Dan Shipper: The First MultiModal Media Company
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- Code is now content. Someone who's a genius at one thing, like Einstein, I still wouldn't want him to run a, be a GM for a product at every, like, he would suck. You know, no shade to Einstein. The models are already smarter. They're being made dumber on purpose. It's the first model that made me laugh. I could have it sort of swipe on hinge for me and it would do a good job. - Oh wow.

Everyone's saying, well, you know, prompting is not a real programming language. That's just what people who have been coding for a long time say. And they're right. This happens with every meeting. That's not real podcasting or like that's not real music. That's not a real radio show.

Hey, everyone, and welcome to Generative Now. I am Michael Mignano. I am a partner at Lightspeed. And this week on the show, I spoke to Dan Schipper, co-founder and CEO of Every, a multimodal media company, which is publishing writing, articles, videos, podcasts, and software.

We spent a bunch of time in this episode talking about the future of software and whether or not software is becoming media. We also talked about Dan's use of all the different AI models and what he sees will be the strengths for each. This was an awesome conversation. I hope you enjoy it. Hey, Dan. Hello. Good.

Good to see you. Good to see you too. Thanks for doing this. Excited to be here. The image of you that I have in my mind and how you relate to AI, I don't know if this is going to... I'm curious to gauge your reaction to this. You're like the most interesting man in AI. You're like, you're writing with it. You have this writing company. You have a podcast where you talk about it. Now you're building products. You're doing all the things.

that one would want to do with it. I guess the only thing you're not doing is you're not training a foundation model. I'm not. Not yet. Maybe that's next. Yeah, and I'd be curious to know like what that foundation model is. Is it just like a pure language model? Is it, anyway. That's like, that's the image of you I have in my mind as it relates to AI. Accurate, inaccurate. Thank you, that's very kind. I definitely, I love it because I think as a personality, I'm very curious and I have a very generalist skillset.

And I think it lets me like go into all these different areas that I would like. I've always dabbled in like I, you know, I code and I like to write and I like, you know, I play guitar and I play piano or whatever. But each of those skills I could teach.

some of them to myself. Like I taught myself coding, for example. But to really like make a lot of progress, like you often like you need to go to school or you need to get a teacher or whatever, or you need to be able to talk to experts. And I think AI sort of changes things where like I actually don't need that. Like I it would be helpful also to talk to people. But like I can be curious. I can make a ton of progress just like coding with, you know, cursor or GPT-4, 5 or whatever.

And I love that. It just makes me so excited every day because I get to explore all these different areas that I'm really curious about. Just maybe focusing on coding for a second. I understand you taught yourself to code, but were you coding...

this regularly prior to AI? - I mean, there have been periods in my life for sure. - Yeah, you founded a company. - Yeah, software company. I started coding when I was in fifth grade. - Okay. - I read a Bill Gates biography and I wanted to start a Microsoft competitor. - Nice. - And I was gonna call it Megasoft. - That would be really cool.

- Classic David and Goliath story. - Yeah, obviously. It didn't work out. Microsoft's still around. - Yeah. Megasoft, I don't think, is still around. - No, it's not around anymore. It never made it off the notebook page, but I still have the notebook, which is kind of fun. I kept doing it 'cause I've always been into business and programming was a way for me to start businesses where I didn't need any money or any other people. I could just make little things. So I made a lot of apps in high school. I started making Blackberry apps. - Oh, wow. - Before the iPhone came out, yeah.

And then I did iPhone apps. And then in college, I started my first actual company called Firefly, which was a software company. I spent a lot of time coding. What was Firefly? It's been a while. I think actually the product is still around, which is kind of fun, but it's not called Firefly anymore. It was a co-browsing product. So co-browsing is like screen sharing, but instead of sharing a desktop, you share what's on a webpage.

Oh, right. Yeah. We applied it to customer service and it has no downloads or installations as a JavaScript snippet. So you, you know, a company installs it on their website, like a bank or, you know, telecom or whatever. And when a customer is having a problem with the website and they call the agent, we let the agent see what they're doing on the website, helping through the site in real time, all that kind of stuff. And this is in 2012, we started it. Just you? Me and two friends from college. Okay. At this point, the technology is like still...

Probably kind of hard to make but not really that hard to make especially with AI But like back then and had to work back to ie8 in order to work with enterprises, which is like this is like a huge nightmare It was pretty wet. Okay, pretty well bar TC. There are these things in browsers called mutation observers that let that let you see what what Dom has changed on a web page and so good browsers like Chrome

at the time had mutation observers, so it was a little bit easier to do it. Bad browsers like IE8 did not, so we had to do all these weird hacks. We overrode every single JavaScript function on the page in IE8 in order to see what people were doing to the page to represent the changes to the agent. I'm on a big tangent, but basically, for every... I really did very little coding. I

I'd always like did like little projects. So like we have this file cleaner app as part of the bundle called Sparkle that organizes your files. And that has it does it with AI. And I like I built the original version of that pre-AI like at the very beginning of every. But like mostly I wasn't coding. And I think the difference is with Sparkle.

A, I know, hey, maybe it's like a little bit more of my job to like be experimenting with stuff and building stuff, but B, it's much more achievable to code with divided attention. So I can be like doing something else and like type a little thing saying like, go do this or whatever, which is a lot more like managing people, you know? Yeah.

Um, where I don't need like, you know, Paul Graham has the like famous maker manager schedule thing. And I don't think that that's true anymore. Um, I think you can be a maker on a manager schedule, um, because you don't need like long blocks of focus time as often. It's,

Good to have that too, but you can still make a lot of progress without it. This totally resonates with me. So I don't code as much anymore, but I do design. I do like a bunch of work in Figma or whatever. And same thing, like I'll be in Figma like focusing, right? Yeah. And then I'll just go over to Claude.

and throw out an idea for like an animation or something and it just goes off takes a few minutes then it comes back and it was like oh wow that was exactly what i was picturing yeah yeah i can just delegate these random tasks without focusing intently on them so that totally resonates with me okay so what was it called sparkle sparkle so that's one of the first products that came out of every every is super interesting to me um it's it's

It wasn't a product company as far as I understood. I mean, I remember when you and Nathan founded it. Yeah. Probably what? Five years ago. Oh, wow. I got my I got my exactly right. It's like a writing collective. Yeah. Like I almost pictured it as a publication on Medium or something at the time. Tell us tell us a little bit about that, because that's very that's very different than building software company. Yeah, yeah, yeah.

There's been a very circuitous route to what we are today. The way I describe Everytoday is we're a multimodal media company. We publish writing, podcasts, videos, and software. And we're sort of in this world where what it means to be a writer and what it means to be a builder, the lines are starting to blur because you can write English and turn that into software. And code is now content in a lot of ways because you can just build a little tool over a weekend and it goes viral in a way that an essay used to, you know?

