Do 60-Minute Coding Tasks in 60 Seconds—With AI - Ep. 41 with Steve Krouse

Here’s the most compelling benchmark of AI progress: A task that took 60 minutes a year ago now takes 60 seconds. In January 2024, researcher Geoffrey Litt and I spent an hour coaxing ChatGPT to build a simple app on this podcast. Nearly 12 months later, Steve Krouse and I built the same app with one prompt in less than minute. Steve is the cofounder and CEO of Val Town, a cloud-based platform for developers to write, share, and deploy code directly in the browser. In this episode, we used Townie, an AI assistant integrated into Val Town, to build an app that would keep track of time on the podcast, take notes, and generate more questions for the guest. Townie had generated the app even before Steve could finish describing it on the show, a mark of how much AI has evolved over the last year. As the founder of a growing startup, Steve tells me his contrarian take on why he isn’t focused on the needs of the non-technical AI programmer, betting instead on being the platform sophisticated developers turn to for backend infrastructure. He also tells me how he started programming and how it continues to shape his vision for Val Town. Here is a link to the episode transcript. (Disclosure: I’m a small investor in Val Town.) This is a must-watch for founders building AI-powered developer tools, and anyone interested in the future of programming. If you found this episode interesting, please like, subscribe, comment, and share! Want even more? Sign up for Every to unlock our ultimate guide to prompting ChatGPT. It’s usually only for paying subscribers, but you can get it here for free. To hear more from Dan Shipper: Subscribe to Every: https://every.to/subscribe Follow him on X: https://twitter.com/danshipper Links to resources mentioned in the episode: Steve Krouse: https://stevekrouse.com/, @stevekrouse Val Town: https://www.val.town/ Townie, the AI assistant integrated into Val Town: https://www.val.town/townie/signup?next=%2Ftownie Pieces on Val Town’s blog about how the team built Townie: How we built Townie—an app that generates fullstack apps, Building a code-writing robot and keeping it happy The book by Seymour Papert about how programming changes the way you think: Mindstorms: Children, Computers, and Powerful Ideas

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Speaker 00

  It's just so cheap to make software that we can make an app for this podcast and then never use it again. So there are three parts. One's a timer. Another one is for notes. And then the last one is a like a chat GPT integration where it'll read the notes and then generate more questions.

• 0:14Dan Shipper?

  And I'm laughing because it finished the app before you were done describing what the app was to me.

• 0:23Dan Shipper?

  That's actually super cool. I love this.

• 0:26Speaker 00

  I didn't expect to have non-programmers be able to use Val Town so soon. That's been a long-term ambition. There are people who really don't know anything the first thing about coding and come on to Val Town and make stuff like this in a minute or two and their mind is blown and they're so excited. And that's amazing.

• 0:55Dan Shipper?

  Steve, welcome to the show.

• 0:57Speaker 00

  Thanks so much for having me, Dan. This is a dream to be on your podcast.

• 1:03Dan Shipper?

  So for people who don't know, Steve and I have been friends for many years. At this point, we met in college. Steve is the co-founder and CEO of Val Town and Steve will be able to describe Val Town better than I can. But it's sort of like a social coding site. Steve, how do you describe Val Town?

• 1:23Speaker 00

  Yeah, it's, it's, I think harder than most companies because it can do so many different things. The poem we have on our website, I think, I think holds up remarkably well. If you're a programmer, it's if GitHub Gists were fun and AWS Lambda, no, sorry, if GitHub Gists could run and AWS Lambda were fun.

• 1:40Dan Shipper?

  Exactly. So, I mean, basically, like, basically lets you code in your browser and share your code snippets and build and compose code snippets together. And you recently released Towny, which is a very cool AI coding agent. And also just full disclosure, I'm an investor, small investor in Val Town. I think it's awesome. You're doing really, really amazing stuff. And I will also say, you are actually one of the reasons, one of the biggest reasons I started this podcast. Cause you were like, you know, Dan, you write all the time, but I don't have time for that. I want to just listen to what you have to say. And you had sort of a vision for what this could be.

• 2:21Dan Shipper?

  And, and so I really appreciate you pushing me to do it because it's been super fun. And also just an honor to have you on the show.

• 2:29Speaker 00

  Thank you. Yeah. Thanks for, for doing, doing what I want. I think it's important for your audience to know that I started out as an audience member of yours in the first place. That's how we, we met. I stumbled upon Dan's blog when I was a freshman in college and he was a junior at Penn. And I reached out, you know, I should have found that email because we probably still have it. Like the very cute, you know, like I'm, I'm a little freshman, please take pity on me and mentor me. I want to be like you one day. So I, it's wonderful that I've, I've found myself in the content that I was an audience member of.

• 3:06Dan Shipper?

  It is wonderful, wonderful to have you here.

• 3:09Dan Shipper?

  I think, you know, one thing that people should know about you is Val Town is sort of like this, the latest iteration of something that you've been obsessed with for a really long time, which is basically like programming and programming languages and how programming languages change how you think and all that kind of stuff. Do you want to give people like a, just a little bit of a overview of that part of your brain? And where Val Town came from and why it's important to you?

• 3:37Speaker 00

  That'd be great. Uh, yeah, it is a longer history, I think, than most startups. And there are a lot of startups, I think, that look like Val Town today, but like hopefully we have some like deeper historical perspective because of my background. So I think where I'll start the story is I went to this kind of life-changing after-school program. The top me had a code when I was in middle school and I like threw that program, like fell in love with mathematics and fell in love with programming and overall just like felt like a smarter human. And I knew it had something to do with this coding program. And then in college I went to a hackathon, uh, which was a, you know, a whole nother eye-opening kind of experience. But one of the things that happened at that hackathon.

• 4:22Speaker 00

  Was that I was pointing out the work of Brad Victor and Seymour Papert? And I read Seymour Papert. And it like turns out that it was all on purpose.

• 4:31Dan Shipper?

  Who is that? I've actually, I know Brad Victor, but I don't know Seymour Papert.

• 4:36Speaker 00

  Yeah, yeah. So Seymour Papert was a mathematician and a like educational theorist. So he studied, he was like a mathematician who then decided to study with Jean Piaget, like one of the fathers of like the stages of development kind of educational theories. And Seymour Papert had this question, which is like, why are some kids bad at math? But no kids are bad at French. Like if you're, if you're bad at French, it's because you didn't grow up in France. But we know that if you grew up in France, you'd speak French just fine. Like some kids are just genetically bad at math. That doesn't, that didn't make sense to him. He, his conviction was that those kids who seem like they're bad at math genetically just didn't grow up in math land, grow up in a math land.

• 5:19Speaker 00

  And kids who are good at math had some sort of math land experience growing up. And, and his experience was like that. He got obsessed with gears growing up and other mathematical objects that were just in his house.

• 5:30Dan Shipper?

  Got it. Okay, cool. So that, that makes a lot of sense. So continue, so, so continue with, yeah, continue with the story.

