You Can Build an App With ChatGPT in 60 Minutes

TL;DR: Today we’re releasing a new episode of our podcast How Do You Use ChatGPT? I go in depth with Geoffrey Litt, a researcher at the lab Ink & Switch, on the future of software and AI. As we talk, we build our own app together in 60 minutes using ChatGPT and Replit. Watch on X or YouTube, or listen on Spotify or Apple Podcasts.

Geoffrey Litt wants you to build software—whoever you are. Not just if you’re a seasoned software engineer in San Francisco, but even if you have minimal—or zero—coding knowledge.

He’s a researcher who’s working on creating a future where anyone can make changes to the software they use—what he calls malleable software. I’ve been writing about similar topics—like how AI might turn everyone into a developer and upend SaaS business models—for a while, and it was great to have Geoffrey on the show to discuss our overlapping ideas.

We talked about how ChatGPT enables anyone to build single-use apps and expands the horizon of who gets to build things. We even put our money where our mouth is: As we talked, we built an app together in ChatGPT and Replit.

It was some of the most fun I’ve ever had recording a podcast episode, and if you’re interested at all in the future of software and AI, it’s a must-watch.

Here’s a taste of what we talk about.

Coding is getting easier—and much faster. ChatGPT has the potential to make coding possible for novice coders and make coding drastically easier—or more efficient—for seasoned pros. “A lot of the time it's actually faster now for me to just make the thing that has the tiny features that I need than to go try to Google which one is the best and learn how to use it,” Geoffrey says.
ChatGPT as a muse, not an oracle. Geoffrey wants people to treat ChatGPT like an in-house consultant: “It's like a designer or or an engineer—the earlier you bring them in, the more they can contribute to the ideas and the more context they build up.”
The benefits of a coding plan. Big projects necessitate ample planning. “If I'm going to spend six months on a huge project, I better have a plan when I start,” Geoffrey says. That’s true for ChatGPT, too. Providing a plan helps clue the chatbot into your ambitions.
Don’t waste time reading the code. Geoffrey says if you’re working off ChatGPT code, just run it and see what happens. Don’t bother poring over the code until you know if it works or not. “It's a waste of time,” he says. “I would rather just see what it did and use the thing.”
The future is “modding and mixing.” If software isn’t doing what you need, the answer currently is usually to start from scratch. “Often what I actually would prefer is to start with an app that someone else made that's almost right, but I just need to make a small tweak,” Geoffrey says. With malleable software, he says tinkering could become the new normal.
“Effortless flow.” Building an app together was easy and fun. That’s what we both want coding experiences to be like. “LLM-based tools are sort of on a path to enabling that for way more people in way more situations,” Geoffrey says.

You can check out the episode on Twitter/X, Spotify, Apple Podcasts, or YouTube. Links and timestamps are below:

Watch on X
Watch on YouTube
Listen on Spotify (make sure to follow to help us rank!)
Listen on Apple Podcasts

Timestamps:

Intro 1:03
What is malleable software? 1:36
Who gets to make software on the web 8:06
Deciding what app to build. 14:50
Starting on our app. 22:06
Don’t read the code first. 31:07
Starting from scratch could soon be a thing of the past. 47:55
Getting past those final error messages 55:50
Voila! An app. 1:03:31
Effortless flow. 1:05:50

What do you use ChatGPT for? Have you found any interesting or surprising use cases? We want to hear from you—and we might even interview you. Reply here to talk to me!

Miss an episode? Catch up on my recent conversations with Waymark founder Nathan Labenz, Notion engineer Linus Lee, writer Nat Eliason, and Gumroad CEO Sahil Lavingia and learn how they use ChatGPT.

Transcript

Dan Shipper (00:00:01)

Why don’t we build something together?

Geoffrey Litt (00:00:02)

Alright. Let’s see how it goes. So I'm going to kick us off with my goal, which is, “I'm appearing as a guest on a podcast. I want an app that I can have open while I'm on the show to help me keep track of time and remember what I want to say.” Okay. So we got this code. I'm not going to read it. I just copy, paste and go. I'm just pasting from ChatGPT. This should update live, this little window here.

So it has the time, did the simple dark theme pretty well. I would say it has a box for notes.

Dan Shipper (00:00:33)

This is magic. Like this is crazy.

[Intro sequence]

Dan Shipper (00:00:47)

Geoffrey, welcome to the show.