And all the people that are at every like it's all sort of generalist multi-dimensional people who are like Every single person even if you're building a product for us like you write articles for us And a lot of our writers are building stuff. That's like a really powerful like kind of like creative Community almost which has always been sort of like at the core of what we're doing. It's just like shifted shifted the focus and

And then what we do is we we bundle everything together. So you pay one price and you get access to all the software that we make and all the writing that we make, which I think is like

um going to be more and more important as the cost of building software goes down having like a trusted place where um you can learn how to use ai and also access like really really high quality ai software all for one price is like i think a really compelling value prop so that's sort of where we're where we're headed the way it started is the way it started is like almost it's weirdly similar like it started in this in one place and then we kind of like did this like

like a long detour into another place and ended back where we started in a lot of ways. Because I started Every as a newsletter called Super Organizers, where I was interviewing people about their productivity tools and systems. And the reason I started there is because what I really wanted to do is build

like a tools for thought app, like a Rome or Notion type thing, because I've always been obsessed with like productivity and tools for thought and note taking and all that kind of stuff. And I had a bunch of ideas for a product that I wanted to build. But what I wanted to start with was doing customer interviews. And I needed a way to get interesting

people because I wanted to talk to like really, really smart, really high performing people. I needed a way to get those people on the phone with me to tell me how to how they take notes so I could build my product. So I was like, oh, I'll just interview them for my newsletter. I'll write the newsletter because I love writing.

But eventually I'll build a software product and I'll be able to launch it to the audience because like the thing about productivity software is that it's it's like a very fragmented space and like having early distribution helps a lot. And it's got like a vibrant community. People are really into these tools. Exactly. And it's built an audience or whatever you ended up building.

Exactly. And that really, really started taking off because it was at the very beginning of the like sort of substack creator economy wave, which at the time I didn't really know, but it was growing really fast. And I was like, oh, cool. It would be awesome to like make this like a media business. And so I started chatting with Nathan because Nathan and I have been friends for a long time. As a detour from the ultimate vision of making the product or a pivot, like, hey, you know what? I'm not going to build this product. Let's just do this. I think it was always in my head and always and always in Nathan's head to some extent that like

We could also build software if we wanted to. There's this weird every DNA, which is like both writing and writing.

Software products. Yeah, cuz like that's that's my background. That's his background You built like a whole CMS like you said sub stack was around but you guys built this whole new CMS that we still use Really is all internal. Oh, wow. Yeah, that's pretty cool. Yeah, so I mean I mean perfectly speaks to what you were saying. I was like part writing. Yeah, it's offered Yeah, cuz just I'm curious to know why you built your own CMS But to be honest with you did it so like we had like at the very beginning so it went from one sub stack to

Nathan started writing his Substack to, we bundled it. So a bundle concept has been sort of part of it from close to the beginning. And we sort of evolved it into this like writer collective type thing where, you know, the idea was with Substack, Substack's great. And it's really cool that writers are peeling off publications to like do their own thing. But also it's to some degree like intangible.

in certain ways, not a great experience for the writer and not a great experience for the reader. So in particular for readers, you have to have multiple subscriptions, which kind of sucks. And for writers, actually like writing alone kind of sucks. And the thing that you, the kinds of things you can write when you have to get out one or two pieces every single week is like a fairly constrained universe.

And so the kinds of people who can succeed at that are fairly constrained too. And so what we wanted to do is find like, is there a way to get writers the same kind of like creative freedom in economics as they get writing on their own, but like also give them the benefit of being part of a group? And if we can do that, like, can we bundle it together and give readers everything for one price?

And some of that worked and some of it didn't. But that was like the basic idea. Super cool. I remember all this now. I remember there were multiple, I don't know if you call them newsletters or publications. There were multiple newsletters. And there was a bundle. It's like every bundle, right? Yeah, it was a bundle of newsletters. And then over time, what I started to realize is like only a couple of the newsletters actually really worked.

Okay. And if that's the case, then you basically like, you have like maybe one or two that are like growing really fast and everything else is like the same fixed cost because you have to pay a writer and you have to do all this stuff, but like it's not generating anything basically. And then you start to be like, oh, we should just do one

which should just be one newsletter or one publication. And then you're like, but it would be cool to have all these writers. So it'd be like, oh, so we just reinvented the magazine from the ground up. So that's basically where we landed is every just became like one publication. Yeah.

And we had a bunch of different writers and there are ways that we still have tried to maintain the ethos of the collective. But my hot take is that there's this whole thing about how like, you know, publications are dead and it's all about individuals. But like, like, my goal is to build every into an institution. And I really actually think that like institutions, publications are like the future of media.

And the reason it seems like it's individuals right now is because all of the institutions are incredibly young. So in 20 years, like Mr. Beast or whatever is going to be a it's going to be a media company like he's not going to it's going to have other stars. It just looks like it's Mr. Beast personally for now. That's what we're building every into and

I think it's working. - And that's still the vision. The vision, it actually sounds like it was pretty similar to what it was when you started. I mean, beyond moving past the bundle and all that. - At least for me, yes. The vision is very similar. We care a ton about doing really, really great writing, doing really, really great writing about technology and business.

What we found over time is that the best way to do that great kind of writing about technology and business is to actually be doing it. So we've always had this sort of like practitioner ethos. Part of doing it is like I built Sparkle on a whim and that taught me a lot about, you know,

building productivity apps that I could use to write about. And then we sell to the audience and the audience starts to like it, right? And so if you're releasing these, if you're building these experiments to write about it, you should probably release them. And if you release them, sometimes they go really much better than you expect and they become businesses. And so there's actually like a really organic loop here of writing experiments and turning into products and then turning into eventually into businesses. So it's very important to me that the soul of every stay, like this sort of like creative playground,

where writers and other types of creatives come to do their best work. But I also think you can make a really, really great fucking business out of that now, especially 'cause it's so cheap to make software. - You said something really interesting earlier that resonates and something I've been thinking a lot about where you view software as a form of media.

Have you always viewed it that way? And where does this end up? The curve is flattening in real time right now. Where do we end up two years from now? - No, I have not always viewed it that way. You can trace the seeds of it back before pre-AI. There's plenty of times when I was-- - App stores is a great example. - Yeah, app stores. But there's plenty of times when I was in college and I would do a weekend experiment and then I would post it to Hacker News and it'd go viral. And write a blog post about it and go viral or whatever. So it's always sort of been like that.

But by and large, it's been so expensive to make software that you couldn't think of it as like really like a throwaway thing or like really just a thing that you just like do over a weekend unless you had like a very particular set of skills like Liam Neeson that you've honed over many years.

and sort of that full stack, like I design it and I whatever, like that's the only way you could do it. And now I think that's quite different, which is it's so cool to watch people do this. What is the exact definition of vibe coding? I feel like the terminology is moving so fast. I'm curious, like on this date in 2025, early 2025, what is the current definition of vibe code?

Vibe coding is like it's basically like having an idea for something and using cursor or some sort of similar tool to just like throw the idea in there and just like keep pressing accept all until it like works basically. And like maybe every once in a while, like futzing around and being like this thing doesn't work or whatever. But you're explicitly like not looking at the code ever.