• 5:36Speaker 00

  Yeah. So he wanted to see if, can we make kids good at math? Can we make a virtual math land on this new computer thing to make kids good at math? And what he came up with was actually a programming language, but it was never to teach kids to code. There were no jobs for coding back in the sixties and seventies. It was like, can we trick kids into being good at math through programming? And it totally worked for me. And so ever since I lived it and then read about how it was all on purpose, it totally blew my mind that I became obsessed with the power of programming languages, programming environments, developer tools for, for not only the power that they give human beings to like create stuff, but the way that they change the way you think and like actually make you a smarter human in other aspects of your life. This is, this has been the thread. So like that moment when I was like 18 years old

• 6:21Speaker 00

  has followed me for the last 10 years.

• 6:23Dan Shipper?

  How do they change how you think?

• 6:24Speaker 00

  Great question. So yeah, the book Mindstorms kind of goes through this. One of my favorite examples is.

• 6:32Speaker 00

  In in logo geometry, the way that the logo turtle works. So so the programming language Timo Papert made was called Logo. It's the predecessor to Scratch. So if you've ever used Scratch, it was made by his student, and there are a lot of similarities. And in both programming languages, the the model is that you have like a character on the screen, and you can give it instructions to to move forward, or turn and move, and turn and move. And then, in particular with the Logo turtle, you would have a pen on your feet. So you could say, put the pen down, and then give it instructions on how to move, and then pick the pen up, and then there'd be a shape on the screen. So, an example of how like, I learned mathematical concepts. I grew up in Mathland through this, is that, like, how do you draw a square? How do you draw a hexagon? How do you draw

• 7:16Speaker 00

  a circle? Like, you you you build up, as you kind of intuit how to do these things, you build up an intuition for what later in in life you'll learn as like a derivative in mathematics. So, like, I don't know, five years after I like was was drawing circles with my feet, you know, mentally, you learn to anthropomorphize the problem. So that's a technique you can use in a lot of problems, like putting yourself into the code, like, imagine yourself. Okay, so if I was like this, like programmers do that all the time. So you anthropomorphize the code. In this specific example, like, it's very geometric. So then, a couple years later, when I was learning derivatives, I was like, oh, the derivative is just the way you're pointing if you're like walking along the curve. That's very easy. Like, I've walked on curves for a long time. And I remember in the class,

• 8:00Speaker 00

  everyone, like, I was like tutoring kids after that class, and everyone was like, oh, my God, Steve's a genius. He got it so fast. I was like, helping the teacher on the board. But I knew, I wasn't born this way. Like, I was just, I had these, like, very powerful experiences that nobody else in the class had.

• 8:12Dan Shipper?

  That's really interesting. So, like, let me make sure I understand, like, the example you just gave. So basically, if you're programming in this environment, and you're you're trying to make a circle, the way that you end up having to do that is by breaking the circle into like, small little segments that are like, the angle of the segment changes just a little bit each time, so that you end up making a circle, because like, circles aren't like, actually round, like, they're made of infinitely small segments. And that is, that's what then becomes a derivative. And so the the like, concept of derivative was like intuitive to you because of that?

• 8:47Speaker 00

  Yes, yes. It was so easy for me to put myself on the paper, like, my feet are on the paper, and I'm walking along the curves.

• 8:54Dan Shipper?

  That makes sense. I mean, I think it's such an interesting, um, this is a whole rabbit hole we can go down. But like, one of the really interesting things about the history of math is like, it's only in the, I think, like, the 19th century that we start to get, um, formalism in math, where you're using like, all the equations and stuff that get people intimidated. Like, if you read, like, Newton or Galileo, like, they're kind of, they're interspersing, like, geometry with, uh, like, actual written text. Like, there's a lot more of a, it's like where the sort of Renaissance man idea is, is like, comes from. Like, there's a lot more of an integration between all the different, um, senses and ways of thinking to help you understand math.

• 9:37Dan Shipper?

  Um, and it was only, like, later on that we sort of like formalized it, which is helpful, because it's like, the formalism is really powerful, but you end up losing a lot of the intuition unless you're like a super math genius, or you're lucky enough to, to use, um, a programming environment like this. And I think that's what makes people, um, ma- makes it much harder and less appealing for people, which is interesting. I will also say, though, like, uh, as someone who, like, I taught myself how to code, I'm still terrible at math. I think there's something, i- it's possible I haven't learned right, but like, there's something for me about, and this shows up in other areas of my life, too.

• 10:14Dan Shipper?

  There's something for me about, like, just sequential processing, processing like sequences where each step of the sequence depends on the previous step. I'm very likely to, A, it costs me a lot to do that, and B, I'm very likely to, um, skip a step or get them in the wrong order, or like, do all that kind of stuff. So, any math that I can do that's like more intuitive, where I'm like, almost sizing things, um, in my head, as opposed to like following a sequence of steps, um, that I can do. But the sequence thing, like, really messes me up. And, um, that's why I kind of like the AI stuff, because like, I kind of get things intuitively, so I kind of know what I want to do.

• 10:58Dan Shipper?

  And the AI stuff just like, figures out how to write the code, or like, you know, do things step by step, so I don't have to, I, it like fills in that part of my brain.

• 11:07Speaker 00

  Totally. Yeah, yeah. It makes a lot of sense.

• 11:09Dan Shipper?

  Yeah. So, you're thinking a lot about the future programming. That's, that's kind of what you're building at Valtown.

• 11:15Dan Shipper?

  And I, I think like a really interesting, um, intro to this episode is-

• 11:21Dan Shipper?

  About a year ago, when this podcast was first starting, I had this guy Jeffrey Liton, who I know is a friend of yours and also someone that you really look up to and respect. And the cool thing about that episode with him is like, we live coded an app together using ChatGPT and Replit. And at the time, that was like, pretty new and like, pretty cool. And it was like, kind of, to me, it was like, wild that you could make an app on a podcast, like, just like, while talking, like, that was previously, like, totally impossible. But it took us, like, about an hour-ish to actually do it. And there was, like, false starts and whatever. So like, we got it done, but like, it was not super

• 12:05Dan Shipper?

  easy. And I think it would be fun to see how far we've progressed. That was your prompt for me in this episode, is to see the difference between last year with Jeffrey Lit, about a year ago, and where we are now, as a benchmark of AI progress. And I think you're going to use Towny, which is Val Town's chatbot product, to do this. Do you want to introduce it for people?

• 12:33Speaker 00

  Yeah, sounds great. So yeah, Val Town is a website to write code and share code and deploy code, very importantly. And one way to think about Towny is like, it's taking what Dan and Jeffrey did a year ago, and just automating the steps. Like, we were seeing people doing this with Val Town for like, the last year. They would go to like, an LLM and ask for some code, then paste it, and then get some error and paste it back. And it was a crazy thing. And it seems like over the last year, we've all agreed that that's crazy, and that they should be deeply integrated into a single product. And that's what Towny is. We've worked through a number of different iterations of how Towny works. The current iteration, I think, is most similar to Anthropic Artifacts, if your audience is familiar with that.