Geoffrey Litt (00:00:48)

Thanks so much. It's good to be back.

Dan Shipper (00:00:50)

Yeah. Good to have you. I interviewed you, I think two or three years ago on Superorganizers. That interview went really, really well. And, I just think you're one of the deepest thinkers about this stuff. And in the pre-production call, I was just saying like, I think generative AI just sort of, it just takes the things that you've been thinking about to a new level. And I'm just really excited to check in with you.

Geoffrey Litt (00:01:12)

Yes, a lot has changed over the past couple of years.

Dan Shipper (00:01:17)

And for folks that are not familiar with your work, you are a researcher at Ink & Switch, which is an independent research lab, and you explore what you call malleable software, which are computing environments where anyone can mold their own tools to their needs. Can you talk to us about what malleable software is and why that's important?

Geoffrey Litt (00:01:36)

Yeah, absolutely. So this has been a quest that I've been on for at least the last five years now. And it all started, I was working at a startup and we were making SaaS software for schools. And, I just started getting really bummed that we kept saying no to every single request that came our way from some teacher in a classroom.

And they would say, “ can, can you change this word because it doesn't match the way I teach?” Or, “Can you add this little button for me that would do X?” And we would say, “No, we,we’re not going to add that button just for you.” And that's such a normal way of thinking about software for, for people used to SaaS.

Bbut it felt really strange to me. And so I started wondering what if we had a world where everybody could craft software tools that match the workflows they want to have, unique to themselves and not just using these, pre-made tools. That’s what malleable software means to me is that we can all have the software that works for us, not for some product manager off in San Francisco.

And the really interesting thing that's happened the past couple of years is that, until recently programming was a huge bottleneck in this space. You need to do a lot of programming to make any sort of software. And the big question was how can we sort of route around programming to give people tools to make software without doing that?

And what really excites me about generative AI is that, oh my gosh, we now have a thing that can kind of, sometimes turn fuzzy ideas into code. And so that's starting to cut almost like a shortcut through that impassable mountain. And I think it's a really exciting time to be exploring how can we apply that base technology to help everybody make and edit the software that they want to have.

Dan Shipper (00:03:15)

Right. I love that. It's an idea I've been thinking about as well. You're obviously far deeper than I am, but I wrote this article called “What comes after SaaS?” I don't know, probably six months ago. And, the short answer is bespoke apps customized by AI. And, I think for people who are sort of newer to this one, one way to think about it, and I'm curious what you think of this metaphor is like the difference between right now, a lot of the software that you use, it's sort of like…when you use Spotify or Gmail or whatever, it's sort of like staying at a hotel where veryone gets the same hotel room. Andthe company is running the hotel and when you sign up for Gmail or whatever, you get your little Gmail hotel room and it's got all the same things as everybody else.

And there's like some ways that you can customize it. Like obviously you put your luggage in the hotel room, like, so there's certain things that are yours. But. Everything is basically the same, the same basic model, and over time, companies get, especially SaaS companies get good at adding little customizations or whatever, but it's always on their terms.

It's always on their guardrails. And I think your vision of software is a little bit less like these infinitely large hotel rooms that people are staying in and more like everyone owning their own home or something like that. And, either having power tools and the ability to use them, or maybe having their own general contractor on staff that they can, they can deploy to make any change they want.

Geoffrey Litt (00:04:47)

Yeah. I love that analogy. I think it's a really good one too, because it's subtle in that sometimes hotels are fine. And there's a whole spectrum from renting a hotel room to renting an apartment to buying a house that someone else built. There are people also who build their own home from scratch and design it all right. And there's a whole spectrum there and it's okay to, I think at different times be on different points. What I think is really pernicious about the hotel idea though is like, imagine we all lived in hotel rooms all the time. you would probably stop thinking about questions like, “Oh, what would be a better layout?” When I walk into a hotel room, I don't start thinking about moving the walls around or changing the decorations because it's not a thing that I obviously am allowed to do. And so, those questions don't occur to me. And that's what I worry about with software, the worst case outcome is that we all use SaaS tools that subtly affect the way we think. And we don't even realize it because we're just so used to living in those tools.