When Cursor's fixing bugs, like you, you have no idea what's happening. You're just accepting. Generally not. There's this really funny meme that was going around yesterday that I relate to that is like, it's basically expressing this thing that you have to decide when Cursor or, you know, Windsurf or whatever has been like stuck in a loop for a while. You have to decide, OK, do I want to like tell it, please fix this? I

again for like the 20th time or do I want to like spend the five minutes to like go look and it's like I always just say please fix this I saw one uh it was just like a row of elderly people at like slot machines in Vegas just like yeah hitting the button that analogy is actually pretty good for these models in general across all modalities right text photos videos music it's like

You prompt it. You get what you were looking for, like maybe one out of 10 times. And that creates this like addictive variable reward system where like, I mean, it's actually not that different than like a social network where you open the thing up and one out of 10 times, hey, maybe that photo that you took got a like. Right. And so that's why you get addicted. Yeah, it's pretty similar. I wonder if that is going to.

remain in place as these models get better. Like when cursor fixes it the first time, maybe vibe coding isn't as addictive anymore. I don't know. I think, I think that there's like a, this sort of like expanding horizons, horizon of possibilities and problems. So even if it's not getting stuck on some dumb bug, it will like,

you know, it'll do a screen that you're like, okay, that works. But like, what if it was like this? Just expands. Yeah, yeah, yeah. Yeah, that's so true. The thing that I keep thinking about is what happens when coding becomes so easy and so ubiquitous and so ingrained in everything we're doing that like regular people are doing it. And I know there's a lot of discussion about this on Twitter. People are like, oh, that'll never happen. My dad's never going to make software. But I think

My guess is the format ends up looking quite different than it does now. I don't know. Have you put any thought into this? There's a bunch of different questions packed in there. But like the first one is, are our regular people, regular people going to make software? Is your dad going to make software? Is my dad going to make software? And I think when people ask that question and they try to answer it, they're thinking about like, is my dad going to make a SaaS app? Exactly. Clearly not. No. You know, but like, is my dad going to be like typing to like Claude one day and be like, hey, like,

Like I'm trying to figure out compensation scheme for the salespeople that I, that I, that I work with. Like my, my dad runs a cemetery and funeral home business and he has a salespeople. And like, there's, I, there's no doubt in my mind that one day Claude or touchy PT, which he uses regularly and loves is going to just like, be like, Oh, I can make that for you. And just like build him a little like front end thing that like calculates like, you know, salespeople's commissions. Is that making software? Yeah, maybe not. But like,

I actually think it is. And I think that that's... Sure, you see it creating a Python script. I think that's clearly the future. I think probably you may not really have access to the code and may not really care, like Lovable or like Bolt or whatever. But that is definitely a mass market thing that everyone's going to do. Also, anyone can make an actual product that they're supporting and becomes a business, and that's a separate category. And clearly not everyone's going to do that. But what I do think is going to happen is...

Right now, there's this small circle of people that want to do that and have the skills and the capacity and whatever to actually follow through with it. And that circle has just gotten bigger and it's going to get bigger still. For example, I was able to make apps in high school because...

There's a lot of different reasons, but one of them is I was willing to and able to take a programming book. I learned from books. Yeah, same. And get through the first five chapters that had nothing to do with anything that I wanted to make and was just like, here's what an if statement is and here's what a for loop or while loop or whatever. I was able to do that and some people are able to do that and some people are just like, I'm so fucking bored I could cry. But one of the things, I taught an AI programming course probably a year, year and a half ago

And it was four people that didn't know how to code. And one of the things you notice when that happens is like, you don't have to spend like six months, like learning abstract stuff that has no connection to like what you want to do. The first day you can make even, even a year and a half ago, the first day you can make something that does what you kind of

are dreaming about, and that just unlocks a lot for people and gives them the motivation to be like, well, how does this actually work? AI sort of fills in for people, even though they might have a desire to make something, they may not have the skills or their proclivities for whatever reason to do it, and I think it fills in those gaps. So there's more people who are gonna build products and businesses, but it's not everyone. - I saw a great post on X from, I think it was Bology,

who pointed out that prompting is actually coding, it's just a different level of abstraction, right? Like long time ago, people just learned machine languages. - Assembly. - Assembly, exactly. And then it's like, okay, here's C and then here's C++. And now we're just using natural language. - 100%. It's been happening for forever. I don't know exactly when you learned to code, but when I learned to code, people were saying that Python was not a real programming language 'cause you didn't have to manage memory.

And now, like, everyone's using Python. And everyone's saying, well, you know, prompting is not a real programming language. But, yeah, I think clearly that's just what people who have been coding for a long time say. Yeah, totally. And they're right. This happens with every media, right? It's like, that's not real podcasting. Or, like, that's not real music. That's not a real radio show. Yeah, exactly.

And they're right to some degree. Sometimes you do need to actually go down into C or assembly or whatever. And sometimes you need to go down into the Python when you're vibe coding. But those instances are fewer and further between and are for more specialized circumstances. And I think we all know, and this has been true for a long time, that a lot of programming, even pre-AI, was doing a lot of rote stuff where you're just copy-pasting from Stack Overflow. Yeah.

It's like the same thing. Guess what? This is much better. So true.

Yeah, I learned Visual Basic. That was my first, which I know even to this day, people are like, that's not a real programming language. And then C and all that stuff from there. But the software as media thing is fascinating to me. And I am very curious to see even what takes place beyond utility, like your dad using Claude to make the sales thing. You know, one area where I feel like there's going to be a lot of interesting stuff is just like...

like memes there's going to be some intersection with software and memes yeah partially depends on like the platform people are making this stuff on which i think is going to evolve i don't think it's necessarily just going to be within claude yeah or within chachi bt totally i mean that's starting to happen a little bit like did you see that meme format that was popular a while ago that was like it's like the make it more format and it was like you have a image of popcorn in a microwave and it's like make it more cooked and it would like

Pops. Like with an image. With Dolly or something. Oh, wow. That's cool. And make it more cooked and it'll like pop some of the corns and then make it more and it'll like pop some of the corns and then like catch fire and then the microwave would explode and then the house explodes or whatever. You know, you can even see that like, I don't know if you've been watching all the like

jd vance stuff but like there's all these like jd vance of his face yeah i'm curious where that is like ai generated yeah i'll pick a lot of it yeah that's very funny i think also like there's probably room for a youtube of ai software thing where it's like um it's sort of like almost replete ask where you're like yeah you make a thing you want to show it to people and like there's like a platform where people are just like building and sharing these like little apps that they make um

And they're probably not full blown apps, but they're like, you know, the kind of thing that people ship as a weekend project on Twitter. And I think that could be like a whole format that evolves that I don't think we know what it looks like yet, but it's definitely coming. Yeah, I think that could be for entertainment. I wouldn't I wouldn't be surprised if some of those things even have some like micro utility to them. And who knows? Maybe it's a special type of calculator or something. But yeah.