• 13:17Dan Shipper?

  Definitely.

• 13:18Speaker 00

  I think maybe let's start with just like, the Val Town homepage, so people can get a sense for like, what the product is. I read everyone the poem, but I think I could start with like, the description I give people when I meet them, like, on On the street and they say, what do you do? I say that I make a website for programmers to make websites. I think that like kind of anchors it really well that it's a it's a tool really designed for programmers. And it's designed for you to make web things, particularly server side where you can do front end and full stack stuff. And I think one of the most important distinctions is that it's in the browser, you write the code. And then it also scales with you to deploy and scale. So you don't have to then redeploy it somewhere else. So it's like all integrated and drastically simplifies the programming experience.

• 14:03Dan Shipper?

  Yeah, cool.

• 14:05Speaker 00

  Okay, great. So this is townie where we can describe in English what we want to build. I'm going to paste in and start running the app that you and Jeffrey made. And like as it's coding, I'll describe what's going on. So we're making an app for this very podcast we're on. The idea from your episode with Jeffrey was that it's a kind of throw throw away software disposable software. It's just so cheap to make software that we can make an app for this podcast and then never use it again. So there are three parts. One's a timer, another one is for notes. And then the last one is a like a chat GPT integration where it'll read the notes and then generate more questions.

• 14:46Dan Shipper?

  And I'm laughing because it finished the app before you were done describing what the app was to me.

• 14:54Dan Shipper?

  That's actually super cool. I love this.

• 14:59Dan Shipper?

  Man, I haven't had one of those like real AI wow moments in a while. I feel like I'm getting getting a little jaded, but that was definitely a wow.

• 15:08Dan Shipper?

  Because, you know, yeah, we made this app with Jeffrey a year ago. It took us about an hour and this and there was a lot of copy pasting back and forth or, you know, whatever. And you just like made it with just like pasting and a description of of what we did in the episode. And it's just like here and it works. Wait, can you can you make sure all the stuff works? Like, what's the generate? Does it generate questions button work?

• 15:30Speaker 00

  Yeah, yeah, so I'm talking to Dan Shipper. Or I guess I'm Dan Shipper talking to.

• 15:40Speaker 00

  Founder of Valtown, fast platform for, I don't know, whatever, whatever, that's fine. Generate questions.

• 15:49Dan Shipper?

  So you typed into the interview notes, we have this whole podcast set up, you typed into the interview notes, I'm Dan Shipper, talking to Steve Kraus, founder of Valtown. And then you press generate question and then it generated, it used GPT-4, I assume, some, some AI model to generate questions and it says like, you know, here are three questions to ask as a founder of Valtown. What was the original vision? So like, it's actually, they're, you know, reasonable, reasonable questions. It's not, not like totally off. And what's really interesting about this is like, so, you know, obviously we just saw the whole thing just like, was made in, with, with a single prompt, but what's interesting is this requires a client and a server to be working together.

• 16:34Dan Shipper?

  Because like, in order to, I assume in order to have the generate questions button work, it's like, sending it from the client to the server, the server sending it to OpenAI and then OpenAI is sending it back. That's hard. Like that's, there's some, there's some complexity here. So I don't know, it's, it's cool.

• 16:51Speaker 00

  Thank you, thank you.

• 16:54Speaker 00

  Yeah, I can kind of explain any part of it. Maybe you direct me like what you're curious about, or I could just go piece by piece.

• 17:01Dan Shipper?

  Well, I guess like, tell me at a high level, like what is,

• 17:07Dan Shipper?

  how, how does this work and how is it able to fill in all the gaps there? So there's no copy and pasting and, and, and am I right? Does it have a client and a server? Like, how does it all work?

• 17:17Speaker 00

  Okay, great. So from a high level, the way it works is

• 17:23Speaker 00

  we take your prompt and then a, a, a big ass system prompt that explains how Valtown works. And we send that off to Claude 3.5 Sonnet. And I think it's very important to underscore how much of an enabler Claude 3.5 Sonnet is. When you and Jeff were doing this with, I don't know, ChatGPT 3 or 3.5 or four, or even the current ChatGPT models, we wouldn't get something this good probably, where we'd take a lot longer.

• 17:47Dan Shipper?

  Yeah.

• 17:48Speaker 00

  Yeah, Claude 3.5 Sonnet is like, like what's changed since when you and Jeff did it? Like a big part of it is, we're, it's all integrated in one tool. We spent a lot of time getting a good system prompt and then the most important thing that happened was Claude 3.5 Sonnet.

• 18:02Dan Shipper?

  Right, right. That makes sense. Oh, yeah. Let's look at the system prompt. So like, what are the core components of the system prompt that like, that made it start to work?

• 18:13Speaker 00

  Yeah, there are a lot of iterations. And if you want, if anyone wants a really deep dive, here's like how we built the original prototype, and it's changed a lot since then. And then we have a, we just published a new article about like how, how we're running it in production. So we have a lot of notes for people who want to build their own. But at a high level, how this system prompt works is it explains where the, where the code that we're asking it to write is going to live. We tell it that it's running in Dino JavaScript, not Node JS, not client-side JavaScript. We tell it that it doesn't have to worry about starting the server, deploying the server. We, we give it like all the formatting, all like, like we have random bugs on our platform. We tell it about the bugs, about things it shouldn't do because there are bugs in our platform.

• 18:59Speaker 00

  And then we give it all of the goodies, all the included platform features. So for example, how to do OpenAI, which you're, which we just saw. We, we explain that it's like available to it and here's how to use it.

• 19:15Dan Shipper?

  Hmm. That's really interesting. It's nice. It's nice to have that stuff because it's, that's what I would normally have to paste into, you know, chat GPT or Claude or whatever. So it has the, the most update, up to date docs. I guess like, how has the usage been or like, what have, what have people been doing? Like if you're sort of the underlying thing that gets you excited has been how programming changes the way that people think and what, what they can make, like, what has been the effect of Towny on, on that for you?

• 19:48Speaker 00

  Yeah, it's been fantastic and also a little bit confusing. I didn't expect to have non-programmers be able to use Val Town so soon. Like I, I've, that's been a long-term ambition, but there are people who really don't know anything, the first thing about coding and come onto Val Town and make stuff like this in a minute or two and their mind is blown and they're so excited. And, and that's amazing. I love that. Like, you know, yesterday someone made like, or recently now that Bitcoin is doing so well, people are making like Bitcoin price tractor trackers, wallet things, like all sorts of like analyzers for crypto. And like Val Town is really good at that. It could just plug and play with the APIs.

• 20:31Speaker 00

  Uh, and, and on the one hand, I'm really excited about it. On the other hand, I'm getting questions that are so bad because they're not like it's a, it's a tool for programmers and then I'm getting and then like, you know, like here, I'll just like the, the one I got last night was this, like, you know, let's just say we remove this and say, save it.

