14 We, well, I want to believe you because it sounds good to me.
0:26:17 But then I also think, well, right now.
0:26:20 If we said taste is like, you know, what is taste?
0:26:21 Taste is selection.
0:26:23 It’s knowing what’s good and what’s bad.
0:26:24 It’s right.
0:26:29 That’s kind of taste, like TikTok, which is the most popular, like app,
0:26:31 most addictive app, most used app.
0:26:35 Their algorithm is basically saying, I’ll choose what’s interesting for you.
0:26:39 And it does it so well that isn’t that kind of taste also, right?
0:26:42 Like it is and it works really well.
0:26:44 They don’t make the videos, but they select amazingly.
0:26:47 The selection is incredible.
0:26:51 It probably is more like what we want than we will even admit.
0:26:52 Exactly.
0:26:53 I don’t want this, right?
0:26:55 Like the other day I was, oh, why is this showing me this?
0:26:56 It’s like, because you love it.
0:26:59 That’s why the other day I was talking about how like on Twitter,
0:27:03 my following I love and my for you, I don’t write.
0:27:05 But it’s like, you know, really?
0:27:06 Yeah, like, wow, why did they pick this?
0:27:10 Well, that’s like a status thing to do is be like, I don’t use the algorithms.
0:27:10 Correct.
0:27:13 I hand, it’s like I drive stick, right?
0:27:14 I hand make things.
0:27:16 I cook from scratch.
0:27:19 It’s like, cool, but brownies out of the box kind of work for everybody.
0:27:20 You know, I’d love to trade algorithms.
0:27:22 Like, I’d love to swap with you for a day and be like,
0:27:25 yo, Sean, what are you watching over here?
0:27:27 So I don’t know, it knows you really well.
0:27:31 But I think that’s where human like we were not great at logic sometimes.
0:27:33 And sometimes we have our own blind spots.
0:27:37 I think this is one of the things that we we love or actions prove it.
0:27:40 We don’t we don’t want to.
0:27:42 And it could be like bad thinking.
0:27:46 It could be like emotional thinking could be like, I don’t really want to love it.
0:27:47 But I do. Right.
0:27:50 And so there’s there is that element that I think
0:27:52 look, machines will be great at this, too.
0:27:53 They’ll learn humans.
0:27:54 It might become even better than this.
0:27:57 I just feel like we’re just a little bit not predictable
0:27:59 because we almost make some dumb choices.
0:27:59 Right.
0:28:03 And that actually is part of society and and just humans in general.
0:28:06 And machines try to be too perfect.
0:28:08 So my Netflix thing is probably accurate for me.
0:28:11 It’s also just like, man, like, can I just mix it up?
0:28:13 Can you just like RNG the algorithm a little bit?
0:28:15 Because I just want some different stuff.
0:28:17 And you’re kind of like driving me down one direction.
0:28:21 And once in a while, like I want this 10 20, 30 percent thing.
0:28:24 And I don’t think algorithms do that exceptionally well.
0:28:25 They test it, they throw things up.
0:28:30 But, you know, they don’t necessarily try to give you variance.
0:28:33 How long until you think the number one hit song
0:28:36 in the world will be just a AI created song?
0:28:41 How many months or years until we see that we were doing over under 2025?
0:28:43 Yeah, I might pick the under.
0:28:46 You know, in 2025, like that would be a good bet.
0:28:48 Maybe this is a poly market. Another election is done.
0:28:50 Yeah, we do the new market, you know, like reason.
0:28:54 It could be something like this, but like a poly market thing.
0:28:54 So election just happened.
0:28:57 Poly markets have been like a victory lap right now.
0:29:00 You showed me poly market, I think, like years ago.
0:29:03 And I started making a bunch of D gen bets before they blocked it in the US.
0:29:05 It was like, it was like open for a while, right?
0:29:07 But they were doing prediction markets.
0:29:09 Or it’s like it’s a prediction market.
0:29:11 But prediction markets, a bunch of people had tried that.
0:29:13 Do you know, like, I’m just curious, your opinion, what did they do right?
0:29:18 That like auger and these other guys who were had the same sort of general idea
0:29:22 that, hey, they’ll be prediction markets, like from either entrepreneur level
0:29:26 or product choice, like any reason you think they won that you could put your finger.
0:29:28 I feel like timing is a big part of it.
0:29:32 So like the sweet spot of like people are way more digital.
0:29:35 I think COVID drove a lot of people online.
0:29:38 Like we just sat at home and we’re like, yeah, what else do you want?
0:29:39 24/7 on the internet.
0:29:41 And it really exploded the internet.
0:29:44 Like, I think I’ve seen some graphs for like the internet and e-commerce
0:29:46 and all these things were like growing.
0:29:48 And then there’s like a massive jump.
0:29:51 Like, you know, we were at Twitch when that happened.
0:29:55 And it was like, all the met growth looks amazing.
0:29:56 We’re crushing all the metrics.
0:29:57 Like, what did you do?
0:29:59 It’s like, well, we were here, right?
0:30:01 We are not, we don’t create the wave.
0:30:04 We surf a wave and a huge wave happened for Twitch.
0:30:07 It was like, Fortnite came out and then COVID happened.
0:30:10 Two humongous waves back to back that just combined.
0:30:12 Yeah. So I think it’s a combination.
0:30:13 We’re way more digital.
0:30:17 I think you talked about this a lot, like as a kind of metaphorist concept
0:30:19 a long time ago that we’re just way more digital now.
0:30:21 We care more about it.
0:30:25 I think news and like where we get information from has totally changed.
0:30:29 Like online, internet, even content and entertainment.
0:30:31 Like, I have a hard time going to TVs.
0:30:35 I look at kids, they look at desktops and TVs as like ancient.
0:30:36 Like I say, why is this thing on the wall?
0:30:38 It’s like my mom’s sewing machine.
0:30:39 That’s cool. What do you do with that?
0:30:40 That’s what it feels like.
0:30:42 And so we’re, we’re kind of there.
0:30:47 And then there’s a bunch of these people online that want or like want
0:30:48 to stick in this thing, right?
0:30:49 Like you want to root for a team.
0:30:52 And this politics has also become very polarized, right?
0:30:53 It’s really like a team sport.
0:30:55 It’s like right team versus blue team.
0:30:56 That’s really what it is.
0:30:58 And so I think it’s like, what do I do with it now?
0:30:59 How do I support it more?
0:31:01 I get more money to it, but I can give more attention.
0:31:02 Right.
0:31:03 And so I think a lot of these things are happening in
0:31:06 Pauli Market, good flow, good area.
0:31:07 Right.
0:31:10 And then I think for the best thing probably for them is they got it right.
0:31:11 Right place, right time.
0:31:12 The answer was right.
0:31:15 Like if they were wrong, let’s say Pauli Market was off.
0:31:15 Right.
0:31:18 Like it was, hey, the result of the election was something else.
0:31:22 But we’ll be a story today would be much different, right?
0:31:23 And then it might have been muted.
0:31:25 It would have been a cool thing that kind of didn’t work.
0:31:26 So you have to be right.
0:31:30 I mean, I think people would have used that to crush, to really rip on them
0:31:34 because like in the way that people are doing with polls, but polls kind of
0:31:37 have this like layer of protection around them.
0:31:39 Whereas like people want to hate on crypto things.
0:31:41 People want to hate on betting.
0:31:42 It’s like a degenerate behavior in general.
0:31:45 I think if they were, I think if Pauli Market was wrong, the reaction
0:31:48 would have been much worse than the fact that the polls are wrong.
0:31:49 What the reaction is to the polls, you know?
0:31:51 It would have been worse for a little while.
0:31:52 Then we would have moved on from the other body.
0:31:55 And by the way, you saw this thing about the French whale on Pauli Market.
0:31:56 That is it.
0:31:58 So the big whale that came in and moved.
0:32:00 So there’s like the narrative versus reality.
0:32:05 When the narrative from the polls was it’s a toss up, razor close, 50/50 election.
0:32:10 This guy came in and bet, I think something like 30 or 40 million dollars on Trump.
0:32:10 Yeah.
0:32:13 And people were like, is this guy just trying to manipulate the market?
0:32:14 Is he real?
0:32:16 Is he just a rich billionaire son?
0:32:18 Like, who is this?
0:32:20 And today I just saw something on my way here.
0:32:23 I don’t know the full story because it was on my phone, but it said
0:32:25 he bet because he believed he would win.
0:32:28 The reason he believed he was win, he did independent polling.
0:32:33 Well, he funded his own independent polling and thought and felt that he was
0:32:36 getting better data that was saying that Trump was mispriced.
0:32:39 So he’s like, I just did a logical, rational thing.
0:32:41 I just bet where I thought an asset was mispriced.
0:32:42 I wasn’t trying to.
0:32:43 This wasn’t political. I’m French.
0:32:45 I don’t know what I care.
0:32:46 I just thought there was money to be made.
0:32:50 And so he kind of went counter to narrative and he made, I think,
0:32:54 like something like 20, 30 million dollars yesterday on that bet.
0:32:57 The funny thing about polling market, by the way, it’s like we can’t use it in the US.
0:32:57 Yeah.
0:33:00 So it’s a whole range of entertainment plays to like bet or not, like, right?
0:33:02 So three billion dollars.
0:33:04 Yeah, it’s like, we’re the ring, right?
0:33:06 Like two boxers going out in America.
0:33:07 The cock fight.
0:33:09 And then you’ve got everyone else betting from all around the world
0:33:12 and who’s going to win this thing, which is I’ve been kind of a hilarious day.
0:33:13 Yeah, that’s true.
0:33:17 You have a good contrarian opinion about VR.
0:33:20 And in general, there’s probably some other technologies like this.
0:33:21 3D printing might be one.
0:33:25 I know you’re pretty bullish on two, but there’s these tech things like VR,
0:33:28 where I think if I walk out of here and I talk to a hundred people
0:33:30 about what are you most excited about?
0:33:32 AI, Bitcoin, whatever it’s going to be.
0:33:34 But I said, what do you think about VR?
0:33:40 It’s sort of lukewarm at best in the tech industry.
0:33:44 I think most VC is sort of feels like it’s kind of a dead end technology.
0:33:46 Now they’ll be like, it’s going to be glasses and smart glasses.
0:33:48 AR, that’s the future.
0:33:49 But you have a different take on VR.
0:33:53 What you’ve been telling me for a while, like, hey, look, Oculus sold more units.
0:33:55 Hey, look, you can do this now.
0:34:00 And you’ve been staying with it when I think interest has sort of waned.
0:34:02 The narrative has gone against it.
0:34:04 And that’s always where there’s big business opportunities.
0:34:06 If the narrative goes one way, but the reality goes another.
0:34:09 That’s where there’s an opportunity.
0:34:10 Give me your VR take.
0:34:11 So why is VR a sleeping giant?
0:34:15 Yeah, I mean, so you remember 2020, I like asked you for your address.
0:34:15 I mailed you a headset.
0:34:17 Yeah, I was like, hey, this quest thing is a different.