Yeah, I'm really fascinated to watch this whole space unfold. So every it's a collective of creatives who are creating media, which could be writing podcasts and now software. When you bring somebody in, when you hire somebody is the expectation that you're doing all of these things? I mean, it depends. But like, for example, we have a studio where we have entrepreneurs and residents who build stuff with us.

When we build a product, so like one of our latest incubation that we released is called Quora. - Yes, I wanna talk about Quora. - Okay, yeah. And it manages your inbox for you with AI. When emails come in, it decides if it's an email that you need to respond to. If it's something you need to respond to, it makes it your inbox. So everything in your inbox is from a human who needs a response for you. If it can respond, it will draft a reply for you, so you don't have to do the repetitive stuff.

Everything else gets automatically archived in twice a day you get like a really beautiful summary of all of the emails that you normally need to look at and need to like look at an archive and whatever but now you just scroll through it and you're done so your inbox is just way quieter and more beautiful that's fascinating to me that AI can be used to gain leverage in these non-technical industries and and I think Cora is like a great example of Something people can use. Thank you. I appreciate that. So Cora

um has a gm his name is kieran okay um and he built quora end to end he's also written articles on every okay uh he is like weirdly like a uh he spent a lot of time as a professional composer of music and a baker

Okay. So he does everything sort of full stack and we, we provide him a lot of help and when there's a lot of collaboration and all that kind of stuff, but like he owns it end to end and. He owns Quora. Yeah. Got it. Like he owns. Like the business. You know, he owns the product. Okay. Yeah. Does he know how to code? Yes. Or is this pure vibe? No, he knows, he knows how to code. Okay.

He's founded several companies before, was a technical co-founder of several companies. A lot of the people that work for Every have that like sort of multidimensional skill set. And particularly for the EIRs, they're like owning the full stack. But like we also have like, for example, we have this with this writer, Katie. When we have EIRs write, sometimes they're good writers, sometimes they're not. And she does a lot of like

co-writing with them to help them like get out their ideas. Um, but she's also like using now using like a lovable all the time to like build little tools for herself. Um, or we have another writer, her name is Ria, who's doing the same thing as like building custom GPTs. And like, so it's all kind of there. All these people are like now curious and interested in like, they sort of see how powerful it is. And once you get them going, they're like, Oh my God, this is amazing. You know? Um, so I think we have an, an

an environment that stimulates that and values. I think in general, startups really value generalists. But this is like incredibly empowering for generalists if you kind of like

allow them the space and freedom to play. So like one of the things we do every quarter is we do this thing called Think Week, where we don't publish anything new. We don't do any meetings. Every day there's a theme, but the idea of Think Week is to sort of recognize that most of the time in a startup, you're spending

time being like sort of very reactionary. Yep. And you're just like under like constantly under fire, like trying to make sure things are not breaking and like whatever. The best creative work comes from a different sort of place where you're not reacting to your circumstances. You are like proactively kind of like playing around and like following like that thing that you just are psyched about.

And Think Week is really about getting back in touch with that. So we don't do any meetings. We don't publish anything new to the extent we can. Like we're like, you know, pausing a little bit on some of the product stuff. And every day there's a theme. And the idea is pay attention to stuff that inspires you. Pay attention to whether or not you're in that sort of reactive mode and sort of get into a play mode. And then like one of the days this time, we did like a day where it was like experiment with a new tool that you've been meaning to experiment with, but you haven't. And that's how Katie started using Loveable.

And I think that that's actually so fucking important for businesses right now. And we do this with, we have a consulting arm where we do consulting with big companies and help them use AI. And this is like one of the big recommendations is find space to play. Yeah. Like every employee has this, like it doesn't matter if you're an employee, executive, whatever founder, you have this decision you have to make every day, which is do I do things the way that I know how and get them done? And then,

I have so much work to do that like if I worked the way I know how for 20 hours a day, it still wouldn't be enough. But like I can just get it done and I can go home and whatever. Or do I spend like two hours like playing around with this new tool that may not work and probably won't. And then I will have to go and do it the old way I knew how anyway. And I'll be further behind. And like everyone, unless you're someone with like a really, you know, curious early adopter mindset, everyone is going to do the first one and they're just going to get their work done.

But the skills are changing really rapidly. And if you have invested the time and you are a little bit more familiar, your rate of progress and your rate of productivity is so much higher. You just need to like be given the space to realize that. We do that as a concerted regular practice at every end. It also, I think, works for other types of companies, too. I'm curious with something like Quora. Again, that product is super cool. If that takes off.

What happens for any of them, you know, core or any of them? What happens? Does does every like reorient itself around that product? No. Spin it out. Each product is is its own separate business. Oh, that's majority technically. Technically, that's majority owned by every how much we own is dependent on the circumstances. So they are already spun out. Yeah. Some of them actually not everyone. Some of them are still internal. It depends on like.

how big a potential there is. Like there's a lot of circumstances where it makes sense to keep it in. How many are there? There's four. Okay. But Quora is already a separate business. What we have found is if those products start to take off and some of them are like Quora is really, I mean, I worked on a lot of stuff and Quora is like the most promising thing I've ever seen. Wow. Yeah.

That's really good. When people start using it, they just use it. Like it just, it's so sticky. They really love it and it solves a big problem. It's very cool. The reason I say code is content is like they push so many more people into the every ecosystem. Like we're growing just in terms of audience size so much faster. So there's this really nice symbiotic relationship where people want to try Quora because they know every did it.

And then Quora starts to grow and it becomes this like thing that's like has an audience in its own right, but they're pushing people back into the every ecosystem because it's like made by every. And then we have a, you know, we have an onboarding sequence. It's like, you should read every because a lot of people who are signing up for Quora are early adopter people. So they kind of, it's good for them to be in the ecosystem. And Quora, for example, we can't let in everyone at once because we're scaling it and it's, it's a hard product. So like we have a 10,000 person wait list. So rather than let those people just like

dry up on the wait list. Like they're now in the every ecosystem. They get emails from us. They kind of like they're in the whole

thing and then they start to get you know introduced to other products and so it becomes really this whole ecosystem that i think is really valuable and i think all of the like ars and stuff recognize that and um and everyone's sort of on board to make every this like sort of special place that i've been talking about so if it if it gets big i think that's amazing and i think the bigger the bigger these things get um the probably the less reliant on every itself that they'll be but um they will prop up

every at just as every props them up and make something that's bigger than either one individually. You said these things are their own entities. I mean, you could end up fundraising just for Quora or you could end up, I mean, yeah, like you can end up putting in a different office and yeah,

And I'm guessing, you know, if you're telling me like it's super, that one is super promising, it probably will grow to some extent. I hope so. Kind of get spun out or I guess it's already spun out. What are some of the other products you guys have built? So there's Sparkle. So we have Quora, we have Sparkle. Remind us again what Sparkle is. Sparkle is an AI file cleaner. Okay. So it just looks at your files and on your desktop downloads and documents folders and then creates, uses AI to create an ontology of like, here's... I could use that.