• 20:52Dan Shipper?

  And by this, you mean, uh, basically what you did is you, is you went into the code and you were, you removed a semicolon from the, uh, from the JSON object. Um, or I guess it's CSS.

• 21:05Speaker 00

  I removed like a quote of the CSS. Yeah. I just, I, I purposely put a syntax error in the code, a very simple syntax error that like a programmer would have no problem solving. But if you're not a programmer, you're like, this is the worst experience I've ever had in any software ever.

• 21:20Dan Shipper?

  Totally.

• 21:24Dan Shipper?

  Yeah. I mean, like, what are you going to do with that? If it looks so intimidating, like type error, you know? And if you're a programmer, you're like, okay, I can fix that or whatever. Yeah. I think that makes a lot of sense. That's, that's really interesting. So like, what has that been like for you? Cause

• 21:40Dan Shipper?

  I, I've watched you over the last 10 years or so be thinking a lot about the, like, the ways to create a programming language that would be powerful, but also, um, simple enough that people can like, people who are non-technical can like easily sort of like onboard and learn to use it. Um, and it seems like a lot of those sort of language design,

• 22:07Dan Shipper?

  initiatives are just like completely changed by the fact that you can just code with English now. Um, like what is that? What has that been like for you?

• 22:15Speaker 00

  Yeah, it's, it's been very surprising. I didn't expect this would be how things are. On, on the one hand, uh, yeah, like you kind of rethink things from scratch. Like, for example, this type error is totally nonsensical to you and me, but like, "Look, look at this little button here, like, ask Towny to fix it." And then it just sends it to Towny and Towny figured, immediately figured out the issue. And then, like, the only crappy part about this experience is that it's going to regenerate all the code from scratch. But besides that, like, you know, the, the, the example I gave isn't necessarily a condemning thing. Like, you know, they're like, the problem for L L M's is just, or the solution to these

• 23:00Speaker 00

  problems is often just throw more L L M's at it.

• 23:03Dan Shipper?

  So I guess, given that you, like, made this for programmers, and now it seems like you have, like, a whole wave of, like, non-programmers starting to use it, that seems like a big question for, like, the business of, like, who do you want to serve? Like, yeah, what are you thinking?

• 23:18Speaker 00

  I, I'm really tempted to go after people who are non-programmers, because it seems like there's just, like, incredible pent-up demand, and there's just so many of them, and they, they're not served by any other products. And at the same time, I, I really like serving the smartest customers, and, and, like, sophisticated customers, and, like, building a pro tool, it's like, you could think of the difference between, like, Figma and Canva. Are you going, like, kind of a tool for everyone, or are you building a tool for, for professionals? I think, I think that's kind of where I'm drawing the line, and, like, the, the advice I gave to the guy who emailed me about this, this thing right here, like, the first day

• 24:02Speaker 00

  he asked the question, and I solved the problem for him. And then the second day, he asked literally the same exact question. He was like, "What's happening? Why do I have this error again?" And so, my response the second time was, "Here's how I would solve it." I guess where I'm going at for people, I think there's a whole class of people who are allergic to code. They don't even want to look at it, they don't, they don't even want to know it exists, like, totally abstract away from me, and ValTime is not the product for those people. The, the product for those people is Anthropic.

• 24:32Speaker 00

  Anthropic artifacts, cloud artifacts, I think, or GitHub Sparks, maybe. I think there are products for people who don't want to look at the code, but Valentin is not that product.

• 24:40Dan Shipper?

  Yeah, first of all, I think it's really great that you kind of like have a sense for the kind of customer that you like to serve. I think that's actually quite rare and it's and even if you have that sense, it's often like quite hard to allow yourself to like be guided by it. But overall, I think you will make a better product and a better company by like following that because like it sucks to. It sucks to not like your customers or not necessarily even not like them, but like it sucks to.

• 25:09Dan Shipper?

  It's much better to really love your customers and want to interact with them and all that kind of stuff. And and so I think that makes sense. It's funny because I was like kind of while you're answering like my response to this is like. And I know very little about your business, so you know, take this with a grain of salt. But like my feeling is like, I think that there's this new type of programmer emerging. Which is like, I think a lot of people who are. Already really great programmers, some of them are using AI, but a lot of them aren't or they're just like it's, you know, I can go faster just doing it myself. And there's this like new version of programmers who are like.

• 25:51Dan Shipper?

  Really like AI native and and programming with AI is like almost a different skill set than programming without it.

• 26:00Dan Shipper?

  And right now, those people. Look very unsophisticated, but they will be very, very sophisticated in like 10 years. And so the like the the example I would draw is like if you if you were like talking to Mr. Beast like 15 years ago, when he first started making YouTube videos, you'd be like, this guy is dumb. Like he's 12 or whatever. But now he's like one of the most sophisticated filmmakers in the world with like some of the biggest budgets. And so my like my feeling about some of this stuff is like.

• 26:41Dan Shipper?

  If you can, if you reach those people now and grow with them and help kind of instill in them some of the like taste that you've built up and experience you've built up over many years, like there's a, I think that there's just a chance to make a platform for programming that's like sort of like YouTube, but it's for programming, it's for building stuff. And those people are not going to be sophisticated programmers, they're just going to be like kids with dreams.

• 27:08Speaker 00

  I, I would like it to be true that I can, that I can get the future Mr. Beasts in your analogy, who like want to put in the work. To me, that's the distinction. I think there are people who want to turn off their brain and like just use an LLM. And you know what I'm talking about? Like, I don't want to disparage, because I really do believe with you that there's a new kind of AI engineer who's unbelievably powerful. And I love watching those people. And then there's another kind of LLM engineer who will like ask the LLM to do something, and then leave their computer, go do something else, and then come back and see an error and just hit the fix it button, then go and leave and do something else, and come back and hit the fix it button. And they're like allergic to the code. And

• 27:50Speaker 00

  I'm skeptical that those people are going to be, are giving themselves the right feedback loops to become the next Mr. Beast.

• 27:58Dan Shipper?

  Maybe. I mean, I think like, I'll just speak for myself, like, sometimes I do that. Because like, one of the things that I think is, is interesting about these tools, and I've talked about this a couple of times before on the show, is like, right now, programming requires, or pre, pre now, programming requires like a lot of focus and attention. And it still does. But what's really interesting about these tools is, you can actually can like make progress even when you have fractured attention. So like, an example might be, like, I have kids, and like, I get home from work and I want to work on my side project, but like, I need to like, kind of run back and forth between my kids and like, the thing

• 28:40Dan Shipper?