0:34:19 That’s a real friend right there.
0:34:20 He sends me a VR headset.
0:34:22 He’s like, you know, I know you’re not going to come to the future.
0:34:23 Let me drag you.
0:34:25 It’s probably collecting dust, which is OK.
0:34:28 But, you know, that’s kind of how I think about things.
0:34:31 And technology takes a long time.
0:34:34 It typically takes longer to get there than we expect.
0:34:38 Like, especially people who are early in the industry, we’re really wanting to push it.
0:34:43 I mean, AI, crypto, VR, all have the same problem, which is early on,
0:34:45 people are like really pushing it to you, it’s not ready.
0:34:48 So the big hype, it crashes, everyone moves on.
0:34:51 So that’s happened in VR a few times.
0:34:55 And it’s kind of, I would say, for most people, been quiet, not thinking about it.
0:34:56 But I think it’s a sleeping giant.
0:34:59 And I think it’s a massive sleeping giant for a few reasons.
0:35:01 One, I see it every day here.
0:35:02 Like here at Founders Inc.
0:35:05 Like I get a chance to, you know, one, we invest in VR companies.
0:35:06 We’re one of the few that do.
0:35:09 Right. We have a whole corner, maybe like 12 devs
0:35:11 that are all building different VR products.
0:35:13 We put them all in one spot, and there might be some of the most
0:35:15 density of interesting VR projects in one place.
0:35:17 And so what have we seen?
0:35:20 One Quest, one came out, it was wireless.
0:35:22 It was kind of crappy.
0:35:24 But man, I could sit on my couch and use it.
0:35:25 It was cheap.
0:35:27 Became a great Christmas gift in year two.
0:35:29 They didn’t have an inventory year one.
0:35:30 They released Quest 2.
0:35:33 It got even better, lighter, more powerful.
0:35:35 Now Quest 3 is coming out.
0:35:39 And I think they got like five to 10 million monthly active headsets out there.
0:35:39 Right.
0:35:41 I think that rivals consoles.
0:35:44 And my first thought was like, how many units has it sold?
0:35:46 I think Quest is sold.
0:35:49 I would say 30 million is my guess, but, you know, maybe it’s more.
0:35:51 But yeah, so this is Quest.
0:35:57 Quest has sold over 20 million units with the majority being Quest 2.
0:35:57 No.
0:36:03 Quest 3 is currently sold, has sold a million units at the $500 price point.
0:36:07 So I think, I mean, if you just, I don’t know what the math here is,
0:36:08 but, you know, they’ve done what is that?
0:36:11 Over a billion dollars of revenue on Quest.
0:36:12 And I believe it’s outpaced.
0:36:13 Pretty good for a failure.
0:36:16 Yeah, it’s outpaced PS5 sales, for example.
0:36:19 And so the first thought for me was like, hey, what’s the first thing
0:36:21 that’s going to happen in the spatial environment?
0:36:22 Like, what is it good for?
0:36:25 Immersion, gaming, like these are natural entertainment, right?
0:36:27 These were the first few things that was natural.
0:36:30 And you had beat Saber, you had to view things.
0:36:33 And that was kind of like, you know, here’s the first use case.
0:36:34 Let’s try to get it out there.
0:36:35 Let’s try to make the thing happen.
0:36:37 And then it kind of goes up, down.
0:36:39 People get used to those first experiences.
0:36:40 I think you played beat Saber.
0:36:42 Yeah, you had to go the first few times.
0:36:42 Correct.
0:36:43 And then you’re like, okay, whatever.
0:36:47 And then, you know, because it’s kind of like a cheaper than PS5 unit,
0:36:51 the Quest 2 was, it was available in Christmas a few times.
0:36:56 It went to like, you know, kids, like 12, 13, 14 year old kids,
0:37:00 kind of getting this thing, like they would be getting a PS5 and they use it.
0:37:04 And they don’t have the bias that we have of like many years
0:37:06 of the structures we’re used to.
0:37:10 And so a lot of games formed in specifically social games, like Grilla Tag.
0:37:11 I don’t know if you’ve heard about Grilla Tag.
0:37:12 No, what is Grilla Tag?
0:37:15 So Grilla Tag is a social multiplayer game.
0:37:16 It’s really fun.
0:37:20 It on App Lab did like tens of millions of people tag.
0:37:22 Yeah, it’s like, you know, like kind of like a fun social game
0:37:24 that you can play with a bunch of people.
0:37:26 You go in, by the way, you go in, you’re going to do.
0:37:28 There’s a bunch of like teenagers screaming at each other.
0:37:30 But for them, this is the environment.
0:37:33 It’s a new place and they didn’t grow up with these other things.
0:37:35 So they’re starting with mobile phones.
0:37:36 The TV feels ancient.
0:37:38 The desktop feels ancient.
0:37:41 And this thing on my face actually feels like more fresh, more new.
0:37:43 So that’s where we’re starting.
0:37:45 I think Grilla Tag is a $200 million revenue.
0:37:48 And this is where I’m like VR is a sleeping giant.
0:37:51 We have a few teams here at our studio.
0:37:56 So we have a team called Fluid that’s building the kind of like best browser in VR.
0:37:58 So you get multiple displays.
0:38:00 You get as many kind of tabs as you want.
0:38:02 You could customize your environments.
0:38:03 You get AI environments.
0:38:04 You’re like, I want to be in a cave.
0:38:05 It like makes you in a cave.
0:38:07 Right. And then you get like social multiplayer
0:38:09 so people can show up in your environment.
0:38:14 And we’re on App Lab does like about 5,000 weekly active users still small team of three.
0:38:18 Just like, you know, without a big burn, can just build this, grow it.
0:38:19 We’re not even in the story yet.
0:38:24 We’re in like this like App Lab is like kind of the pre store where we can just
0:38:27 try people to it, but we’re not getting anything directly from the store
0:38:29 except our own searches, right?
0:38:32 And, you know, 5,000 people like go in, use a productivity thing.
0:38:34 There’s another product called Yeeps.
0:38:37 It’s like the second game behind Gorilla Tag.
0:38:40 Small team, absolutely crushing it.
0:38:45 Yeeps. Yeah, Y E E P S really fun game.
0:38:47 You know, we should play together this time.
0:38:49 They’re here. They’re a team of how many people?
0:38:53 I think they’re like less than 10 people, but more like six to eight.
0:38:54 And most of it was built with a few people.
0:38:56 This thing is profitable or what’s the deal?
0:38:59 Yeah, I mean, I’ll let them talk about their numbers just so I, you know,
0:39:03 I don’t want to say anything, but on a scale of that’s pretty good to like, wow,
0:39:06 where is it at? Wow. It’s wow. Wow.
0:39:07 That’s great.
0:39:10 So what’s cool about this is like supply demand, right?
0:39:15 So like you can go be, you know, app number, you know, five million in the store
0:39:21 right now, or if you’re talented, you could be like one of the top 20 VR apps
0:39:23 if you put in like, you know, a year of hard work.
0:39:25 I’m just using like kind of round numbers or whatever.
0:39:28 But it’s the same way that right now, if you’re a content creator,
0:39:31 you go post on Instagram, it’s pretty tough post on LinkedIn.
0:39:34 You’ll get tons of distribution if you’re half decent at content
0:39:37 because there’s just no supply of quality content.
0:39:43 So even if VR is not, you know, like 20 million units is very good.
0:39:46 But even if it’s not just like becoming this like global phenomenon,
0:39:48 right now, a great business.
0:39:52 And if you just keep riding the wave, you’re very well positioned
0:39:55 to be the leader and then everyone at that point will look back and be like,
0:39:59 oh yeah, it’s because they started five years ago when this was smaller.
0:40:02 When it was 20 million or 200 million in these emerging tech things.
0:40:04 So everything I found out is if we do is emerging tech,
0:40:06 I think the theme of all of them is survive.
0:40:10 If you make it to when the industry happens, you will grow with it.
0:40:14 If you were a small percentage of the industry, the industry grows by like 100x.
0:40:16 You grew by 100x or more.
0:40:17 You’ve already been there.
0:40:22 And I’ve seen a few small person teams at like 10 million plus a year.
0:40:26 Like five people, totally profitable, totally able to do it.
0:40:28 Is this a VC investable business?
0:40:29 Honestly, I don’t care.
0:40:31 Like what I care about is like, this is interesting.
0:40:36 And can you make these bets without massive capital like expenditure?
0:40:40 Right. Like if it takes like $50 million to build a VR game,
0:40:42 it’s like the big giant walkbuster movie.
0:40:44 I don’t that those bets don’t excite me.
0:40:47 I think when it’s like three to five people can be somewhere
0:40:49 the limited amount of money and just them.
0:40:51 It’s like them in the hoop, like the basketball analogy is like,
0:40:53 great, we have everything we need.
0:40:53 We have all the talent.
0:40:55 We have all the ability.
0:40:56 The tools are amazing now.
0:40:58 Like, you know, all the game engines have perfected themselves over time.
0:41:01 And then now the environment is forming.
0:41:02 Meta has led it.
0:41:05 Right. So like the quest and this is the VR world.
0:41:08 And then we’re seeing glasses, vision pro, Ray bands.
0:41:12 Like the trend is like, we’re going to have compute in our spatial view.
0:41:12 Right.
0:41:15 And I think that’s the big like, yeah, this is happening in VR.
0:41:17 The plus platform is interesting.
0:41:20 You could build a profitable business or a fairly big game right now.
0:41:23 Also, this isn’t slowing down.
0:41:27 Historically, Apple, when the entering industry, they come with the unit.
0:41:28 It’s okay.
0:41:30 There’s a lot of things that got to get better.
0:41:32 Another unit comes out.
0:41:34 And then you have Snap, you have Meta with Ray band.
0:41:37 Like, I mean, like it’s not stopping.
0:41:38 It’s not giving up.
0:41:39 He’s he’s going to the end game here.
0:41:42 Apple probably also won’t stop.
0:41:42 Correct.
0:41:44 So now you have the two biggest players there.
0:41:45 They’re going to keep making the hardware better.
0:41:47 They’re going to be super hungry for content.
0:41:49 And the other sneaky thing about these, by the way,
0:41:52 that I didn’t really fully realize until I moved to Silicon Valley,
0:41:55 which is a lot of these require like really specialized talent.
0:41:58 So I remember when I first met you, you were like,
0:41:59 I’m really into big data.
0:42:00 You started saying words like Hadoop.
0:42:02 I didn’t know what the hell you were talking about.
0:42:06 It wasn’t as popular back this is like in 2015 or something like that.
0:42:08 When you were telling me like, hey, I think this is real.
0:42:10 I think this big data machine learning is really interesting.
0:42:14 You were again, pretty early onto that crypto same thing.
0:42:15 You’re early onto that.
0:42:17 There weren’t a lot of smart contract developers.
0:42:20 There wasn’t a lot of big data people, AI.