My desktop is pretty cluttered. So my desktop always looks clean and I don't have to do anything, which is great. I love it. So that's really cool. And that's actually growing pretty fast. We have someone who's really talented doing that. We have Spiral, which is basically does marketing automations for you. So there's a lot of repetitive work in marketing and marketing.

Writing and anything you might do so like for me like I do a podcast or you do a podcast every week like there's a Format to the tweet for that podcast. Yeah So like you can put a spiral that like you train it on examples and then it like forever will like get you to 80% on the like

- That's really cool. - Yeah, it's really cool. I think it's really valuable. We've got a really talented AIR Danny working on that. And then the last one is Lex, which I think that's how we met. - That's right, yeah. When Lex was still inside of every-- - Oh right, so Lex is a great example of a spin out. - Yes, exactly. So Lex was built by my co-founder Nathan. Lex was launched like pre-ChatGPT, so it was like really early. It went super viral.

And then we ended up spinning that out. That's his own business. Nathan runs that, raised money for it. Different businesses take different paths, basically. And we'll do a bunch more. We have a bunch more in the pipeline that I'm really excited about. So the people that build these, it sounds like it can happen any different way. But are you bringing in EIRs dedicated to...

to pursuing specific products or is just like, hey, one of your writers might end up making a thing and then they're an EIR now? The answer is yes, both. So basically, like sometimes we'll make a product like I built the first version of Spiral or Sparkle.

And then we will go and like recruit an EIR, um, to run it. And the recruiting is more like we like put a little thing in the newsletter and then we get a bunch of applicants and like some people stick, you know, then sometimes we've, what we've done is like, we have a little bit more of like a program where we're like, you don't have an idea, but you kind of want an idea and you love every, so like come hang out with us and, um, build experiments, write about them. And then like, uh, we'll launch them to the audience. And if something works, like

great becomes a business and we have like three or four EIRs that are like that. That's really cool. It almost reminds me of back in the like the early iterations of Betaworks back in the day if you remember what that was like. I've definitely gotten a lot of Betaworks sort of comparisons which I love. Yeah, yeah. And I was not really around like I was sort of in New York at that time but like Betaworks like had like it still has but like really back then really had this like aura which is really cool. Yeah, you know there were the

the first check I raised for, I was so drawn to beta works. - Yeah. - You know, we were building anchor. I was like, I gotta work with beta works. - Yeah, yeah, yeah, yeah. - Maybe you already do, like sort of have that same sort of, oh, I gotta go build something at every, I don't know what it is, but I wanna go build something at every, right? - I hope so. - And the podcast now, that's another media format or property you have. Tell us about that. I mean, I guess maybe it's kind of obvious what that is. Just, it's all the stuff you're doing, but now in a new format. - More or less, yeah. I mean, it's called AI and I. It started as a podcast called How Do You Use ChatGPT?

Oh, that's right. I remember that. And that was like sort of at the very beginning of ChachiBT where everyone was like, I know I should be using this, but I don't know how. And there were some people who had really figured it out. So that was like the first, I don't know, six to nine months of the show, which was awesome. It was very timely. It was also at a time when video podcasts were really starting to take off and go viral. So that was very cool. What I found after the first six or nine months is like,

most people use ChachiBT in the same kinds of ways. And so there are still people who are doing crazy stuff, but like they're harder to find. What's the craziest thing you're seeing people do? I think the biggest, like most, most crazy stuff right now. And I,

I've been doing this, but you know, it's sort of it's starting to happen is like doing notes and stuff with cursor. It's like a really, really cool one. I keep saying this. Explain this. I haven't tried it yet. Yeah. This is where I started with every with super organizers is like I want to organize what I know.

That's like the core question for me. And AI just like totally changes the game where you're not like, you don't have to do these like backlinks and like whatever tags or like it just it solves every problem that we thought we wanted solved in a much better way than previous technology could solve. At least where I started with this, there's a guy who wrote a blog post about this that originally inspired me that I had dinner with who I whose name I'm completely blanking on right now. So please excuse me, whoever you are. I think you're amazing. Poor guy. Yeah.

I talked to him about it, but basically the way that it works for me is I take a bunch of notes. Some of them are like from my Apple Notes or some of them are from like my export from Roam or Readwise or Evernote or whatever. And they're all in text in a folder that I then open Cursor. And Cursor has this like agent experience, right? Where you can be like, find me a note that whatever, and it's supposed to work for code, but it actually is quite good at just like searching through text files for particular things, which is kind of cool. But the really cool thing is that

If you want to do something more advanced and you're like, OK, I want you to gather all of the notes that I have that seem to be about, I don't know, the Civil War. And I want you to organize them by time and then put them all in a file so I can read them through. So it can't just do that in the agent, but the agent can build any kind of software you want. So you can be like, I want you to make a tool.

that is really good at searching through and finding bits of information for my notes that are like this and then outputting them to a text file and it's like cool i just built it and then then you update your cursor rules and you're like cool here are your powers here are your tools and so the cursor rules and tell it like what it can do and it becomes this like kind of that's really organizing thing it's do you have to recreate it for each use case or just kind of

build on this one. You kind of build it on this one thing. That's really cool. Obviously, Christian and I have not built for it. I think someone's going to do it really well. There's a big opportunity for that. Another thing that I've been doing, which I...

I think is really cool. And I will probably release this as a product. It's called deep background. Um, and it's sort of like a play on deep research. Yeah, of course. So one of the things about deep research, I think deep research is just like the coolest AI tool that's been released in the last year. Um, and one of the things that's really interesting about it is the responses get better if you give it better sources, which, um,

We've known for a long time. You have to direct it quite a bit. Yeah. If it's too open-ended, it doesn't really perform that well. I spent a lot of time, like, I don't know, a couple years ago talking about, I was calling it at the time knowledge orchestration, but basically, like, the context you provide to a model governs a lot of whether it's good or not. It's not just about the raw intelligence. Yeah.

And deep research, like it has a search tool, but a lot of the stuff it finds is like blog spam because that's just how the Internet works. Yeah, I noticed that too. Deep background allows you to provide your own context to deep research. So basically what it is, it's a web app. You can drop any file into it and then it organizes it on a deep research friendly web page. It's just plain text built for AI agents. And then you can kind of like say deep research like

I'm interested in this question. Here are all, here's all the sources. And then you can put books, you can put like all your notes, you can put whatever you want. Why couldn't you just put that into the context window on deep research? I've found that it's not very good at, um,

if you get a bunch of files like exploring all the files well they may fix that at some point it's much better at browsing through a bunch of web pages um and uh and also it makes it more portable and like you can just have this like one repository everything that you might want to give to an ai agent that you're constantly adding to like notebook lm meets deep research yeah sort of like that yeah pretty cool i think it's really cool we might merge it with sparkle we're not sure yet um so you have it on your computer but yeah but i think just generally like the way that i think about it right now is um

It's sort of the about.me but for AI agents where everyone's going to have their own little knowledge repository that is like...