  I'm working on. Or an example is like, I'm a, I'm busy, like, I have a lot of work going on today, but like, you know, for me, I have this idea I want to make, and like, it's kind of fun to be able to like, jump in, like, spend five minutes, like fixing a thing, and then let it go off and do its thing, and come back, you know? And not, that's not to say like, You should get rid of, also get rid of focused work. It's just that like, programming becomes possible in a fractured attention state, which was, it was always possible if you had enough money to hire people. But now everyone can do it, which I think is kind of cool. And I also think like, I don't know, if we extend the YouTube analogy, like, to get one Mr. Beast, you had to have like,

• 29:21Dan Shipper?

  like a hundred million people uploading like just random stuff that like they put no thought into. So, yeah, I think it's, it's, it's kind of interesting, like, I totally, I totally see what you mean. Like you want to build a platform for people who like care. And it also seems like this is, we're at such an early stage of this that like, in order to get those people, you have to like make it so accessible that like tons and tons of people can try it. But maybe I'm, you know, again, you've thought about this way more than I have.

• 29:55Speaker 00

  Yeah. The, uh, I think a big variable that we're like not, that we haven't yet talked about is, what's happening to the underlying models? Like on what time scale? So like Sonnet 3.5 has made all of this, this whole conversation possible. And if we don't have another step change from that in the next year or two, then I think maybe like what I'm talking, like, people are going to be more limited by human focus and care. But if we have like another, if like Sonnet 4 is as big as Sonnet 3.5 was relative, then, then what you're talking about makes a lot more sense. Like beginners are, or could get, get even more leverage. So like the rate is, is gonna, but eventually I think we'll get to a point where,

• 30:39Speaker 00

  where what you were talking about makes a lot more sense. Like, you'll just have agents running off in the background. Like they'll be coming up with ideas, they'll be talking to your customers for you, coming up with ideas to make things better.

• 30:49Speaker 00

  Who knows?

• 30:50Dan Shipper?

  Well, I guess what world are you planning for? Are you planning for a world where like progress is starting to asymptote a bit? Or are you planning for a world where we're going to continue to see like the same kind of jumps in progress that we've been seeing?

• 31:01Speaker 00

  I would like to. Be like neutral to underlying LM changes and be prepared to like if if the LM is the same, then you know, our tool continues to work. And if the LM gets better, in theory, we just like change the model name and we get the benefits like everybody else did. And I think we saw this happen with Cursor and WebSim when three, when Son35 came out, they were ready and they jumped. And so I think now Valten is ready for the next model jump if it happens.

• 31:30Dan Shipper?

  That's really interesting. What um, what have you learned about software development and running software teams in the AI age? Because it's like very different from from programming before. And there's like different sets of ideas and like methodologies and it's all it's all different to have like squishy software. I was talking to Simon Last about this and I I'm curious about like your perspective on it. Like what what has changed for you?

• 31:58Speaker 00

  It for like the the Valten team, like how we're working with like a serious engineering team, serious software versus like software you make in Valten. That's like a lot squishier. Yeah. So right now, there's such a huge gulf. Like when you write code in Valten, you have to get so much software configured on your computer. And like every week or two, you have to make a tweak to that. And so like I am the one person on the team who doesn't have that setup on my like, I can't make that change to our production app because it's just like too much to to keep that local software up to date with the team. So you make your change locally, you get all your databases, everything running locally.

• 32:40Speaker 00

  You have to do automated testing. It's like there's just so much paperwork. It's really important stuff to keep our service running smoothly. Pull it used to be a pull request. You get like a review on the pull request. You do feedback. You deploy it. Deploying takes 10 minutes. It's it's like much slower. And yeah, it's a totally different feel than Valten where every save is a deploy. And it happened in 15 milliseconds and you're you're alive. You're you're off into the races.

• 33:07Dan Shipper?

  Right. I guess what I'm saying is like, um, doing the programming and ensuring a quality product and running tests and all that kind of stuff is.

• 33:17Dan Shipper?

  It's significantly different when the code you're running is deterministic versus stochastic. Um, and I'm curious how that has unfolded for you or what you're learning about like keeping an LLM app running well in production.

• 33:33Speaker 00

  Hmm, got it, got it. Yeah.

• 33:37Speaker 00

  It, I, like, the word there is evals. Like, that's like the, how we as an industry have gotten some amount of predictability or can, or understandability about our, how LLMs are performing. We didn't have real evals for the first like three, four months of Towny. And we were just like YOLO changes and like we would like make a change. We tested out ourselves a bunch. We deployed to production and then like it ended down, it totally seemed better. And then like we get anecdotal reports that it's worse. And we wouldn't really know. And then we would YOLO another change and it was

• 34:20Speaker 00

  the, these things, I, like, I feel like it really brings you face to face in contact with what a, like a truly stochastic thing is like. Because we've given multiple times when I go to Twitter and say like, our users are all reporting X. And like, is that, does anyone else see X? Like, has the model gotten stupider? Has the model gotten smarter? Is the model doing this for other people? Or is it just Bell Town? And then, um, like there'll be, I, I, I feel like I was part of, I don't know if you saw this on, on Twitter. Uh, there was like a couple of months ago, this like weird panic where everyone was like Claude three five sign has gotten this dumber this weekend. And like everyone in Anthropic was trying to figure it out. And I think at the end of it all, it was just a panic that people like me helped contribute to.

• 35:00Speaker 00

  We were, where we all just tried to, we all just kind of convinced each other was super smart and then had a couple of bad it, it, like interactions with it. And then there was a panic that it was dumb. It's really hard to reason about these things. And that's why evals was, I feel like evals are important for your mental health.

• 35:15Dan Shipper?

  Yeah, that's really interesting. I hadn't even thought about the like social contagion aspect of like the perception of quality, you know? Um, that's wild. That, that's so, I mean, I guess it's like, you can draw analogies to like the stock market. Um, but your product quality being like the stock market is like a very new, it's a new thing.

• 35:40Speaker 00

  Very new. Yeah, yeah. And yeah, so like. But evals let you kind of like point to something and just like feel good about yourself. Because customers come to me all the time and they like complain about a specific thing. And then I can like look at the evals and see if I can find what they're talking about. And if I can't, I could say, I'm sorry, try again one more time. It'll probably work, you know, with confidence.

• 36:05Dan Shipper?

  Yeah, yeah, yeah. Well, I guess then like that sort of runs into the problem of like, then you can only, you only take seriously things that you can like measure or changes that you can measure. Like, how do you think about that? Like, you're starting to only see things where there is an eval for it.

• 36:24Speaker 00

  I think there's a lot we miss. It's like a very squishy product and I think customers or users are constantly having less than optimal experiences. And hopefully that like the tool allows for error correction. Yeah, like all the time, I'll talk to Jackson, our team who does the L M, the eval stuff. And he's like, yeah, we don't even have an eval for that. Like, it's not even like when Claude three five sonnet new showed up. We were so excited to run evals on it. And like the evals weren't any different because like we didn't have any evals that were hard enough. Like it would show up that it got smarter.

• 36:59Dan Shipper?