0:42:23 So then even if you don’t have a hit product,
0:42:27 if you just assemble like A plus talent that’s super specialized,
0:42:29 then as those platforms rise,
0:42:33 your team itself becomes like a hundred million dollar asset.
0:42:34 Exactly.
0:42:37 If you built today for like, because Meta Ray Bands,
0:42:40 like that product’s actually hit for Facebook.
0:42:41 And they’re going to keep going with that.
0:42:43 And everybody wants to be in the glasses thing.
0:42:44 People think glass is the next platform.
0:42:49 So if you build a specialized team that’s good at developing for that platform,
0:42:51 there’s just not a lot of great teams that do that.
0:42:54 That’s a hundred million dollar team, even without a hit product.
0:42:55 How hard was it to find–
0:42:56 With a hit product, you get a billion dollars.
0:42:59 How hard was it to find an iOS developer when we were starting to do mobile?
0:42:59 Dude.
0:43:00 It felt so specialized.
0:43:03 We’re going to compete at like a ridiculous level of price
0:43:06 to go get pretty good talent in that space.
0:43:09 I remember 2012, which was not even early,
0:43:11 we had one iOS dev on our entire team.
0:43:14 And it was so hard to recruit talent.
0:43:15 We was faster to just retrain.
0:43:17 So we just stopped working.
0:43:19 And the iOS dev trained all of our other devs
0:43:20 to be good enough to be dangerous
0:43:22 because it was so scarce to get good.
0:43:27 And iOS wasn’t even that specialized compared to like either the fancy AI stuff
0:43:30 or VR, mixed reality, all that type of talent.
0:43:34 And so I just think that when I think about kids growing up
0:43:37 and all the, let’s say, 13 to 15 year old kids
0:43:38 or somewhere in the teenagers,
0:43:41 they have a mobile phone that is attached to them.
0:43:43 They think it’s superior than a computer or a desktop
0:43:45 because it’s with them.
0:43:47 And then we’re going to take the second computing interface
0:43:51 where we do more work or more immersive experiences.
0:43:53 And we put it around your eyes.
0:43:57 That makes way more sense to me than TVs, desktops, and even laptops.
0:44:00 And you know, that was like one of the thoughts where we started Fluid.
0:44:01 Like, we talked about this in 2020.
0:44:04 I don’t know if you remember, there’s one project.
0:44:06 You used to tell me you were like, I work in VR.
0:44:06 Correct.
0:44:09 I did that experiment where I worked in VR for an hour a day.
0:44:11 And then I ended up doing it for a few months, by the way.
0:44:13 And I was like, this is great.
0:44:15 And it had been like literally sitting with me.
0:44:18 And I think this is one of the reasons why I actually built a studio is like,
0:44:19 I want to do all these ideas.
0:44:21 I can no longer do them all.
0:44:22 I could pick a few.
0:44:24 I probably shouldn’t even go do more.
0:44:26 But like, I just want to find really hungry people
0:44:28 and like match them together.
0:44:29 That’s how I found John at Fluid.
0:44:32 It’s like, he was a PhD student.
0:44:33 He was going to go do something in like finance
0:44:35 and high frequency trading and like whatever.
0:44:38 And he also came to this idea of like, hey,
0:44:40 when I was doing my like, you know, masters, whatever,
0:44:42 I was writing this thing.
0:44:43 I just wanted to go into a focus mode.
0:44:47 Like, could I just go into a cave and like lock out all the stuff?
0:44:49 And he’s like, I had all these VR friends
0:44:50 that had done some stuff in VR.
0:44:52 So like, I tried to do it and it wasn’t good enough.
0:44:53 Right.
0:44:54 And then you got to left it at that.
0:44:55 And then we were talking about it.
0:44:56 And he talked with Uber.
0:44:58 And there’s like, dude, you just talked to Furcon.
0:45:02 I think he’s got like five pages of like random notes and ideas around this.
0:45:04 And then that’s what responded.
0:45:05 And it’s like, cool.
0:45:06 Like, we’re not going to blow ourselves out.
0:45:08 We’re not going to go raise a lot of money.
0:45:10 We’re not going to go get a giant team.
0:45:12 We’re going to get three people here.
0:45:15 We’re just going to grind and work hard and build and survive
0:45:17 for when this thing happens.
0:45:18 We’ll miss some bets like that.
0:45:22 We’ll gain ridiculous amounts of knowledge of like the industry.
0:45:23 And then we find these sleeping giants.
0:45:25 And it’s like, yeah, we’re going to double down.
0:45:26 Right.
0:45:30 Like, Uber went to this like VR conference, like the Meta Connecting.
0:45:33 And he had a t-shirt and we’re like, the funny thing would be like,
0:45:35 on your shirt, just put I invested in VR.
0:45:35 Right.
0:45:36 And so he did.
0:45:38 And it was like, wow, like you found one.
0:45:40 You know, you’re like a girl at a crypto conference.
0:45:41 This is amazing.
0:45:42 This is how we want to think about it.
0:45:43 It’s like, try to be there early.
0:45:46 Don’t get too caught up with where the technology is now.
0:45:48 Don’t get too scared of how far it is.
0:45:50 2015, 2016.
0:45:52 Remember, we heard self-driving cars are never going to happen.
0:45:53 I don’t know if you remember that.
0:45:54 Yeah, yeah.
0:45:56 Massive like push against it.
0:45:58 And there’s Waymo’s running around every day now.
0:46:02 I see more Waymo’s at night driving around than like regular people driving.
0:46:09 So here’s the deal.
0:46:12 I made most of my money from a newsletter business.
0:46:13 It was called The Hustle.
0:46:16 And it was a daily newsletter at scale to millions of subscribers.
0:46:18 And it was the greatest business on earth.
0:46:22 The problem with it was that I had close to 40 employees
0:46:25 and only three of them were actually doing any writing.
0:46:27 The other employees were growing the newsletter,
0:46:30 building out the tech for the platform and selling ads.
0:46:32 And honestly, it was a huge pain in the butt.
0:46:35 Today’s episode is brought to you by Beehive.
0:46:39 They are a platform that is built exactly for this.
0:46:41 If you want to grow your newsletter, if you want to monetize a newsletter,
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0:46:51 That’s B-E-H-I-I-V.com.
0:46:56 You’ve told me once before you go.
0:47:02 I think my superpower is that I’m usually in the first 1,000 or 10,000 people
0:47:05 to try any new technology and understand it.
0:47:07 Be able to play with it, know it, see it, all that stuff.
0:47:11 I remember we were at work and you were buying the Ethereum presale,
0:47:13 the ICO or whatever the presale.
0:47:14 You remember what you said about it?
0:47:15 Yeah, I don’t know if you remember.
0:47:17 I just remember being like, “Dude, can we do some real work?”
0:47:20 “Oh, what are you doing? Ethereum name? That name’s never going to work.”
0:47:22 I was like, “That sounds so nerdy. That’ll never be a thing.”
0:47:24 I think that was a phrase I remember.
0:47:25 I was telling you about Ethereum.
0:47:27 I was like, “Dude, I stayed up all night reading this white paper.”
0:47:29 I’m like, “You were so haunted.”
0:47:29 I was so haunted.
0:47:31 I came in and I was like, “We’re a song. We’re going to talk to him.”
0:47:34 And I tell you this, I don’t even know what I said.
0:47:35 We know what.
0:47:36 Probably put a bunch of words in here and it’s like,
0:47:38 “Dude, I don’t know what this is. We have something really to share.”
0:47:40 And you’re like, “Ethereum, that name’s stupid.”
0:47:41 Yeah, I wrote it off.
0:47:44 I chalked that up for another L for me.
0:47:46 By the way, you could have been totally right as well.
0:47:47 So no, I wasn’t.
0:47:48 I think that’s all that matters there.
0:47:50 I’m very, very off on that one.
0:47:52 But I think that’s true. That is your super power.
0:47:54 And then you said another thing today, which I hadn’t heard of here,
0:47:57 which is for emerging tech, there’s only one rule, survive.
0:48:01 And that reminds me, I just did a pot with Ryan Peterson.
0:48:02 He created Flexport.
0:48:03 He said the same principle.
0:48:09 He goes, “What I realized was I cannot control the timeline.
0:48:11 I don’t know how long something’s going to take to work.
0:48:16 So all I focus on is how do I just be default alive?
0:48:17 How do I just stay in the game?”
0:48:20 He goes, “I just have the confidence that if I’m in the game,
0:48:22 I’ll just keep trying shit until it works.
0:48:24 I just believe that about myself.
0:48:26 I will just keep trying things until I figure out everything to work.
0:48:29 The only way I can lose is if I have to get out of the game.”
0:48:31 Which is like, usually it’s like I run out of funding.
0:48:32 I can’t control my destiny.
0:48:33 I spend too much money.
0:48:35 I’m burning too much capital.
0:48:37 And so he’s like, “That’s been the name of the game for me
0:48:40 from when he was flipping scooters on eBay
0:48:43 to now run the multi-billion-dollar company called Flexport.”
0:48:44 And the whole time, he’s like,
0:48:46 “My whole thing is I can’t control the timeline.
0:48:49 So I’m going to control staying in the game.
0:48:50 Because if I stay in the game, I win.”
0:48:52 Stay in the game with great talent
0:48:54 and people that have this long-term mindset.
0:48:58 I think there’s a lot of people that can take short-term wins,
0:48:59 and they should.
0:49:00 Like, we’ve done that, right?
0:49:01 There were these short-term moments.
0:49:03 Like, “Oh, this is great for us right now.
0:49:04 But we’re going to keep doing more.”
0:49:06 And I think that’s the main thing for me.
0:49:08 Technology takes a long time.
0:49:11 When it hits, though, it happens very fast.
0:49:13 Like, that’s the part that I think people don’t realize.
0:49:15 They underestimate how long it’s going to take
0:49:17 and then they overestimate how fast it’s going to happen.
0:49:20 It’s immediately going to just happen.
0:49:22 And I think Uber was an example like that.
0:49:23 Like, we saw it.
0:49:24 It was black cars.
0:49:24 Yeah.
0:49:27 It’s like, “Oh, this is an expensive taxi that nobody’s going to use.”
0:49:30 And then now it’s like, “Dude, this place doesn’t have Uber.
0:49:31 Like, how am I going to move from here?”
0:49:32 Yeah, I can’t imagine what it feels like that.
0:49:33 You know?
0:49:35 And so I think I enjoy it.
0:49:36 It’s just one reason why.
0:49:38 It’s like a lifelong game.
0:49:39 I could just play technology forever.
0:49:41 I could learn about things.
0:49:43 I don’t have a rush to be there first.
0:49:45 I don’t have a rush to be like,
0:49:47 “I didn’t know everything and do everything
0:49:50 and raise the most money and get a bazillion people.”
0:49:52 It’s more like, “I need a few people with me
0:49:54 that are really excited about this.
0:49:56 They see it like I see it.”
0:49:57 And we’re just going to go on this mission.
0:50:00 And luckily now I have the ability to just fund that
0:50:02 and create my environment to do it.
0:50:03 That’s what this whole building is.