Dan Shipper (00:05:43)

Yeah. I was just talking to a couple of weeks ago—I was talking to Linus Lee on this show, and he was talking about something similar, which is, the idea of agency and how our tools shape the agency that we have, and, and thinking about ways to give users more agency in the context of general AI, where I think, in large part for now, there's maybe a little bit less agency in something like using Midjourney than you might get in something like using Photoshop because you can like literally, with Midjourney, you can prompt it, but in Photoshop, you can literally change the pixels and, so figuring out ways to give people finer-grained control, it's a really interesting challenge in generative AI.

Geoffrey Litt (00:06:26)

Yeah, absolutely, and I think one really important point here is that there's a lot of different dimensions of how people gain agency.

And some of them are things surrounding the AI and are not core to the AI itself. So one, one, example following on with the hotel analogy, right. As you said,maybe everybody has a general contracting team that they can bring to their hotel room. If you show up at a hotel with a construction crew, they're not going to let you tear down your room and rebuild it. There's like a sort of social agreement or legal framework or whatever around, your contract with that entity, where it's not really like your ability to move walls physically, that is the constraint. And so, to bring that back to software, what I think about a lot is, if I had a personal team of 100 developers that were working for me, what could I do with that power and, let's say I'm using Spotify and I'm like, “Oh, I hate the way that Spotify shows me these playlists. I wish that it showed me that in a different way.” I can’t edit the Spotify app. I don't have control over that and so, what I'm thinking about a lot these days is how can we reorient the way software is distributed and constructed so that my, so to speak, personal dev team can actually do useful stuff for me.

And, for example, maybe they could make browser extensions for me, or maybe they could, if my software is open source and I control it, maybe they could start adding features for me. How can we change the foundations of software in a way that is best positioned to take advantage of the fact that everybody is going to have this power available to them in the coming years?

Dan Shipper (00:08:06)

Yeah. No, that makes total sense. And it's just making me think of … I teach this course called “How to build an AI chatbot” and one of the really incredible things about this course is we take people from not really being able to code to shipping an app in 30 days. And, it's really cool because I feel like there are all these people out there who are just waking up to the idea that they have these magical powers where they can literally now build stuff in a way that they couldn't before.

And a lot of these people are like, okay, it's a product manager who you work with engineers and you've maybe you took one coding class in college, but you've never felt confident enough to actually go build and ship a React app or whatever. And what all they really need is like a little push to be like, okay, just use ChatGPT, ask it what to do. Here's some sample code and like go. And it really changes things for people where on day one, they can have a working chatbot with a couple prompts and that's like a big, “holy shit, I cannot believe that I can actually make something.” And then what it does is it motivates them to try to learn the underlying fundamentals in this way that's like very connected to practice, as opposed to the way that you used to have to learn programming, which is like, you spend six months like learning about loops and if statements and like all this stuff, and you're like, “I have no idea how this connects to like the things I want to make.”

And so I just think that there's this really, quickly expanding horizon of who gets to make things in the world and there are a lot of people who are within the horizon of being able to make stuff that don't know it yet, but all they literally have to do is sit down with ChatGPT. And that horizon is going to be significantly larger in five years. And I think that's one of the things that you're working on. And I think it's so exciting.

Geoffrey Litt (00:10:05)

I love that way of thinking about it. For me, the way that I learn best has always been to make first and then figure out what I'm doing second. And I think people often end up in these dumb debates that are like, “people should be able to make stuff without learning the fundamentals.” And then other people are like, “it's really important to learn the fundamentals.” And my take is yes, it's important if you want to go really far at some point, you're going to have to dig deep and actually learn what you're doing. And that's going to propel you. But, that shouldn't be a barrier to you doing anything. And so in my career, I got started in web development, just throwing together Rails apps. And I didn't really know how to program. I didn't know Ruby. I was just sort of copy-pasting and messing around and I fought through the pain just cause I wanted to make and share stuff. And I think you're, you're exactly right that the flip that I see when people start using ChatGPT is all of these frustrating moments that before took incredible dedication to fight through because they were so frustrating and programming is full of these absolutely full of these things—you're missing a semicolon and it takes you three hours to realize that that's why your thing wasn't working. That's so demoralizing and People who don't have access to a friend or tutor who can help with them with that. There's just a huge drop-off chance, I think, at that point. And when I'm using ChatGPT, even now, I'm a skilled programmer, but I'm often working in areas that I don't know as well. Having ChatGPT with me just feels like the default flips to, I have flow, I have momentum, and I have this, this sort of support that's going to make sure everything goes okay. And I'm just less worried about getting stuck. And I think that that feeling is really qualitatively different. And I agree when people realize that it's a really exciting flip for them.