publicly accessible to AI agents that they like take around with them. One of the things I keep hearing a lot about is the opportunity for these MCP servers with Claude. That's one of the things I'm now thinking about for this tool. Like I'm going to do that this week. Basically like MCP, it's called model context protocol. It stands for model context protocol. And the idea is that

It is a way to build little APIs or website type things for agents. So if you're using an agent and you wanted to have access to a certain type of information, like let's say it's like GitHub repositories or maybe it's your deep background website,

It provides a format for the agent to understand what information is available and what tools it can use to like search through that information. It's sort of a layer between like whatever context you want to give the model and the model itself so that the model can like optimally

and find what it needs to find inside of the information. And it's like a standard protocol that I think Anthropic created. So there's a standard way for, you know, Cursor to go access like all the files on a particular website or whatever. Got it. And so I guess the idea is people are going to start to build all these hooks into all these different things. Your email, your notes, your whatever, your GitHub repository,

That's pretty cool. And they already are. Okay. Oh, they are. Where do people find these things? There's a bunch of like GitHub repositories that are like little directories right now. Okay. And then there's on Twitter and whatever. It's just starting, but it seems like it'll be a big deal. All right.

All right. So back to the podcast. So this was a way to explore the way people were using chat to BT. And that's how we got on this tangent around using cursive. And then I got bored with that. And then I was like, I just want to talk to interesting people. So like every podcast starts with a very specific idea. And that just becomes an everything. Yeah. I mean, you know, so now it's AI and I, we rebranded to AI and I, and I,

I'm really interested in how AI changes how we work. Like the eye in AI and I is also about like how it changes like ourselves and what it means to be human and how we see reality and how we see ourselves and all that kind of stuff. And so I tend to talk to a mix of like startup B type people. And then I guess I'm like sort of starting to branch out a little bit more into like

scientists, philosophy, creative type people who are working at that intersection because that's like the stuff that fascinates me. Yeah. With the podcast, do you imagine that you will maybe eventually take a similar approach as you've taken with the writing and have different hosts or different shows? Like, does this part, does this become part of the collect,

Yeah. Of every, I mean, it is, it is already. I think like we've, we've had, this is not our first podcast. We've had a hundred different podcasts. We used to have a podcast with Legion called means of creation. Oh yeah. That's right. We've had a couple other different ones. Me and Nathan used to have a podcast. There's just, there's a bunch of them. We'll definitely do more. I think like the core is the writing. And then I think the big exciting thing is the software. And then I think we're also starting to branch out into video. So I've done some videos. We have a really good

- Beyond the podcast, you're saying, like one-off type. - Yeah, a lot of like, I got this access to this new model, like let me tell you how it works. - Oh wow, yeah. That's really cool. - And those go really viral, it's really fun. - Yeah, I noticed that it seems like you do seem to get access to these things early. You're almost becoming one of these AI influencers that's part of the influencer program, some new video model. Was that intentional? - Definitely, yeah. For a lot of different reasons, the core is just, it's super fun.

If you told me when I was 12 that I would be able to just like get access to new stuff before it came out, I'd be like, yes, sign me up. Did you have 4.5, GPT 4.5? What are your thoughts on it? I know there's like, people are very divided over GPT 4.5. So we got access to it for a couple of days before it came out. And the take that we published initially was like,

this thing isn't isn't mind-blowing yet but like it's very hard to evaluate models really quickly and so like everyone should just like take a deep breath and like play around with it and um right now it seems like it's sort of like claude sonnet 35e and that's what that's what uh openai is saying but like we just we just don't know yet and it's not one of those things where it just obviously knocks your socks off the first time you use it now it's about a week later and i'm like oh this model's great

I really like it. An easy one is it's funny and it's really hard to be funny. Yeah. These models, they really struggle with comedy. This is good. Yeah, it's really good. It's the first model that made me laugh. I actually think it's the first model that like I could have it sort of swipe on hinge for me and it would do a good job. It being funny as a sign of intelligence because we're so used to the default picture of intelligence being something like, oh, it can do math well.

or it can code really well. And it turns out that that was like sort of, it's still hard, but it was like relatively like the lower hanging fruit. And actually just making a good joke requires a lot of intelligence because you really have to know a lot about the world because

because a lot of humor is um saying the exact opposite of what's true right and so you have to have a good sense of like what's true and a good sense of being able to say it in a way that like comes off as a joke um and is the opposite of what you actually mean and that's that's a very subtle thing to be able to do so it's funny in the sense that it could write a stand-up routine it could tell a joke one of its best tricks is you know the like 4chan green text where it's like be me like uh

uh, Google exec or whatever. And then, and then it will just like, um, write out just like a funny narrative about like a person's day. Like I'd had to do that for me. And I thought it was so funny. Um, and I've seen a lot of other people do stuff like this. The thing that actually just totally changed my mind is, um, I started getting into do chain of thought reasoning. And once it started to do that, it was like incredibly good, which is interesting because chain of thought is like one of those things where it was like a big deal. Like

a year ago. And then you started to feel like you didn't really have to use it, especially with reasoning models, which like just internalize the chain of thought in the, in the reinforcement learning. Some of the things I've been using it for are, I had to write some poetry with, with a chain of thought, which was like incredibly good. Um, and it made, it wrote some lines that I was like, oh man, like I'm, I feel touched. Um, but I've also, um, had it help me like, um,

edit writing where George Saunders is a short story writer, like one of the top short story writers in the world. And he has this editing technique. You read one sentence at a time and you just feel whatever that sentence makes you feel. And it's either going to be like,

Like it's sort of starting to make me like into this and there's something interesting happening or it's negative. Like I got pulled out and I'm bored or like I'm confused or whatever. And all of writing aside from the first draft is basically just like doing that process of one sentence at a time. Just like saying like, how do I feel? Do I like this? Do I not like this? And why? And embellishing the stuff that you like and editing the stuff that you don't like and sort of like radically infusing your taste over and over and over again into every little thing that you do. Sounds like a model in a way.

It sounds like tokenization. There's something about that. There's some overlap there. But I had GPT-4.5 do that with a couple pieces of writing that I have where it's like reading each sentence and then outputting what it's thinking and feeling. Oh, wow. And

It's really good. Wow. It's very helpful. That's really cool. Yeah. It feels like there's a product to be built there. There's a lot. Yeah, an editing product. Yeah. There's editing. One of the other things I've been excited about recently, because I fucked up my wrist as we've discussed. We should discuss it on camera. Discussed off the show. Yeah, yeah. I was living in Panama for the last three and a half weeks. Again, most interesting man in AI. Yeah.

I had a little, it's called a pocket bike. So it's like a motorcycle, but it's like small. Okay. I was going downhill on it and I just like braked a little bit too much with the front brake. And I just like went over the handlebars and braced my fall and

I don't think it's broken, but it's like, you know, I sprained something or there's some tendon that's like... If all you did was sprain your wrist getting thrown over the handlebars of a motorcycle, I'm just glad you're here. Yeah, me too. I was wearing a helmet. My mom doesn't know about this. So sorry, mom. Hi, I'm fine. What's funny is like that was the day where I got access to GBT-455 and we had to write the article for the next day or something like that. So I was like writing...