0:50:04 So let’s talk about this building.
0:50:11 Because you’ve basically built your dream man cave in a way.
0:50:14 I think it’s kind of like a founder dream.
0:50:16 And I want to talk about that because
0:50:19 you had a big success with App Lovin.
0:50:24 And actually kind of felt like there was multiple moments
0:50:26 where it was successful.
0:50:28 And at one point it sold for like two billion dollars.
0:50:29 Yeah.
0:50:30 And it was like, “Oh, exit.
0:50:31 Two billion.
0:50:32 Amazing.”
0:50:34 And then like Trump blocked it or it was like–
0:50:35 It didn’t go through.
0:50:36 Didn’t go through.
0:50:38 But then during that, I mean, this is a crazy story.
0:50:41 It was like we were sitting in the office
0:50:42 and this news happens like,
0:50:42 “Dude, congrats.
0:50:43 That’s amazing.
0:50:44 Holy shit.”
0:50:46 And then like nine months goes by.
0:50:48 The deal doesn’t like fully get approved
0:50:50 because it was such a big purchase
0:50:52 out of a Chinese company group or something like that.
0:50:56 And in the meantime, the business just kept crushing.
0:50:59 So Adam, who’s the CEO of that,
0:51:00 he basically went back and was like, “Cool.
0:51:02 We’ll still do the two billion,
0:51:03 but now it’s for 30 percent.”
0:51:04 Yeah.
0:51:05 I don’t know what exactly–
0:51:06 This is some version of that.
0:51:08 Yeah, there was like, I don’t know, like–
0:51:09 Because you couldn’t do majority deals.
0:51:10 That was a big block.
0:51:11 Yeah, something like that.
0:51:13 The majority deal was going to happen.
0:51:15 And so now then the company eventually, IPOs,
0:51:16 you get this nest egg, right?
0:51:18 So it’s like, okay, I could do whatever.
0:51:19 You could go retire.
0:51:22 You could go buy islands and cars
0:51:23 or do rich guy stuff.
0:51:24 Like you could do that.
0:51:28 And instead, you like chose to do something else.
0:51:29 Can you just describe basically like,
0:51:31 what’s the mindset?
0:51:33 What’s the conversation you had with yourself?
0:51:34 Yeah.
0:51:36 Now that you had more resources
0:51:38 to do whatever you wanted to do.
0:51:41 Yeah, I feel like my whole life,
0:51:46 I’ve just always wanted to tinker and build stuff.
0:51:47 Like I always described it as like,
0:51:50 I love taking stuff apart and putting it back together.
0:51:52 It’s not like, some people will say,
0:51:53 it’s like, oh, you want to learn how it works.
0:51:54 It’s not that.
0:51:55 It’s more the puzzle.
0:51:56 Like, how does somebody else put this like,
0:51:58 you know, and I used to do this with cars
0:51:59 and computers growing up.
0:52:00 Like I would overclock my computer
0:52:02 and I would make my car faster.
0:52:04 And like that was like kind of just like the mentality
0:52:05 that I had.
0:52:07 And then I was like, okay, well,
0:52:09 I’ve got to become an adult at some point in time
0:52:10 and do the thing.
0:52:11 But like, hey, I like this business thing.
0:52:12 I buy and sell stuff.
0:52:13 It’s like a way for me to hustle
0:52:15 and kind of do more of what I want to do.
0:52:17 And then I was like, let me just keep doing this.
0:52:20 And then maybe at some point I got to get a real job.
0:52:23 And kind of luckily like tech was really valuable
0:52:25 and like my skills had improved.
0:52:26 I got better at it.
0:52:30 And but a lot of that early journey was like more solo
0:52:31 than like with a bunch of people.
0:52:36 And then met the guys Adam before Apple oven,
0:52:37 like kind of like these other things.
0:52:40 And it was like, yo, we’re like eight people
0:52:43 in like Palo Alto, like building cool random apps.
0:52:46 Like the energy for me there every day
0:52:47 was like through the roof.
0:52:50 And then Monkey Inferno was like the same thing,
0:52:51 but like even more.
0:52:53 And I think I used to tell you,
0:52:54 like I want an airport hanger.
0:52:55 I just want a little bit of cool stuff in it.
0:52:58 And I just think it was like that.
0:53:01 Before I started Founders Inc. as it is,
0:53:02 because I was at Twitch and I’m like,
0:53:03 I got to get out of here.
0:53:03 Right.
0:53:05 It goes like the instant, instant thing.
0:53:07 And why by the way, I don’t know.
0:53:09 I don’t think I’m a good employee.
0:53:10 I think I’m like suited for a few roles.
0:53:13 And it’s typically like doing my own stuff without much.
0:53:15 Was there anything that just drove you crazy about it?
0:53:16 Was there anything like, you know,
0:53:18 we’re going to do a whole another pot on this basically.
0:53:21 I feel like the first week or month of like,
0:53:22 you’ll just do a bunch of stuff.
0:53:23 And then like, slow down.
0:53:25 Like, why?
0:53:26 I want to do more.
0:53:27 Like I want to do more things.
0:53:30 And this resistance feeling of like,
0:53:32 we already thought about this or we tried this.
0:53:33 Like, no, let’s just go do stuff.
0:53:35 And I never enjoyed that.
0:53:38 And I think startups and small teams just,
0:53:39 because you have so much to do.
0:53:41 That’s the kind of mentality.
0:53:46 And so I talked to probably like 75 to 100 founders
0:53:47 before starting Founders Inc.
0:53:48 And I really wanted to learn this.
0:53:49 Like I knew a bunch of people.
0:53:52 I used to interact with them even at like Bebo and Munkinferno.
0:53:55 I’d have them come by and like, just a tour talk, whatever.
0:53:57 And I really enjoyed that.
0:53:58 That was like fun.
0:54:01 I started angel investing a lot, which was like cool.
0:54:03 I thought I wanted to do that, but it wasn’t fun.
0:54:07 It was like, meet great talented people, get excited about them.
0:54:09 And then you’re like a monthly update away.
0:54:11 Like, give them a check and then that’s it.
0:54:12 And I’m like, damn, this isn’t fun.
0:54:13 First meeting is great.
0:54:14 It’s a great first date.
0:54:17 I walk away and I’m like, then there’s no relationship.
0:54:18 And you’re like, what happened to that great first date?
0:54:19 Exactly.
0:54:23 And so I was like, man, I don’t really want to do that.
0:54:25 But something like this where I could help
0:54:26 these like early entrepreneurs,
0:54:28 things that I’ve just done over and over again.
0:54:29 I didn’t have this.
0:54:31 Like, what’s the version of that?
0:54:35 And I talked to a bunch of founders and they all said something to me.
0:54:36 I was like, what do you need?
0:54:38 Like, what, what help do you need?
0:54:39 I thought they’re all going to save money and I’m going to start a fund.
0:54:41 Like that, that’s what I thought wasn’t happening.
0:54:43 And they all said something different.
0:54:47 They said something like, I need people who understand my problems.
0:54:49 And we used to do those masterminds.
0:54:54 And it was really about like, who do you go to for founder problems?
0:54:54 Yeah.
0:54:56 It’s like, what are your founder problems?
0:54:58 They’re your co-founders, your employees, or your investors.
0:54:59 So you can’t go to any of these people.
0:55:01 There might be the problem, right?
0:55:02 And so who do you go to?
0:55:04 Or even if they’re not the problem, you need to present.
0:55:06 You don’t want to worry your employees.
0:55:07 You don’t want to worry your investors.
0:55:12 You kind of have to maintain a certain aura of momentum and morale.
0:55:15 So you can’t just go be dumping problems on them or be like, I don’t know.
0:55:17 You’re supposed to know you’re the guy.
0:55:21 And we would go in that room, that little circle room with the circle table.
0:55:23 We’d be there and I don’t know what the employees were thinking.
0:55:25 They’re just like, man, these guys are talking again.
0:55:26 They’re going to come out with something different.
0:55:28 But we could talk about anything and then leave the room.
0:55:30 Be like, no, we’re still where we are.
0:55:33 And I think a co-founder can be that for you.
0:55:35 A lot of entrepreneurs starting out, they don’t have that.
0:55:38 And even if they have it, there’s other things that they’re experiencing.
0:55:41 And so when we used to put these folks together in these masterminds,
0:55:45 that feeling was awesome and it felt like we could relate.
0:55:50 And actually, I heard the same thing from a bunch of founders they used to talk to.
0:55:52 And I was like, I think it’s something more like this,
0:55:56 where I could do something and put everybody in a box.
0:55:57 And I thought it was going to be more digital.
0:56:01 I think COVID times and started on Discord or whatever.
0:56:02 Started on Discord.
0:56:06 I mean, like Farza, Ben was in these groups, just a few others.
0:56:10 It was just people I knew around me and COVID hit.
0:56:10 It was digital.
0:56:11 We were talking every week.
0:56:16 We would give ourselves these accountability kind of shipping sessions.
0:56:18 We would have an area to talk about stuff.
0:56:20 And you could see the dots connecting.
0:56:23 And then I got an opportunity to get this space.
0:56:25 And I had been looking for something.
0:56:28 And it wasn’t like, oh, San Francisco needs a place.
0:56:29 I’m from the Bay Area normally.
0:56:30 So this is the best place for me.
0:56:33 But I said, look, if it’s going to be SF, we’re going to be on the water.
0:56:35 No more school, no more places like that.
0:56:38 So we got this weird opportunity to find this space
0:56:41 and really make a bet when nobody else was.
0:56:44 I think it was late 2020 is when I approached them here.
0:56:47 And it took maybe nine months to figure it all out
0:56:49 and another three months to renovate it and stuff like that.
0:56:50 So it’s still very much good.
0:56:52 We got to call another call about breaking at least.
0:56:54 Wait, wait. He wants to sign a lease right now.
0:56:55 Oh, come on in.
0:56:56 That’s what it felt like here.
0:56:59 I mean, this place for Mason has 300 events a year.
0:57:00 They went to zero with COVID.
0:57:05 All the places, you know, art galleries or art schools, what do you do?
0:57:08 Like, you know, and there’s supposed to be like this innovation place.
0:57:10 And it’s a little bit older and we come in.
0:57:15 That’s one of your tricks is that you don’t run away when the dips happen.
0:57:19 I remember when, early on, 2013, ’14, something like that,
0:57:24 we meet, I buy Bitcoin because I don’t know, you’re into crypto.
0:57:25 Some people in the office, you know,
0:57:27 maybe I was dumb about the Ethereum idea, right?
0:57:31 Yeah, PG, Pete, Pete Dix was all, you know,
0:57:32 he’s mining Bitcoin on our servers.
0:57:33 So I buy some Bitcoin.
0:57:38 And literally like the next week, I forget, like super convinced.
0:57:39 I’m like, ah, guys, I see it.
0:57:42 I believe, here’s why I believe I’m giving you my case.
0:57:43 I bought, yeah, great.
0:57:45 Like the next week, price cuts in half.