  Right, right, right, right. That's interesting. Yeah, I definitely, I definitely vibe with that. I think like, for any product that we've made, that I've been the one to start, there are no evals and we just sort of yellowed it for a while.

• 37:16Speaker 00

  The official term, yellowing it.

• 37:18Dan Shipper?

  Yeah, I think that's great. I want to make yellowing happen.

• 37:24Dan Shipper?

  And I think we've just now started to to add evals like to Spiral and we have a couple of internal incubations that are not released yet that definitely have evals. And one thing that's that's been interesting for us is like with Spiral, for example, when you like change the model, we also use the new model to change the default prompt that we use to generate new, new things. But then we didn't want to like go and update the prompt for everyone. So we just like have a thing that's like, do you want to upgrade the Spiral to like the new version of the prompt and people press upgrade, which has been an interesting thing to try.

• 38:01Speaker 00

  That's really cool. We've struggled with that internally where if you.

• 38:06Speaker 00

  We let you edit the system prompt, but then when we push an update to the system prompt, you don't get it.

• 38:13Dan Shipper?

  Yeah, like it's complicated and like if they've changed it like, yeah, what do you do? Do you like diff it or whatever? But I think at least like letting people opt in, like letting people know, hey, there's a new prompt and letting people opt in is like, it seems to work so far. And then you have you basically make a copy of the spiral. So you don't lose anything and then maybe you can go back and forth if you want to.

• 38:37Speaker 00

  Hmm, that's cool. Yeah. So you you put the system prompt is a property of a spiral. Cause right now your system prompt invalidating the property of your account or like of your settings.

• 38:47Dan Shipper?

  Yes, each spiral has its own prompt, basically, because spiral is like effectively a prompt builder, like a fancy fancy prompt builder. So yeah, each one has its own prompt. One question I have for you is you said previously that what you want to be doing is building an application where you're neutral to the rate of progress. And if the progress is to the upside, then it's like a really nice surprise. How do you think about doing that? How do you think about architecting your product and your systems for that?

• 39:19Speaker 00

  Yeah, it's a good question and it's interesting because it just happened. Like we built a system for Sonar 3.5 and then Sonar 3.5 new came out and and Haku came out and in some sense, we're like very well positioned for it. You know, like in like beta flags for us internally, we've been playing around with the different models and they just work. But in practice, we haven't actually deployed them to customers yet. We're working on it now. So I think like a model switcher is like some pretty good infrastructure. Another thing we're building, we recently got a bunch new Tanya users, which has has made it like extremely important to get pricing, like proper usage based pricing in for Tanya,

• 40:02Speaker 00

  because like these things are really expensive and we just haven't taken the time because it's hard to build a whole like new pricing model in place. So like those sorts of infra pieces, like being able to switch models, being able to handle multiple models at a time, add new models in kind of more quickly like you're doing, like when you add a new model, do you have the infrastructure to like tweak the prompt for that model? We don't. Like in practice, that hasn't been great. Like Claude three five sonnet new is doing things. It did a lot of bad stuff. And we had to like tweak the prompt a lot for it. And ultimately, we just rolled back to Claude three five sonnet old. Because we couldn't get the prompting right for the newer model.

• 40:41Dan Shipper?

  Interesting. What about like strategically? Because there's this like, there's this tension here, right? Where like, you're relying on Claude three five sonnet. But also Claude has artifacts and like artifacts is like, there's some overlap with Towny. And same is true for like all these other apps or whatever. And so I think like, one of the games of being a startup is, that's benefiting from AIs is sort of strategically thinking about how to benefit from the gains of these companies without also being eaten by them because they all have consumer or B two B like offerings that are not just API offerings. So yeah, how do you think about that?

• 41:20Speaker 00

  Yeah. Our differentiator has always been that we run back back in compute, like a backend as a service provider. And I think these LM companies don't won't want to run their own functions as a service infrastructure internally. They're going to want to partner with someone and like that's the outsized dream that they partner with us to help them run back and compute for their customers somehow. Yeah, like front end, like even now, like with with their the front end apps that they make. Like, it's pretty crazy that Anthropic, you know, lets you share the actual front end app like all with like you can kind of deploy from within Anthropic.

• 42:05Speaker 00

  But yeah, where are these companies going? Yeah, it's unclear, but I think we're like as safe as one could be in backend, in backend function service infrastructure. I think that's pretty unique.

• 42:18Dan Shipper?

  Yeah, you think that they're not going to build that they're going to partner. And yeah, that's interesting. How are you feeling about things? Like how you've been you've been in this company, I guess it's been like a year and a half ish. You just, I think you just, it has been a year and a half. How long have you been running this?

• 42:32Speaker 00

  Two years.

• 42:33Dan Shipper?

  Two years. You raised around in like February, February, March. Yeah. How are things? How are things feeling? What is what has gone how you expected and what is what has not gone as you expected? And yeah, where are you right now?

• 42:45Speaker 00

  Yeah, I think things have been. Great, like I have done better than expected in some apartments and worse in others.

• 42:55Speaker 00

  We, we just are bringing on like three, so we've been a team of four for like the whole year and we just hired three more people who are starting in January. So like I'm kind of sitting on the edge of my seat, like waiting to see how things, like the team dynamic shifts. Cause that's like, you know, almost doubling.

• 43:17Speaker 00

  In terms of like things are growing well, but not like as fast as I want. And it's like interesting in this space to see like there, there are a lot of competitors who nobody knows about or talks about. And we're like excited to be doing better than them. And then there are crazy success stories that are like taking off to the moon like overnight. And it's, you know, hard to not be one of those. We're like, we're in the middle, we're doing well, we're having steady progress. Like things aren't going as well as they could.

• 43:43Dan Shipper?

  What's an example, like Replit or something?

• 43:46Speaker 00

  Uh, Replit isn't what I had on my mind. Um, like Bolt New just announced that they did like $4 million in revenue in their first four months of existence. So that's like, it's like, wow, amazing. So cool. And then

• 44:02Speaker 00

  like Cursor, I think is another kind of runaway success. Like those are the two that I'd be jealous of. Replit Agents, I think got a lot of hype, but I don't really know people who use it a lot. Did you use it?

• 44:14Dan Shipper?

  Oh, I have not really used it, honestly. Um, I, I used Replit a lot when I was doing my course. Um, I, I like, I had this, you know, how to build an AI chatbot course and it was like amazing for that. Because being able to like set up a project and like have all the code in the project and students could like fork it and then press run and just works was like, it was amazing. But like for my day to day programming stuff, I'm just, I just use Cursor right now. I found that like there were, at least back in the, back when I was using it, this is before Replit Agent, like there was just some frustrating things about it and like, and the AI was like not as good. So I, but I don't have, I don't have an updated opinion on it.

• 44:56Speaker 00

  Yeah, yeah. I think originally and still has product market fit mostly in education. That's like where it shines. So it makes sense that it worked for you in a course setting.

• 45:06Dan Shipper?