One-handed this this this review and And the thing that saved me is our speech-to-text is so good. It is really good So I was using whisper flow a lot Yeah, and I would not be able to work right now because I can't type so I would have to be like so you just dictated it just a kid Yeah, GPT 4.5 like edited and I dictated it what's for flow did it? I had a lot of I was there's a lot of back and forth with Which you'd be 45 to like make it better and

I have a co-writer that I do a lot of the model releases with. His name is Alex and he's fantastic and is such a big model nerd and also like really, he is dramatically improved as a writer over the last like

Two months like dramatically more than I would expect having worked with a lot of young writers and it's entirely because of AI It's wild like he's made progress that I would expect to take at least a year in a month or two anyway So he did some of it and then Kate who is our editor-in-chief who was previously the editor-in-chief or the publisher of strike press? I just got a little Kaylee. Yeah, I just got on the phone with her and I was like look like I

we need to get this out in like two hours. Like, I just need to tell you what it should say and like you write it and then I will like edit it a little bit. And she's like, I got you. Because just glad you're alive. Yeah. So it was a true team effort of humans and AI collaborating to get that article out. But it's been an interesting forcing function to like use all the text to speech stuff. And now I have so many ideas for this. Like it just feels and I've actually heard this. I'm curious what you think. I've heard this from a lot of parents

that voice is the native interface for computers for their children. Yeah. For a lot of different reasons. And that I think is like really intriguing and makes me feel like it's important to interact with a lot of things using voice. Yeah, I feel the same way. I, you know, as somebody who built an audio company, I've always wanted voice to be like the primary input and, you know,

know output modalities or whatever i'm hopeful but like still somewhat skeptical because it's i think it is the most natural but it's just at least for consuming it's just not as fast it's not listening it's only dictating yeah dictating it's voices the interface just to get your thoughts out i use i use you know voice transcription or dictation on my phone all the time and it's like

It's never perfect, which is frustrating. I think if it was perfect, yeah, I would use it constantly. And I do always find myself wanting it on my desktop. I'm always like, ah, I wanted to just talk to it. Have you tried Whisperflow? A little bit, yeah. I need to really commit to it. It does that pretty well. It's so funny. I usually write every Friday, and I haven't been doing that this quarter because I'm writing this big, long piece that I think is turning into a book. Oh, wow. Yeah.

We'll see what happens. I got up this morning. We're going to record this morning. And I try to do a thousand words a day. And I just did my thousand words in like 30 minutes. And it felt like cheating because I was just like talking and it was done. And I was like, is that it? And just cleaned it up. Yeah. I mean, it's not final at all, but it's like it's enough where I'm like, this is this is good enough. You know, like I'll come back and

and like really, really edit all this like once my hand is healed. But yeah, it's really cool. - It's like when people said audio books are not read it like it feels like it's gonna be the same thing for writing. What about some of the other models? Like how do you feel about let's say Grok? - In my limited testing it seems good. I haven't really needed to use it that much. I think the interesting thing to me about Grok is one of my,

In the very early days of AI, I wrote, or this generation of AI, I wrote this piece called Artificial Unintelligence. And the basic idea is that the models are already smarter than we allow them to be. Like they're being made dumber on purpose by the model companies because it's risky for them to be too smart. The easy example is they're not going to tell you to make a nuclear bomb, which is good.

They should not let you do that. But there's all of these ways in which like we are artificially constraining their capabilities already, even in the GPT-3 days. A place where there is going to be a competitive advantage is companies that allow

their models to return risky results. Which seems like Grok is. It's the whole idea. Exactly. Ground truth. And there's like, you know, you can interpret risky in lots of different ways. So like Grok is like Nazi for work things or whatever. Another form of risk is like

it will give you legal advice. But so whatever, whatever form of risk we're talking about, but like Grok definitely fits into that category. And so I think that that's really interesting. I think in a lot of ways, open source models are more fit for that job. Yeah, except they're,

far less accessible for most people. - For now. - Yeah, for sure. - I think at some point, more on-device stuff is gonna be a big deal. - Yeah, I totally agree. - So I think Grok's cool. I mean, Claude. - Yeah, what about Claude? - Everyone inside Evry is like, "Holy shit, this is so useful." They're just going a lot faster. People love Claude code. - Oh, you think Claude's going faster than the other? - Yeah, for code specifically. - For code, yeah. 'Cause I feel like some people feel like it's the opposite, Claude's moving slower. But I guess for code,

feels like everyone loves claude for code one of the takes that alex who who's my who's my co-writer some of these pieces one of the takes he's been playing around with that i think he may maybe post this week i don't know if it's published yet i think it is um

is a lot of the, you can see some of the model providers starting to pick their lanes a little bit and it's not just like totally general intelligence. It's like actually, Claude is like, well, we should really be good at coding because that's what everyone uses us for, you know? And I think that that makes a lot of sense. Well, all the revenues, not all of it, but most of it's in the enterprise, right? So that makes sense. Just to piggyback on that a little bit, I just think that that's so...

It's so clearly where things are going and we had this idea of you know general intelligence is this like a God thing that could just do anything and One thing is becoming clear is that distinct different models have distinct like sort of views on reality or different vantage points that they come from and That is not something that is like easily you can't easily get rid of that which is everything all the time and

because the way models work is knowledge is distributed implicitly across like all of the neurons in the network and all the connections in the network. And so each connection relates to thousands and thousands and thousands of things that a model knows. And so if you change one of them, you're changing lots of different things in the network. And so good things or things that models are good at tend to be like very highly interrelated. And so if you make

really good at coding, you end up unintentionally damaging its ability to tell jokes. And there are things you can do to make it better at jokes, but then there's something else that changes. And I love that. I think that's a really beautiful and interesting result. And it's also...

You know, you can see that in people. Everyone that you meet is a general intelligence and people are very different. And that's actually a good thing. Pretty clearly, like everyone has their own arsenal of tool or models that have different viewpoints on reality that they use for different things. And I think that's definitely the future. What is GPT's lane? It's like just consumer and enterprise, basically. Most of their, they're the inverse, right? All their revenues for most of it's consumer. A lot of it. But I still think like if you go talk to businesses, like no one's heard of Claude.

Everyone knows OpenAI. You think so? Yeah. Everyone's like, what is that? OpenAI is the standard. And I think that they're just hitting the gas on that and they're becoming an application company. They still care a lot about research, but like,

the application layer is like where they're going to compete and win and they have the distribution and the kind of like name brand advantage and i think they're going to be that i to be honest i don't know like anthropics revenue figures off top of my head and i think they're amazing people um and their model is amazing but they're very very far far behind even in the enterprise the lesson that open ai learned from

ChatGPT is that the power of the model doesn't have that much to do with how well it's adopted because it was the same model, but when they wrapped it in ChatGPT, it took off.