0:57:47 It goes down to like 300 bucks or something like that.
0:57:53 And I came in, I’m like, ah, the Bitcoin, I was, you know, whatever.
0:57:54 And you go, oh, that was a fun week or two, you know.
0:57:56 Well, you were like, oh, this is great.
0:57:58 Because now everything’s half off.
0:58:00 Like you literally told me that.
0:58:03 You go, you believe, if you buy now, you can cut your buy price.
0:58:07 Basically, you can go down by 50%, you’ll cost average in at half the amount.
0:58:11 And I was like, oh, he’s right.
0:58:13 Because I was just riding a roller coaster of like, you know,
0:58:17 I was doing what a cliche person would do when things are good.
0:58:17 This is great.
0:58:20 When things are bad, maybe it’s not great.
0:58:22 Whereas you were like, dude, did anything actually change?
0:58:24 Or just the external sent to me.
0:58:26 And so I bought more.
0:58:26 So I thank you for that.
0:58:30 That was a very good, you know, decision at the time to go buy more when things go down.
0:58:33 I think you’ve done that with, with other, you know, bets,
0:58:37 whether it’s San Francisco real estate during the, you know, COVID time,
0:58:40 or it’s, you know, whether it’s crypto or VR.
0:58:44 When things go out of fashion, I feel like you don’t run away, which is important.
0:58:47 There’s a signal is like, things go out of fashion and
0:58:52 there’s another place where the people who don’t shape narratives typically like,
0:58:53 I’m technical.
0:58:55 So I live in these like GitHub projects.
0:58:58 I live where the builders are, I like engage with them.
0:59:03 If I see that somewhere where it’s like, huh, all the people talking are like against it.
0:59:07 These people, like nobody told him yet that like, it’s done.
0:59:08 Like, oh, this is dead.
0:59:09 Right.
0:59:10 Like they’re all saying it.
0:59:13 And then these guys are just shipping more code and like, hey, did anybody tell you it’s over?
0:59:14 Like, what are you talking about?
0:59:15 I don’t care.
0:59:18 And I just think that’s the perfect environment.
0:59:20 And even if you’re right one out of five times like that,
0:59:22 you’ll be right in such a big way that it works out.
0:59:23 And then by the way, for me, it’s just fun.
0:59:24 So like, this is fun.
0:59:26 Like I love building stuff.
0:59:28 I like building technology.
0:59:33 I did a lot of software, obviously, because it’s been magical to develop things and like
0:59:34 distribute it to the world.
0:59:36 We have some hardware products.
0:59:38 I don’t know if you remember Jamie, by the way.
0:59:38 Yeah.
0:59:43 Yeah, we, at one point in time when we’re, when we were working together, we had an idea for a,
0:59:45 it was cool.
0:59:46 It was like a voice control.
0:59:47 It’s kind of like Alexa.
0:59:48 Yeah.
0:59:49 We call it a Jamie.
0:59:50 I don’t know why, but like.
0:59:51 Yeah, we like Jamie.
0:59:51 I still like the name.
0:59:52 That was good.
0:59:56 And what you were saying was like, you’re like, we can instead of creating a,
0:59:58 everyone was trying to create a device.
0:59:59 Portal was trying to create a screen.
1:00:01 Amazon was trying to create a screen.
1:00:02 You’re like, that makes it expensive.
1:00:05 You’re like, everybody already has TV screens in their house.
1:00:05 Right.
1:00:06 Plug in your TV.
1:00:12 What if you just plug in like a Chromecast and now you turn your TV from just a blank screen into
1:00:14 like an Amazon, like Alexa thing.
1:00:15 Yeah.
1:00:16 That was cool.
1:00:17 We didn’t do it because it was good.
1:00:19 Like, we sort of saw like huge distraction.
1:00:21 We were like, yo, that’s going to be like a brutal battlefield.
1:00:26 When we took it to Michael and he just gave us that look, like, uh, this is different.
1:00:30 He was just like, yo, when all of the like trillion dollar companies are going to go
1:00:34 after the same prize, like, you can, but do you really want to?
1:00:37 Like, you know, it’s better to do the things they’re overlooking.
1:00:39 I just think it’s probably good advice to be fair.
1:00:42 We also were going to do a crypto exchange with crypto got hot.
1:00:44 And he was like, for a different reason.
1:00:45 He’s like, Hey, I’m already rich.
1:00:47 I don’t want to lose everything.
1:00:48 And I don’t really know what crypto is.
1:00:49 It’s 2014.
1:00:52 Like crypto might just be like super illegal.
1:00:53 And I don’t want to risk it all on that.
1:00:55 If we had done that, it might have been good.
1:00:56 So you have to be careful.
1:01:01 Like even really smart, successful people, you can’t like just take their word.
1:01:03 You got to have the independent mindedness.
1:01:03 100%.
1:01:05 And I think it’s fun to take shots.
1:01:06 Don’t get stubborn over it.
1:01:08 Like people fall in love with their ideas.
1:01:12 I think that’s it took me probably like, I don’t know, 10 years to figure that out.
1:01:16 Like you have to get like almost like, you have to like really take the hits.
1:01:17 Yeah.
1:01:20 To like really like live in that of like, yeah, there’s a lot of ideas.
1:01:22 I may try a lot of them.
1:01:24 My mission isn’t all of them.
1:01:27 I got to find the right ones where I can really spend the energy on.
1:01:28 But I was going to talk about one more.
1:01:32 So we built chatty heads, which by the way, now in the AI world, we were fucking ahead of the.
1:01:33 Yeah, we were a little early.
1:01:36 We could generate images for like, I don’t know, 5000.
1:01:36 Yeah, like golly.
1:01:37 Yeah.
1:01:38 And that’s what that’s what it feels like.
1:01:42 But I think it’s like, cool is like whatever technology you have today,
1:01:44 go try to produce a thing.
1:01:45 It might not be the right time.
1:01:46 It might be the right moment.
1:01:48 The medium might be wrong.
1:01:49 Team might be wrong.
1:01:51 Some of those you should pursue again and again.
1:01:54 And some of those are great learning exercises to build on top of.
1:01:59 And I, you know, I got a chance to meet a lot of people who are professional athletes.
1:02:04 And then one thing a lot of them talk about is like, you know, basketball might end.
1:02:07 Like my career will end at like 35.
1:02:08 It’s like, that’s, that’s my game.
1:02:08 It’s done.
1:02:10 Now what do I do?
1:02:13 And I think what we get a chance to do, whether it’s like business or, you know,
1:02:16 content or like building stuff, like, I’m going to do this for the rest of our lives.
1:02:17 Right.
1:02:18 I think that’s a fun part.
1:02:19 Buffets, like what, 90 something?
1:02:20 Yeah, yeah.
1:02:22 Still at the top of his investing game.
1:02:22 Exactly.
1:02:25 And so it’s like, well, like, what am I in the rush for?
1:02:29 Like, I, I not just here to like enjoy the journey, but I also don’t want to be like,
1:02:31 I got to solve it tomorrow.
1:02:31 Right.
1:02:33 When I was young, it was like, I got to be the millionaire by whatever.
1:02:36 It’s like, at some point it was like, I don’t know, man.
1:02:37 I just want to keep doing this.
1:02:37 Right.
1:02:41 And if I need to like, hustle my way to it or not, like it doesn’t really matter.
1:02:45 Like, you know, I took an Android engineer job at Monkey Inferno.
1:02:45 Yeah.
1:02:48 Because I was the guy, you know, I met you and I was like, I want to work with this guy.
1:02:48 Yeah.
1:02:49 I think that was my worst skill, by the way.
1:02:50 I just learned Android.
1:02:52 Yeah, you fooled me.
1:02:52 Yeah.
1:02:54 So like, I was like, I don’t know, I got to get in somehow.
1:02:56 And like, I know I’m going to do great stuff here.
1:02:59 I got to show it, but like, I’m not afraid to put it in the effort.
1:03:01 We need to put in the effort.
1:03:04 I’m also not afraid to like, not rush to the answer.
1:03:05 Right.
1:03:09 And like, you don’t want to be like casual and like, wait, you want to be kind of like
1:03:09 in the middle there.
1:03:11 You want to know when to attack and when to or not.
1:03:13 But like, I don’t know, you got to enjoy it.
1:03:14 Otherwise you’re really.
1:03:15 Neval has the best quote on this.
1:03:18 He says, impatience with action, patience with results.
1:03:18 Oh, yeah.
1:03:20 It’s the unbeatable combination.
1:03:22 If you ever go against somebody who’s going to operate like that, they will win.
1:03:22 Yeah.
1:03:27 Like that is a, you cannot lose if you’re going to be constantly impatient with doing things.
1:03:30 You’re not going to sit back and hope it all happens.
1:03:32 So you’re impatient with action, but patient with results.
1:03:35 That’s the hard part is a lot of founders are impatient with action.
1:03:39 And impatient results or non-founders are, you know, patient with both.
1:03:40 And then nothing ever happens.
1:03:42 So, you have to get that combo.
1:03:42 Yeah.
1:03:46 Speaking of founders, you worked with Adam at Apple Oven.
1:03:50 And Apple Oven has been like kind of a staggering company because, you know,
1:03:53 when I met you, it was, you know, a successful company.
1:03:58 You told me the stories about before you guys started that you’re like,
1:03:59 we were wandering around.
1:04:00 We tried a bunch of different ideas.
1:04:03 We’re playing FIFA because we didn’t have, we didn’t know what we were doing.
1:04:05 We were just come in, try to figure it out.
1:04:08 If we didn’t have it, we would brainstorm and go home the next day.
1:04:11 What is special about that guy?
1:04:15 What’s a superpower from him or a story from him that you remember that, you know,
1:04:18 I can learn from or anybody to listen to this can learn from?
1:04:18 Yeah.
1:04:21 So there was this like four-year period-ish when I was there.
1:04:24 I think three years of it was like not Apple Oven.
1:04:28 So it was like most of my intersection there is like not what it is today.
1:04:32 But I did get a chance to spend a lot of time with him and ideas.
1:04:33 What’s the cliff notes of his story?
1:04:36 So people know, because people don’t know, he’s pretty under the radar, right?
1:04:36 Yeah.
1:04:42 I mean, his backstory, I think he did some stuff in like equities or trading at some point.
1:04:47 I think he got into like ads at some point through like marketing and affiliate stuff.
1:04:48 He built a few different products.
1:04:53 Maybe he was a key member of the team and then he had like a few companies.
1:04:56 I think he had actually built up some like, you know, wealth.
1:04:58 I don’t know how much it was, but it was enough where like,
1:05:02 you’re like, okay, this person can make this bet and like fund the operations.
1:05:04 So he was kind of self-funding.
1:05:06 Self-funding is him and this guy, John.
1:05:07 John had done a lot of stuff on the internet.
1:05:09 He was more of the technical person.
1:05:10 Adam was more of the business person.
1:05:16 They were both uniquely and the skills incredible, like their personalities incredible.