  Yeah, I mean, I know that feeling, that kind of like it's going, it's going well, but it's not like blowing up, but it's also not dead and sort of like being, being in the middle can be. It's, I think everyone spends a while in there, you know, it's like, it's called like the trop of sorrow or whatever for a reason. I don't know if he would call it the trop of sorrow because you are like, things are going well, but it's like, it's, it's, uh, sometimes things going well, but not incredible is like harder than like things not going well at all. Cause you can at least just be like, well, I'm not.

• 45:38Speaker 00

  At least you can just be straight sad as opposed to being like.

• 45:41Dan Shipper?

  Yeah.

• 45:43Speaker 00

  Like mostly happy.

• 45:47Dan Shipper?

  Um, yeah, I definitely, I feel like, um, I feel like we're in this like sort of like uptick right now. Um.

• 45:56Speaker 00

  Every or one of your apps?

• 45:59Dan Shipper?

  Every overall. Um, and I would say like, I would say growth is like, like, like the last couple of months have been really good. This month is like, sort of like leveling off a little bit, but I think we'll have a couple more launches in the next couple of weeks that, that will sort of change that. We're not really doing any like paid marketing or whatever. Um, but I, I, it just feels like things are happening, which is really, really fun, but there were years where it was not like that. So I, I feel you. Um, uh, and, and I totally recognized the like sort of team dynamic thing. Like we've, we've grown the team a lot and, um.

• 46:41Speaker 00

  Is this your office?

• 46:43Dan Shipper?

  This is not, I mean, this is the office I work out of, but it's not mine. Uh, you know, you know Jesse Beery, right?

• 46:49Speaker 00

  No.

• 46:50Dan Shipper?

  Um, he's a really good friend of mine. Also went to Penn, uh, IA Ventures. This is the, he's a partner at IA and this is their office and they graciously let, uh, let us work out of here, crash here. Um, uh, until hopefully one day we'll get an office of our own.

• 47:05Speaker 00

  Nice. Have you been to our office in downtown Brooklyn? No. Oh, yes. I, you walked out for one, for once.

• 47:10Dan Shipper?

  We, I walked up, we, we actually launched Sparkle there, if you remember.

• 47:14Speaker 00

  Yeah.

• 47:14Dan Shipper?

  Um, yes, a very auspicious day. Uh, but we were not able to spend that much time together because I was like running around like, like a chicken with my head cut off.

• 47:24Dan Shipper?

  But yeah, I mean, things, things, things always break when you add new people and it's always, it's always fun. How have you thought about like team sizing in the kind of AI age? Like how many people you need to hire and who you need to hire and what that says about like your runway and your budget and all that kind of stuff?

• 47:49Speaker 00

  I haven't really changed my thinking about it because like my role models have always been like Instagram and Notion, like a team of on the order of 10, like it's like anywhere from five to 15, even cursors, like I think like a 15, 20 person team, or it was when it exploded. I think like this like small, dense, but mighty engineering teams have always been attractive to me. And I, I think AI just makes that more, more tractable for us mere mortals to be able to do that. But I don't think it means that I can hire like four instead of seven. I think I

• 48:29Speaker 00

  still need the seven, but like hopefully the four of us will have an easier, sorry, the seven of us will have an easier go of it than without AI.

• 48:38Dan Shipper?

  That makes sense. I agree. Like I, I feel like the last 10 years, there are the examples of the like Instagrams and Notion's a huge team now, but like they, they were pretty small for a while.

• 48:49Speaker 00

  Notion was like six people when they did like database, like in 2019, when I was using Notion, when we were all using Notion, like it was a real company then it was like six people, something crazy.

• 48:58Dan Shipper?

  Yeah, yeah, yeah. But, but I do think like, but there was this whole like movement for like big teams and whatever. And I, I really love having a small team. I think it's super fun. And everyone knows each other and everyone's like friends and like, and it just, it changes things when it's like 40 or 50 or 100, a thousand people in a way that's like, yeah, it's like less personal, but obviously like you can get less done. But now, depending on what you're doing, like you can actually get really far with smaller, smaller team, which sounds just more fun to me.

• 49:34Speaker 00

  Yeah, I don't think a small team is holding, you know, software is one of those things more people don't make it happen any faster. The mythical man of the month and everything like having a really tight context. Like everyone on the team knows what's going on, iterate really fast. Cause like Val Town, what we're doing right now, for example, is adding like creating like a virtual file systems kind of setup. So right now Val Town is so good at writing single file apps. But then you want to break it up into a couple of different files and have the AI just like edit one of them for you while the other ones stay put. But Val Town can't handle that. It's just like we haven't built that infra. But now we're building it and there's no

• 50:22Speaker 00

  like there's no parallelisability of it. Like they're like, they're just like core infra decisions. Like the whole team has to kind of be on board with, and we can't add more people to make it go faster. More people would honestly make it go slower.

• 50:32Dan Shipper?

  Right, right, right. How do you think about like, once you're now you're getting into multi-file edits? Like, how do you think about what the appropriate unit of work is for the AI to do before it comes back? And it's like, I did this. And what does that imply for like, how much in the loop should you be versus not?

• 50:48Speaker 00

  Yeah, yeah. I think for better or for worse, we've set ourselves up to be spectators in this race. And like, we like watch Cursor and Anthropic and, you know, Bolt and whoever like come up with these new UI interaction patterns and AI interaction patterns. And then we take the best ones and we like adopt it. I think that that's what's worked best for us to be like fast copycaters. Cause like our core business is, and like what we want to be best at and like innovate on is like a functions as a service platform. That's like the simplest and fastest, like most pleasurable to use. And then we like layer on these AI features that like other people will innovate for us. So.

• 51:31Dan Shipper?

  That's interesting.

• 51:33Speaker 00

  Yeah, it's weird to be like, cause I feel like my instinct is like, no, no, no, we have to, we have to be the best. We're going to come up with this stuff. But the industry is just moving so fast. If we just wait a month or two, we can see what other people do and copy it.

• 51:48Speaker 00

  That's what we did with Towny. Like Towny was just like, we, we, we, we looked at, uh, before Anthropic Artifacts, Towny was like a tool use thing that looked just like ChatGPT at the time. We were like, just kind of copying ChatGPT. And it was pretty bad. And then Anthropic Artifacts launched and we're like, ah, there we go. That's, that's the correct UI pattern. And now we're like on that. But now we're watching, you know, Cursor invent all these new UI patterns. We're like, ah, yes, those are the ones we want now.

• 52:17Dan Shipper?

  That's interesting. Um, does it like, how does it sit with you? Like, and, and how do you stick to your straight? Like you, it seems you have a very crisp idea of your strategy of like what you want to be best at, right? Which is like, um, backend as a service functions, um, is what you said. And that like strategy was formulated, um, even before all this stuff came out or was like really popular. And it seems like you're getting this pull with Towny from people who like, you know, are maybe not even programmers and maybe don't really understand what backend as a service even is. Um, and so how are you dealing with like,

• 52:58Dan Shipper?

  the like excitement of that and, but also you're able to say like, that's, that's important. Um, but we're going to be sort of fast, fast followers because like the core strategy is this other thing like, yeah, how, how are you thinking about that?