And I think you can see that in all the rest of their product releases. So like their computer use operator, it's an app, right? Anthropic released an API. They released an app. I think you can see it with Sora. It's not an API. It's a product. It's a product. It's a dedicated product. So that's the lane that they're picking is like mass adoption consumer and enterprise products. And I think that's valuable. I think there's lots of other places in the stack to play.

It seems like Claude is picking the code path. I think that's super valuable too. Or Anthropica is. Yeah, they have to figure out something with the model names though. I'm getting really confused personally. It's very bad. Yeah, but I saw somebody, maybe they're in some testing group or whatever. Somebody on Twitter yesterday is getting like the automatic...

- Switcher? - Yeah, that makes sense. - I don't know if you have that yet. - I haven't seen that. - I haven't gotten that yet. That makes a ton of sense. I think especially as more and more people adopt this stuff, they're not gonna wanna pick them. They're just gonna wanna do the thing, right? And the model will get sorted out. - To some degree, the models are already like that. They're a mixture of experts models, so they have different models inside of them, more or less, that they route to automatically, but then there's

There's layers of this. So, yeah, I think the automatic routing makes a lot of sense. Maybe GPT-405 can help them figure out how to name these models. Yeah, exactly. You know, you're playing with all these models. Obviously, you're also playing with products. Like, what products are exciting you, right? Obviously, Cursor. You're spending so much of your time in Cursor. What else is interesting to you? Cursor, Windsurf. Windsurf. It's really cool. Obviously, Granola. Granola. Yeah. Thank you for that.

All the credit is due to the team, Chris and Sam. Like I was just very, very lucky to be a tiny part of the part of the journey. Yeah. Yeah. It's a great product. I use it as well. I'm biased, but I use it every day. Yeah. Obviously, all the internal products we have, those are really the main ones. I think people ask me that question a lot. And yeah.

I really think a lot of the, you know, the clods and the chachiwitis of the world are so still so untapped. I think there will be a lot of really great AI products that are standalone and not part of that ecosystem. But I think of them as being this generation's Excel, where Excel is very easy to start with.

um anyone can type into it yeah into a cell but you can build mario kart in excel you know it's it's endlessly powerful and i think chad gbt and claude are like that easy to start with but there's there's so much we're just scratching the surface what you can do with just chat models and um it will take some time before people have built up these really specialized power workflows that they are like

I know how to use this and I can do it in cloud, but it's like hard. I would like a special tool. Same thing for Excel. Like Excel taught a generation of people how to use computers.

And eventually they made powerful workflows that they were like, it'd be great if I had another app for this. And then B2B SaaS became a huge thing. I think the same thing will happen in AI. You do? Yeah. So you don't think, because a lot of people think that ChatGPT, Anthropic, like the model's ultimately going to take over these individual sort of verticalized workflows as well. You still think there's a huge opportunity for companies, startups, people to build dedicated products. If I had to pick what OpenAI's product strategy is going to be, I'd like...

probably pick Salesforce. Salesforce. Like Salesforce has like Salesforce Marketing Cloud and like CRM and like all the sales cloud, like whatever, every vertical they have, every like, I don't even know if,

Every business sector or area, they have a product, you know? So I think they're definitely going to, it's not just going to be like ChaiGPT. Reports are they have a sales product, sales automation product, you know? I imagine they will do a customer service product eventually. But they won't do everything. They definitely won't do everything and there will be a lot of room for specialized players to participate.

to do amazing stuff. - What about this whole theory that when the model gets good enough, we have AGI or super intelligence or whatever, products will just get spun up dynamically for all these things. So business needs, I don't know, business needs

note transcription, like, yeah, you just spit out to granola, you know? Yes. And I think that's not going to happen. There's two things about this, that vision of the world that I think people are missing. One is the thing I brought up earlier, which is this sort of like bundling of capabilities. So as you get good at one particular thing, you get less good at other things. Reality is very complicated. It's very high dimensional. You get one, get good at one part of reality. You start to get less good at others. It's just still sort of

somehow the way things work because of the way that these networks are built, which parallels a lot of the things that happen in our brains. That's one reason. Another reason is something we talked about earlier, which is the power of the model is in large part

governed by what context you can give to it. Being in a particular area of the world where you know a lot about the world allows you to prompt the model in ways that like a generalized player, they could do it, but it would like, it's not just about raw intelligence. You have to actually go into that part of the world and get the data. So there's like this whole empirical aspect of intelligence, which is like, yeah, you need a lot of experience to like actually in a particular part of the world. And lots of worlds have, the world has a lot of these like little niches with like, um,

Things that you can't just learn by going and having a conversation. You need to spend years. There's lots of long feedback loops. It's incredibly complicated. And so I think that there's a lot of room for people to sort of specialize, even in a world where we have AGI and the...

a way to think about it is, okay, you're starting a, like a waste management company. I don't know. I'm just picked it. I just finished rewatching The Sopranos. I mean, that's why I'm thinking about this. Amazing, amazing show. It's about that. It's about that time. Time for a rewatch. And who do you want to hire for that? People who are in waste management, I'm just,

you know, using my own experience for other things. Like they have a certain like flavor to them or like way of seeing the world. People who work at Evry have a certain flavor or like way of seeing the world. And you want to find people that are like that or you want to find young people who can train to see the world in that way. And I think models are going to be quite similar. I think people forget about that when they think about AGI because they like,

we actually have very little intuition for what an AGI is going to be like. So we imagine it to be like this all powerful thing. And if you imagine all powerful thing, there's a lot of conclusions you come to that are wrong. If you imagine it to be like, just like a person, which is sort of what you're trying to do anyway, which is like, yeah, it can just learn anything that I can, that a person can know. There's still lots of differences between different people. Yeah. And even someone who's a genius at one thing, like Einstein, like I still wouldn't

want him to like run an app, run a, be a GM for a product at every like he would suck. So, so I think maybe, yeah, maybe, you know, no, you know, no shame to Einstein. But I really think that's, that's the case. And that's, that's where we're heading. And I think that's really cool. I think there's a huge emphasis on

um, intelligence as, um, sort of abstract reasoning, which is definitely part of intelligence, but there's another part of it, which is, um, uh, built up through experiences in the world, um, that I think we're underweighting in our thinking about this stuff that will become much more, much more apparent and much more, uh, uh,

critical to our thinking over the next year or two. So the future is bright for startups and app builders in AI. The models aren't just going to take everyone's jobs and take away all the opportunities. I mean, I do think there are important social conversations to have. I think jobs will change and some jobs will be eliminated, but definitely the doomsday scenario is definitely not happening. That sounds like a perfectly optimistic place to leave it. Dan, thank you so much. This has been awesome. I can't wait to do it again. Thanks for having me.

Thanks so much for listening to Generative Now. If you liked what you heard, please rate and review the show on Spotify, Apple Podcasts and YouTube. And of course, subscribe. All that stuff really, really does help. And if you want to learn more, follow Lightspeed at Lightspeed VP on X, YouTube or LinkedIn. Generative Now is produced by Lightspeed in partnership with Pod People. I am Michael Mignano and we will be back next week. See you then.