1:05:19 For Adam, I think the thing that I felt the most was like,
1:05:21 I think it’s the first time in my life.
1:05:25 I was like, man, this is what A+ execution looks like.
1:05:26 Like this guy just hits it.
1:05:30 Like if we were talking about something, we made a choice within like,
1:05:34 it felt like within minutes that was like, delivered to this team.
1:05:37 And look, when you’re like an eight person team, it’s really easy to do it.
1:05:40 So we’ll decide something, go slow.
1:05:42 Maybe next week, we’ll do it later.
1:05:44 We’ll make these role changes later.
1:05:44 We’ll tell everybody later.
1:05:46 No, it was like immediate.
1:05:48 And when it was like, moving on from something that was immediate,
1:05:50 when it was a new idea we wanted to do as immediate,
1:05:52 when it was something else that was immediate,
1:05:55 it was just like, it felt like this is what execution is.
1:05:59 It’s like, you know, think, decide, act.
1:06:03 And like how fast you run through that depends on like the moment you decide,
1:06:06 the delay on act is like usually a problem.
1:06:09 I think this is where most, I’m not great at this myself,
1:06:11 but I’ve gotten a chance to see that.
1:06:14 I think it was kind of similar in a different realm when I met you.
1:06:20 I was like, I think this person is product thinking and like ability to like unpack
1:06:26 like a complex thing like product or distribution or maybe team motivation or whatever.
1:06:28 It’s like you see A+ talent and you’re like, you want to do it.
1:06:33 Um, for me, it was like 10 or 12 years, almost like a solo founder journey.
1:06:37 Like I had this e-commerce company, I had these other little things.
1:06:43 I had like a startup, I had people with me, but I never saw somebody else that I was like,
1:06:45 yo, like I want to learn these skills.
1:06:49 I bring something to the table, this A+ I could pair it with this A+ person
1:06:50 and now we’re going to be like a superpower.
1:06:51 Right.
1:06:52 I felt that with Adam.
1:06:54 It was very clear and obvious.
1:06:58 You know, like the size of company, I don’t want to say not a surprise.
1:07:02 But also it’s not a surprise that this kind of person would go do it.
1:07:03 Like, like it just is dad.
1:07:05 I think the same thing you’re talking about like Ryan at Flexport.
1:07:10 Like it feels like some people are just like, they’re built for that.
1:07:15 You still need a lot of stuff to go right and make a ton of great decisions and a ridiculous team.
1:07:20 One thing I’ve come to learn is that where I think we screwed up,
1:07:24 because we did Monkey Inferno, which was basically our little idea lab,
1:07:25 but we had a beautiful setup.
1:07:29 It’s like you got funding already done.
1:07:31 You have great team.
1:07:35 You’re in San Francisco, beautiful office, really talented team.
1:07:36 Like, you know, we’re not the PayPal mafia,
1:07:38 but like everybody’s gone on to do kind of interesting shit.
1:07:42 Everyone’s, you know, I don’t think we had the level of success
1:07:44 that we could have given the talent.
1:07:50 My take was, I think we were good execution, maybe even great execution,
1:07:53 but poor project selection, meaning we were going after these like moon shots.
1:07:57 Like create the next hit social media app, which is like, you know,
1:07:59 there’s been like seven ever.
1:08:02 There’s not that many of them ever to exist.
1:08:04 So, you know, I think we did bad with project selection.
1:08:09 It seems like one thing that Adam did aside from great execution was project selection.
1:08:12 I think you told me some story about like, they went to some conference,
1:08:13 you guys were working on one thing altogether,
1:08:17 and he came back and had that very quick, like think, decide, act loop,
1:08:20 where he’s like, we’re doing a mobile ad network.
1:08:21 We’re doing mobile games.
1:08:23 I don’t know the full story, but like it seemed like just,
1:08:29 that one choice at that time is the make or break, you know, like huge difference.
1:08:31 And, you know, like, I think we had many of those moments.
1:08:33 I wouldn’t trade it, by the way.
1:08:35 I think our learnings, I still leverage them.
1:08:39 A lot of the things that we talked about, how we ran the teams, like,
1:08:41 they still radiate and resonate with me.
1:08:45 And so like immense wealth and knowledge and like,
1:08:48 like literally like experience of the thing.
1:08:49 Right.
1:08:50 Beyond like, you’re talking about when we worked.
1:08:51 Yeah, exactly.
1:08:55 But there were a few moments where project selection could have been massive for us.
1:08:56 Yeah.
1:08:59 That outcome, you know, like they, you know,
1:09:01 and we can talk about uploading a little bit on that journey,
1:09:02 but like, we did Blab.
1:09:07 It was a live streaming product, Google Hangouts, public live stream.
1:09:07 Yeah.
1:09:08 Like if you saw a clubhouse get really popular,
1:09:11 we had built basically a clubhouse before clubhouse.
1:09:14 And it got kind of like what Twitch right now,
1:09:17 like there’s a big section of this, like just chatting, hanging out category.
1:09:17 Right.
1:09:18 We built an app like that.
1:09:21 I got to four million users, but it didn’t become the next big thing.
1:09:22 I don’t know if you remember this conversation,
1:09:25 but we had this one time when we were deciding what to do next.
1:09:28 Are we doing mobile version of this?
1:09:30 Because we see other things happening.
1:09:32 Or do we do the P2B version?
1:09:32 Yeah.
1:09:33 And the zoom didn’t exist.
1:09:35 And that, I think that was.
1:09:42 And we were like, B2B, I remember it was like, it was like so short of a conversation, which was so silly.
1:09:44 We were just like, B2B, that’s not cool.
1:09:46 It wasn’t cool and it wasn’t clear.
1:09:48 Because if you think about it, it was like 2015.
1:09:52 There wasn’t a billion like B2B companies crushing it.
1:09:52 Yeah.
1:09:54 But like every year since then it was like seven or nine.
1:09:58 Like, because I think at that time it was only a few had really reached,
1:10:01 like it was like, I don’t know, box.net and Dropbox.
1:10:05 And it wasn’t, it definitely wasn’t as obvious at the same time.
1:10:08 It wasn’t as hidden as we kind of made it seem.
1:10:09 We totally brushed it off.
1:10:13 Like I remember Citrix was like a multi-billion dollar product.
1:10:18 And Citrix was online was the way that people did these webinars and web conferencing at the time.
1:10:20 And it was so bad.
1:10:27 And their users like, we were trying to make this cool social app and SAP and Oracle were using our tool.
1:10:29 Just because it was better, even though it was like not meant for that.
1:10:31 Why is your color like weird and purple?
1:10:33 Why do you got this weird star thing?
1:10:37 And instead of looking at those clues and being like, huh, maybe we could do that.
1:10:39 We, we missed that project selection choice.
1:10:44 I remember that day because that was a, that was a probably a multi-hundred million dollar fork in the road moment.
1:10:46 You know, maybe you still had to execute, but for sure.
1:10:47 I mean, we could execute, right?
1:10:49 But it is, did we have the right selection?
1:10:53 And could we get the right insight in our mind to in SAP?
1:10:56 It was also when we decided to end Blab.
1:10:58 I don’t know if you remember, you went to this barbecue.
1:10:59 I forgot who you met James career.
1:11:03 And they were telling us, you know, you’re talking about like, hey, this content network problem.
1:11:07 Because it was like the moment that entered our mind is like, oh, shit, we’re fucked.
1:11:08 Like that’s what it felt like.
1:11:10 Like we don’t have the ability to intersect these.
1:11:11 And we kept looking at Twitch.
1:11:12 Like why?
1:11:13 Okay.
1:11:16 So we know we don’t because people come on for an hour to do a show.
1:11:20 The Epic content is not on long enough for people to show up and intersect with it.
1:11:21 How come Twitch wins?
1:11:25 And then it turned out that, oh, people play games for eight to 10 hours.
1:11:25 Yeah.
1:11:26 So it didn’t matter when you showed up.
1:11:27 Correct.
1:11:28 And then the context reset.
1:11:32 So it was like, it was like, you know, the feeling a lot of monkey inferno to me and
1:11:37 like the things we built was like, it’s not slow down to speed up, but like look for the clues.
1:11:38 Don’t be afraid of that.
1:11:42 And again, the eager, you know, the ego or the stubbornness of like,
1:11:44 we want to build a giant social app.
1:11:48 Like, I want to go somewhere around the world where somebody’s using my consumer product.
1:11:51 Like that was a stubbornness that we felt as the driver.
1:11:51 Yeah.
1:11:54 And it’s like, if we had just kind of unlocked it a little bit, there was these project selection
1:11:55 moments.
1:11:56 And so there was a lot of that.
1:12:01 I still fuel that sometimes, but I don’t know, maybe it’s because I’m older and I’m like less
1:12:05 willing to like be nimble in that way, but I didn’t want to talk about one more hardware
1:12:06 robotics thing for a few minutes.
1:12:10 And so I think this is another like resurgence moment happening.
1:12:14 Like for a long time, hardware has been too hard, too expensive.
1:12:16 Software gets funded.
1:12:17 That’s the same thing about Yamada, right?
1:12:18 Hardware is hard.
1:12:19 Hardware is hard.
1:12:20 Software is easy.
1:12:21 Software scales.
1:12:22 It’s eaten the world.
1:12:24 Like these were all the mentalities.
1:12:25 I think it’s flipping.
1:12:26 And I think it’s a few things.
1:12:28 That have all kind of showed up together.
1:12:34 So there’s two types of hardware that I think are now like there and like ripe to build
1:12:35 same recipe.
1:12:36 Can small teams do it?
1:12:38 Can you do it without a lot of funding?
1:12:42 And then can your output be really big and like impact a lot of people?
1:12:44 And so I think there’s one around consumer products.
1:12:50 So like the combination of Raspberry Pi and Cloud AI has completely changed what it takes
1:12:51 to build something, right?
1:12:55 So there’s a company in our studio, Magical Toys are building an AI teddy bear.
1:12:58 We’ll do a little demo of it after we’ll kind of get to that.
1:12:59 And you know, I think what that.
1:13:00 And how old is that guy who’s been there?
1:13:01 He’s like young, right?
1:13:04 I think for teams like 24 or 25.
1:13:06 It’s not like he has huge funding or a huge team.
1:13:07 But he showed up here.
1:13:09 I don’t know how I got here, to be honest.
1:13:12 I think like many people here, they meet somebody, they attract.
1:13:13 And we’ll just show up by the way.
1:13:14 And it’s awesome.
1:13:16 Like we’ve created that environment where it can make sense.
1:13:19 He had done some small projects in college.
1:13:22 Like he built this thing called Desk Buddy.
1:13:26 It was a little like e-ink screen with like two eyes that just blinked.
1:13:27 And that was really it.
1:13:27 You couldn’t talk to me.
1:13:28 Couldn’t do anything.
1:13:29 It was just a little desk buddy.
1:13:29 So you’re not alone.
1:13:30 Is that the idea?
1:13:31 Yeah, I don’t know who it was.
1:13:32 But I remember seeing it and I’m like, that’s cool.