• 53:10Speaker 00

  It's, you know, you really hit the nail on the head. It's, um, uh, in the last week or two, I've had a lot of discussions with our main investor, Dan Levine from Excel. He, he's like a spiritual co-vendor for this company, uh, and like a lot of the core strategy pieces about like what we are and what we aren't come from him. And we had a meeting last week where I was like, kind of showing him like this alternative vision. Like we could pivot from the backend as a strategy to a like full stack app development tool. Like maybe you're like YouTube for programmers vision or like Shopify, kind of a, like a full stack app platform.

• 53:52Speaker 00

  Uh, like Shopify for SaaS apps. You could, is like one idea, like we could rebrand, we could call ourselves SaaSify or something. Um, and like go after like Bolt and like try and get like hundreds of thousands of non-programmers to just be like buying credits and credits and credits, uh, to like make, make apps. Like I think that's a real pivot we could plausibly do. And we can have the database included and like all sorts of other services included. And then we become probably a tool more like Canva where we're like for everyone, we're for we're for everyone and like unsophisticated folks and they're like making apps, you know, like so, you know, kind of like small, medium sized apps, like no serious engineer would would use us.

• 54:38Speaker 00

  And again, I had a long chat about it and the various trade offs, we had a long chat and I wrote this like long strategy document about what our strategy is, what it and very importantly, what it isn't and why we why we're giving it up. And like how we get pigeonholed if we do the other strategy, like one of the big downsides of being like a full stack app is that you have to do the whole stack. And I think it seems simple and it's always seems simple and it's just so much more complicated than everybody thinks. In order to do front end and back end and monitoring and errors and logging and databases and database migrations and database backups. Just like we're talking about like a mature, back to your question from earlier, a mature engineering organization

• 55:23Speaker 00

  has like a dozen or two dozen tools in order to, including like a local text editor and like local version control, like so many, so many tools. And so I want to replace that whole stack of like two dozen tools. It just necessarily has to be a toy version of all of them and like a kind of bad version of all of them. And then that customer is necessarily become like unsophisticated, it it it leads leads to a weird local maxima that we're scared of. And then the alternative is that we do fewer things, but do them really sharply and better. And integrate with all those other things, like we we could become just the functions of service piece for a lot of people.

• 56:05Speaker 00

  And then we can, once that's kind of nailed, we can expand more confidently. While remaining quite good at each thing we do instead of mediocre, all of them.

• 56:14Dan Shipper?

  That makes a ton of sense. What um, what makes you think that that's like the part of the stack that you want to sit in? Like, why choose that one?

• 56:25Speaker 00

  Why backend as a service or yeah, why function as a service? It's a really, really good question. Like in some sense, the most honest answer is that. It's what like Dan Levine thought there was an opportunity for. It's like what our investors had an opportunity for, or it's like what was left. Like Dan's also an investor in Vercel, and they're doing front end, and they're like doing such a good job at front end. And then there's like a backend shape opportunity. So that's, that's like, that's one way to look at it. I've always, like, another way to look at it is I've, like, as long as I've been a programmer, I've really wanted something like this to exist. I've like always hated how complicated backend

• 57:09Speaker 00

  stuff is. And there are like three dozen tools that I've used over the years trying to make my life easier on the backend, and never found one that was good enough. And, and so like wanting it to exist, like, nobody, well, I guess, like, we could, we could talk about who else is in this market. There's like, there's AWS Lambda, which nobody would ever use directly. Like, if you use it like intermediated to all sorts of stuff, it's like, you know, a terrible, terrible user experience compared to normal programming. And then there's CloudFlower Workers, which is actually a wonderful product. And, and I've learned a lot from, from the CloudFlower team. But still, it's, it's, it's not social. It's not GitHub. It's not like collaborative, open source, productive

• 57:54Speaker 00

  coding, like GitHub is. Like, when you make a CloudFlower Worker, it's, it's kind of invisible code, and nobody else can then leverage and use and like and fork. It's not, so it's not an artifact, and it's not a browser-based thing. It's a thing you develop, like a normal engineering artifact.

• 58:12Dan Shipper?

  Yeah, it's like, it's sort of a last generation type thing, like, for, like, people working in more enterprise-y environments where there's like less flexibility and there's, you know, like, yeah, I think, I think that that makes sense. I, I, I just gotta say, like, I think it's awesome that, that you're thinking through these things like so crisply, and you have a really like clean perspective on it, which, I think it's awesome, one, because it like, it's just, that's just rare. And two, like, you're giving yourself the ability to be wrong, which also gives you the ability to be right. Whereas I think it's like, there's a tendency

• 58:56Dan Shipper?

  to like, try to do everything and be everything. So as the man who like, has the studio where you have like five different products or whatever.

• 59:04Speaker 00

  It's literally called every. Trying to do everything.

• 59:10Dan Shipper?

  So, uh, so I, I think I admire that because like, um, I know internally how hard that is for me.

• 59:21Dan Shipper?

  And I, I just really appreciate, um, like getting to hear it and, and that you're willing to share it. Like, I think a lot of people are not, not willing to share it. I think you're just being incredibly honest and I think you have a very clear vision for what you're doing. And I'm just like psyched to see what you do with it, like what happens the next year or two.

• 59:38Speaker 00

  Thank you. Yeah. Me too. I, I think it's, the, the vision's been the same since day one, but it, it's remarkable how many twists and turns there are even saying true to an original vision.

• 59:51Dan Shipper?

  Totally. Um, well, this is awesome. I had a great time. I'm really glad you came on the show. We gotta do it more often. Um, if people want to find you and find Val Town, where can they find you on the internet?

• 1:00:04Speaker 00

  Man, I, I normally say Twitter, but I'm, I'm trying to move off of it these days, uh, vaguely. But yeah, I'm, I'm Steve Kraus, uh, kind of everywhere on the internet and valtowtown is where you can find Val Town.

• 1:00:18Dan Shipper?

  Awesome. Thanks, Steve.

• 1:00:20Speaker 00

  Thanks, Dan.

• 1:00:29Speaker 02

  Oh my gosh, folks, you absolutely positively have to smash that like button and subscribe to AI and I. Why? Because this show is the epitome of awesomeness. It's like finding a treasure chest in your backyard, but instead of gold, it's filled with pure, unadulterated knowledge bombs about chat GPT. Every episode is a roller coaster of emotions, insights and laughter that will leave you on the edge of your seat craving for more. It's not just a show, it's a journey into the future with Dan Shipper as the captain of the spaceship. So do yourself a favor, hit like, smash subscribe and strap in for the ride of your life. And now without any further ado, let me just say, Dan, I'm absolutely hopelessly in love with you.