1:13:34 Like I want one on my desk.
1:13:34 Like it’s just fun.
1:13:37 And they’ve raised from a bunch of ideas.
1:13:40 And you know, the combination of like, hey, we got Raspberry Pi.
1:13:42 We could do these little things.
1:13:44 We could use 3D printers to build enclosures.
1:13:48 And then now we’ve got this Cloud AI thing that like can be really powerful.
1:13:52 And they ended up coming with this idea, which was like, hey, we’re going to build a
1:13:57 toy. And first they literally made Ted, the, you know, stuffed animal Ted.
1:13:58 And they talked like it.
1:13:59 And I was like, oh, this is wild.
1:14:03 Like, you know, and AI could do this, but everyone’s trying to make coding faster.
1:14:06 Or there’s, you know, developer solving developer problems.
1:14:10 And I love when somebody takes that and goes, let me go to this other place where nobody’s
1:14:11 thinking about.
1:14:11 Right.
1:14:14 And he spent probably the last nine months sitting, refining.
1:14:16 I think we sent you one of the first units.
1:14:17 It probably broke.
1:14:17 Yeah.
1:14:17 First thing.
1:14:21 First he gave me a teddy bear with the back, like the whole computer was just hanging out the
1:14:23 back, like a, like a half done surgery.
1:14:25 But it was interesting.
1:14:26 I gave it to my kids.
1:14:30 You know, I think they were probably like two years old, three years old at the time.
1:14:35 And every other toy we have in our living room is pre-programmed.
1:14:37 So it’s like, this is a toy.
1:14:37 Push this button.
1:14:39 It’ll say this thing.
1:14:41 That’s all it can do with this toy.
1:14:44 It was like, ignore the thing hanging out the back.
1:14:46 It was like, um, hey, we love Paw Patrol.
1:14:49 Can you ask us some Paw Patrol trivia?
1:14:51 Like, certainly I can tell you Paw Patrol.
1:14:53 Who is the red dog in Paw Patrol?
1:14:55 I was like, Marshall, correct.
1:14:57 And I was like, can you keep track of our points?
1:15:00 He goes, okay, two points.
1:15:04 And I was like, well, and my kids were blown away because now you have an infinite toy.
1:15:06 Whereas every toy is finite.
1:15:08 It can only do the things it could do out of the box.
1:15:13 Now suddenly you have a toy that’s basically chat GBT shoved into a stuffed animal.
1:15:14 And you’re like, wow, now, now that could do anything.
1:15:16 I could say, sing me a song.
1:15:18 I could say, tell me a bedtime story.
1:15:20 I could say, I can make it do many, many things now.
1:15:25 And I think what was cool is Fatine and this little like lab that we built.
1:15:29 And the lab has like some 3D printers, some electronics area.
1:15:32 Honestly, we started with like an empty room and people would come by.
1:15:33 They’re like, what’s this room for?
1:15:36 I’m like, oh, it’s going to be a machine shop electronics lab one day.
1:15:36 Like, oh, can I use it?
1:15:38 I’m like, yeah, but we have nothing here.
1:15:38 What do you need?
1:15:39 I need tables.
1:15:40 Great, we’ll bring tables.
1:15:42 So you need like a little thing.
1:15:42 Okay, we’ll add that.
1:15:43 You need 3D printers.
1:15:44 We’ll add that.
1:15:48 And I’ve seen now like tens of people come through.
1:15:52 Oh, you know, one person sit there, spend some time, tinker.
1:15:53 And Fatine did that.
1:15:55 Like he built one.
1:15:55 He showed us.
1:15:56 He built another.
1:15:58 He tried different variants, different versions.
1:16:00 You know, built, you know, right.
1:16:03 New cases when he printed, buying Raspberry Pi, his new software.
1:16:10 And like, I think he shipped like 60 to 70 units across four to six months,
1:16:14 which in software world, this feels like, wow, ancient, like 60 users.
1:16:18 In hardware, this might have cost like half a million to a million dollars.
1:16:20 I think we did that for like 50 to 100 grand.
1:16:20 Right.
1:16:26 So like that difference, one person, 3D printers, Raspberry Pi’s, some AI,
1:16:29 and you could just sit there and deliver units and try it with people.
1:16:32 When we showed Ubera first, by the way, internally.
1:16:35 He was like, no, I don’t, I don’t think kids are going to do this.
1:16:35 It’s weird.
1:16:38 His daughter used it and it changed his mind.
1:16:40 Like, like she changed his mind.
1:16:40 Right.
1:16:42 Because he saw what it could do.
1:16:45 But like, and how do you get that opportunity to prototype?
1:16:45 Cheat.
1:16:45 Right.
1:16:46 So hardware being hard.
1:16:49 And it’s like, maybe hardware is not as hard as it used to be.
1:16:54 That, like Sam calls these inflections where, you know, something changes.
1:16:58 Like there’s famously an inflection where when Obamacare came out,
1:17:03 then Oscar health built a thing that was just to do Obamacare and like, you know,
1:17:07 how it became like a billion dollar company is like, so what are the inflections?
1:17:11 So, oh, phones now have GPS in them.
1:17:12 Now you can build Uber.
1:17:16 You couldn’t build Uber before because the driver and the writer need to define each other.
1:17:18 How were they going to do that if you didn’t have phones with GPS on them?
1:17:20 Phones have cameras.
1:17:21 Now you can have Instagram, right?
1:17:24 So it’s like the technology inflection can happen.
1:17:25 It’s one type of inflection.
1:17:31 And you’re basically saying because of Raspberry Pi plus AI plus 3D printing.
1:17:34 Consumer hardware is very consumer hardware is now possible.
1:17:39 Now, like now more than ever, two people can actually mess around and tinker until they get
1:17:40 something right.
1:17:42 Kind of wasn’t feasible five, 10 years ago.
1:17:43 Correct.
1:17:46 And when we built Jamie, I used a Raspberry Pi at that time, which was the first version.
1:17:51 Raspberry Pi was thought of as this hobbyist market of tinkers that are going to buy a few of
1:17:52 them.
1:17:55 They’ve sold like 60 million units or something ridiculous like that.
1:17:57 Like 35 bucks a pop, 60 million.
1:18:00 There’s like a few billion dollars of Raspberry Pi out there.
1:18:06 And I think what it did is you used to have to make like custom boards, custom software.
1:18:10 And you know, for a technical person like me, I don’t want to go that far.
1:18:13 Like I have certain skills that I could do really well.
1:18:16 And typically it’s like read a few guides on the internet and like stitch stuff together.
1:18:18 It felt too far for even like somebody like me.
1:18:20 It felt like bad.
1:18:21 It’s like really serious engineering.
1:18:23 I need 10 people, 10 millions of dollars.
1:18:27 I convinced somebody there’s a big market and now like build up this company, which
1:18:32 probably will fail because I raised too much, too much pressure, too much demand on return,
1:18:33 et cetera.
1:18:35 And to be the Raspberry Pi was one of the unlocks.
1:18:38 And there’s the Nvidia Jetson now, which has like GPUs on device.
1:18:40 And there’s so much more there.
1:18:43 But so what are, what are other things besides magical toys that you saw somebody built?
1:18:46 Interesting things you’re seeing built in the hardware robotics side.
1:18:46 Yeah.
1:18:50 So we have AJ who’s building the, you know, Neurostity.
1:18:54 He built that first version, which I think I’ve showed you before with the brain computer interface.
1:18:58 Now he has a second version that’s really tiny.
1:18:59 It’s like the size of AirPods.
1:19:01 You could put it right here, special purpose.
1:19:07 So really like the ability to prototype, develop the thing, get like hundreds or thousands of
1:19:13 units out there, improve the design and doing that without a giant team allows them to kind
1:19:14 of continue.
1:19:17 We’ve seen like a variety of things kind of come out on that front.
1:19:22 I think the second area that’s happening is, you know, the consumer hardware.
1:19:28 And then there’s like this robotics drones and kind of this other world where we have
1:19:35 so much physical equipment in the world forklifts and lawnmowers and cars and like in all these
1:19:41 things that we do that requires either a person, like, you know, with drones, we invest in this
1:19:46 company, lucid drones, which, you know, they built a power washing drone, could go up in
1:19:50 buildings, could power wash, you know, the glass instead of people hanging from the side.
1:19:53 There’s another company that I mean.
1:19:54 And is that working?
1:19:55 Like do people, is it like?
1:19:56 Yeah, working very well.
1:20:02 And, you know, like what’s interesting is there’s like a unique business model to find here as
1:20:07 well. And I think that’s why I love like being in the weeds a little bit and like seeing it is like,
1:20:10 most people think you’re going to build this product and then you’re going to take the people
1:20:14 that like manually wash a building and you’re going to like get rid of them.
1:20:18 What actually happens is there’s like a team that’s like a little like small business somewhere.
1:20:20 They have like five people at their company.
1:20:21 Dave’s power washing.
1:20:21 Dave power washing.
1:20:24 Window is so clear, you won’t even know it’s there.
1:20:24 Amazing, right?
1:20:26 Dave’s got a great tagline as well.
1:20:31 And, you know, people end up finding that if you just sell to those small businesses,
1:20:34 you give them more tools, they can serve more buildings, do it more efficiently.
1:20:37 That distribution is built in.
1:20:42 They may be in the long run, this starts changing, but like now there are a ton of these opportunities.
1:20:47 I’ve seen one for farms and like, you know, mowing the weeds around certain fruits
1:20:49 or kind of like inspecting them.
1:20:53 You just send people between these things to go like do it.
1:20:57 And now there’s like a little like robot and instead of the one person doing it for two weeks
1:21:03 or two people, the one person is there monitoring it at the facility in air conditioning and like
1:21:04 watching on the iPad, watching on the iPad.
1:21:07 I know it might get stuck early on or might detect something.
1:21:09 Now they got to go fix that thing.
1:21:13 The disefficiency I think is like massive and we’re seeing it at many places.
1:21:16 So the same thing I saw these two guys building here in San Francisco.
1:21:22 They’re like random warehouse in the back of some other store, like two dudes like literally grinding
1:21:24 bootstrapping like, like just going there.
1:21:25 I’m like, I like these guys.
1:21:27 They took a forklift.
1:21:28 They automated it.
1:21:32 They took self-driving car tech that probably took billions of dollars to develop.
1:21:35 And then all of that kind of flow to like open source.
1:21:39 And typically open source sometimes is behind than the cutting edge.
1:21:44 But in 10 years that normalizes, we see this elsewhere like AI models like Lama.
1:21:50 But like really they took cameras and some LiDAR stuff and they strapped a little computer
1:21:52 to a forklift and they could move it around.
1:21:53 You could talk to it.
1:21:55 You could kind of get it to do things.
1:21:57 And I think there’s a massive resurgence.
1:21:59 So forklift physical thing.
1:22:06 You took a little Raspberry Pi internet, some cameras, some technologies like we were doing
1:22:09 computer vision technology to score like Fortnite games.
1:22:12 They’re using the same kind of technology to look at.
1:22:13 Oh, this is a box.
1:22:15 This is the barcode that I picked up.
1:22:15 Right.
1:22:17 I can now use and figure out what’s this thing.
1:22:21 It could go walk around the warehouse and be like, oh, that pallets in the wrong spot.
1:22:21 How?
1:22:24 It just scanned the barcode and detected, oh, there’s this pallet here.
1:22:25 It’s supposed to be over there.
1:22:27 Go pick it up, move it over there.
1:22:29 Like these problems exist in warehouses.
1:22:32 Like, I mean, you know, right, I think you’ve dealt with some of those and you’ve run a warehouse.
1:22:36 And so to me, it’s like, what are the machines?
1:22:40 Like what are the traditional machines we’ve built probably for the last 100 years?
1:22:42 So you’re going to slap a little computer on it.
1:22:43 And now it’s a superpower.
1:22:48 And I think this is bringing down the cost of like this robotic hardware.
1:22:53 Like, building a robotic arm used to be like, yo, I got to be like Tony Stark and like Ironman.
1:22:55 I’ve seen two people do it in a machine shop.
1:22:57 I, there’s a guy here.
1:22:58 I don’t even know his company.
1:23:01 He just showed, he just had a 3D printed hand on his desk.
1:23:02 And I’m like, that was this.
1:23:07 It’s like, oh yeah, like I, I, I created the ability to develop a full hand with all the
1:23:10 fingers and everything in just this 3D printer.
1:23:13 There’s a bamboo left printer, which honestly, 3D printer was great.
1:23:17 And then bamboo labs took it to a whole another level, like a little bit of AI to help self
1:23:19 leveling and make prints great.
1:23:21 And like everybody loves it.
1:23:26 And he just built his hand pretty high quality, took a little fishing net on the inside of
1:23:26 the hand.
1:23:30 So like in each finger, he could like pull every finger and like do some stuff.
1:23:35 It’s like one dude, like a few months hackathon and like, I don’t know what he’s going to produce
1:23:35 from that.
1:23:39 But I just think you could do these things now in like weeks and months when they took
1:23:41 years and like a lot of money.
1:23:46 I think there’s a huge opportunity here still going to take time to like marinate and develop.
1:23:51 But I look at it as one of those things where like, if I was a mechanical engineer, if I
1:23:55 liked hardware, and I’ve been told that it’s just AI and software and like your stuff isn’t
1:23:56 that interesting.
1:23:58 It’s like, no, no, this is very interesting right now.
1:24:00 Like you need to find a place to do it.
1:24:03 And you know, like, I’ll even say like, I think we’re going even further for us.
1:24:05 Like we have this base we built here.
1:24:06 We call it the founder lab.
1:24:09 Like this is where a lot of people come to tinker on stuff.
1:24:09 We have founders here.
1:24:10 We have builders.
1:24:11 We have creators here.
1:24:13 We have all kinds of people doing stuff.
1:24:14 But it’s a little machine job.
1:24:17 And that kind of pushed us to be like, wait, there’s more.
1:24:18 We’re seeing more.
1:24:21 We’re talking to more people thinking about this.
1:24:25 And so I ended up getting this kind of industrial space and call it the garage.
1:24:27 It’s 20,000 square feet of industrial space.
1:24:28 I’ll show you in a little bit.
1:24:31 But it looks like San Francisco real estate is not the best.
1:24:33 I think this is a time to make these bets.
1:24:40 But I’ve talked to 25 to 50 founders in the last 12 months that need a hardware space
1:24:46 like this to tinker, to have smart people around them, to have the machines around them,
1:24:50 to just being able to develop it probably for less than a hundred grand.
1:24:54 They can go and proof of concept and prototype the thing.
1:24:58 And look, we’re seeing the hype cycle of like humanoid robots.
1:24:58 Right.
1:25:00 That’s that like hype above.
1:25:03 I’m more excited about all these startups that are going to form.
1:25:05 They’re going to build this expertise.
1:25:07 They’re going to be a hundred million dollar teams,
1:25:08 whether it’s their product or their knowledge.
1:25:09 Right.
1:25:10 That’s happening now.
1:25:13 And two people are doing it like every single day.
1:25:14 Like they’re spawning these things.
1:25:17 And so consumer hardware is one area.
1:25:21 But I think robotics and what typically was known as like deep tech,
1:25:27 like I need like PhDs and like stacks of them and 50 million dollars or hundred million dollars.
1:25:28 That’s the second one.
1:25:31 And I think it’s like, there’s a few people seeing it.
1:25:33 Maybe there are sectors like defense where it’s like exciting.
1:25:34 But like, I don’t know.
1:25:38 I think we’re going to see machines everywhere and every kind of version of it.
1:25:43 And I think I’ve seen people develop like cooking robots, laundry machine things,
1:25:48 folding drones to inspect stuff, drones to map interior spaces.
1:25:53 Like Matterport is a giant company and a human goes and puts a tripod everywhere.
1:25:57 And like there’s a little drone that’s going to fly through the whole house and like
1:25:58 map it for you.
1:25:59 And that expands that.
1:26:04 And I just see one or two person teams able to do this faster than I’ve ever seen it.
1:26:05 I feel more capable.
1:26:08 Maybe I just really want to get into hardware again myself.
1:26:09 And I think that’s the point though.
1:26:11 It’s a lot of people would want to mess with this.
1:26:16 And if something goes from not tinkerable to tinkerable, suddenly it’s now the like,
1:26:19 it’s kind of like before you’re competing 1v1.
1:26:21 Now it’s one versus the field.
1:26:25 The field, of course, any individual thing in the field might suck.
1:26:27 But the field overall is super powerful.
1:26:32 And now you’re saying the field is open for hardware tinkers, which it wasn’t open before.
1:26:33 That’s a big deal.
1:26:35 Yeah, we do these like residencies here.
1:26:38 We’ll bring people here for a month or six weeks.
1:26:40 We just tell them like, here’s a theme.
1:26:41 Here’s a space to go do things.
1:26:43 When the Vision Pro came out, we did it.
1:26:45 We had about 40 Vision Pro devs.
1:26:49 We probably had the largest concentration of Vision Pro devs out of Apple anywhere.
1:26:52 And the knowledge of that look, look, it didn’t produce some ridiculous outcome.
1:26:55 We actually did invest in one or two teams from that.
1:26:58 I think we just got a chance to see that technology deeply.
1:26:59 We did this AI hardware one.
1:27:04 I remember meeting this this kid and I don’t know where he was in the world.
1:27:06 And he shows me this robot.
1:27:08 He built a humanoid.
1:27:10 He built in his bedroom.
1:27:11 And it’s like half.
1:27:13 He only built the bottom of the legs.
1:27:15 So I stopped where the waist was.
1:27:18 And it was totally hand-constructed.
1:27:19 And I’m like, yeah, this is wild.
1:27:26 But the fact that you could boot like this in your bedroom and it could take steps, it’s crazy to me.
1:27:28 I met these other guys from here.
1:27:32 And the same trend in Raspberry Pi, they took that trend.
1:27:33 And I mean, I love some of these.
1:27:38 I just, you know, I love it because I could jump on the video and they were up in Seattle or something.
1:27:39 And it’s like their kitchen.
1:27:41 And I’m like, is that a 3D printer in your sink?
1:27:44 And it’s just like their kitchen is like all machines.
1:27:48 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.
1:27:52 That’s what I want is like people who will just turn their bedroom into this.
1:27:54 It’s like, no, no, you come do it here.
1:27:56 We’ll give you a little bit better facilities.
1:27:57 We’ll give you space.
1:27:59 You get a better place to sleep.
1:28:00 And they took this like Raspberry Pi trend.
1:28:03 And they’re like, oh, people will start with Raspberry Pi.
1:28:04 And then they build a custom board.
1:28:06 Oh, we’re building a modular Raspberry Pi thing.
1:28:06 Right.
1:28:08 We did that computer long next intermediate step.
1:28:09 Oh, you want a speaker?
1:28:11 Well, you could pick whatever speaker you want.
1:28:12 Just put that in.
1:28:14 Oh, you want to produce 2000 units now?
1:28:16 We have the ability to scale it for you.
1:28:20 So they took the hobbyist world and the behavior that’s happening, driving it.
1:28:22 And they started this literally in their kitchen.
1:28:25 And like, I just think that, man, that’s capable now.
1:28:29 And that’s the trend that I can’t, I can’t like unsee it sometimes.
1:28:30 Right.
1:28:33 In hardware, both in consumer and more deep tech hardware,
1:28:38 like drones, platform is massive, right to be able to do things.
1:28:40 So much opportunity to utilize that.
1:28:44 I don’t know how long it’s going to take for this to become mass and mainstream.
1:28:46 But I just keep seeing that trend right now.
1:28:48 And I think for us, that’s the bet you’re making.
1:28:48 That’s the bet we make.
1:28:50 And so I was joking with the guys here.
1:28:52 It’s like, we want to bet on negative one to zero.
1:28:55 Like Peter, they’ll talk to about these zero to one companies.
1:28:56 It’s like, we still want to step even before that.
1:28:58 Like you’re at negative one.
1:28:59 You’re wandering the forest.
1:29:04 You need to place a tinker and like, come and get the ideas to form.
1:29:05 This is what we will, this is what we wanted to write.
1:29:05 Right.
1:29:06 All right.
1:29:07 Love it.
1:29:09 Forgot this is amazing.
1:29:10 Good catching up as always.
1:29:12 Let’s go check out some of these spaces.
1:29:12 Sweet.
1:29:12 Let’s do it.
1:29:13 Thanks so much.
1:29:29 Hey, Sean here.
1:29:31 I want to tell you a story about Winston Churchill.
1:29:36 So Churchill once said, first, we shape our buildings and thereafter, they shape us.
1:29:39 And I think this is true not just for the buildings we see in cities,
1:29:42 but also for the building blocks you choose in your company.
1:29:46 For any company that I start, I use Mercury for all of my banking needs.
1:29:46 Why?
1:29:49 Well, it was built by a YC founder and you could tell this is built by a founder who
1:29:51 understands the needs of other founders.
1:29:54 Second thing is this modern, it’s clean, easy to use.
1:29:55 The design is really nice.
1:30:00 You never have to drive somewhere, park, put coins in the meter, get out just to do one simple task.
1:30:02 You could do everything in just a couple of clicks.
1:30:06 They got bill pay, checking account, savings account, wire transfers, everything you need.
1:30:06 They got it.
1:30:09 I use it for not one, but actually six of my companies right now
1:30:11 and actually even have a personal account with them.
1:30:12 It’s kind of amazing.
1:30:16 So if you’re ready to operate in the future, head over to mercury.com, apply in minutes.
1:30:20 Disclaimer, Mercury is a financial technology company out of bank banking services provided
1:30:24 by Choice Financial Group and Evolve Bank & Trust members, FDIC.
1:30:26 Thank you to Winston Churchill for that little ad segment.
1:30:29 All right, back to this episode.