Dan Shipper (00:11:47)

Yeah, it really is. So I think that that sort of brings us to,the, the main thing that we wanted to do today, which is… In most of these episodes, what we're doing is we're going through historical chats and then, and then we both kind of interact with ChatGPT and we explore something and find things that we never would have found before.

And what you suggested, which I think is brilliant, is why don't we just build something together? Why don't we build an app? And I think in the process of building an app, people will be able to get just a little bit of an idea of what you mean by malleable software, what this future of being able to modify things is going to look like.

And then two is they're going to be able to see what are the specific ways that you're using ChatGPT to achieve these results, in just a very, very detailed way. And we'll try to make it so that if you're a programmer, you can get a lot out of it. And if you're not a programmer, you'll be able to understand what's going on and you'll be able to see it, get a little bit of a taste of what would it be like to push myself in this way a little bit and try to build stuff. And I think it'll be really cool.

Geoffrey Litt (00:12:47)

Yeah, I'm excited to try it out. And maybe just as a preamble, I can talk a bit about how I think about this task that we're going to do. Right? So,what I've been trying to do in my work is, sometimes there'll be a brief moment when I'm in the middle of something and I have this thought that's like, “Oh, I wish I just had a software tool that did X.” And, again, this is getting out of the hotel mindset. And I've been trying to notice those moments and, and think, “Wait, like, could I actually make that?” And, before maybe that would have taken a day. So the answer is like, “No, not worth it.” But now if the answer is like “Five minutes,” maybe, right?

And so I've been trying to notice those moments and, I've come up with a workflow that's very, very simple and crude, but has worked for me a few times for making these sort of quick apps that help me with stuff. One small example of one that I built before, is I was prepping for a trip to Japan and I actually grew up in Japan and I speak somewhat fluent Japanese. But I have some sort of pockets of missing skill, particularly in more formal communication. And I was on these text message threads with some of my mom's acquaintances who I don't know as well. I mean, I needed to sort of text them in a way that was correct to the context, and I was just struggling.

And I was doing all these ChatGPT chats to try to help me with the translation. And it was really helpful, but I kept hitting these really annoying Chatsituations where I would be like, “That sounds too formal. Make it sound a little more casual.” “Oh, like that sounds too casual. Make it sound a little more formal.” And so what I did in the end is I made this, this UI tool that, you can do a translation and then there's a little slider to adjust how formal the translation should be. And that was just way more, way easier, way more fun. And it sort of encapsulated a lot of the wisdom of the system prompt I had been iterating on in a nice GUI tool that I could then just whip open whenever I wanted.

And so that's sort of what I mean when I talk about these little helpful software tools that I wish existed just for me. Right. And so that's I think the kind of thing that would be fun to try to, to build together.

Dan Shipper (00:14:50)

Okay, cool. Well, let's find it. Let's find a tool to make, I know you have some ideas. I've got some ideas. Why don't you start and we'll just kind of go back and forth until we find something we like.

Geoffrey Litt (00:14:59)

Yeah. So, one idea I had was I'm a guest on your podcast right now. And so what's like a utility that I would want to have while I'm a guest on your podcast, and I could imagine, maybe there's like a time bar that kind of shows me like, how are we doing on time? And so I have an ambient awareness of pacing sort of like, you can imagine it's like keynote presenter mode, but specialized to being a guest on your show. Maybe there's a checklist of like topics we want to, I want to make sure I hit with you and I can check them off. So I have this aid. I don't know if there's stuff, maybe as a host, do you have ideas for what you might want?

Dan Shipper (00:15:36)

Yeah, let's ideate a little bit because I think you're, you're onto something, this podcast is sort of unique in that ChatGPT is its own, like it's a, it's a guest and insert in certain ways or it's a part of it. And I really love to bring it in even more where like, for example, one thing that I think would be really useful, I often find myself wishing that we had a live transcription that could then get easily fed into ChatGPT and have ChatGPT respond to what's being said, and, I don't know if you feel equipped to do that or if that would take too long, but something like that would be really helpful, because I'm often sort of, as we're talking, I'm often writing stuff into ChatGPT and then being like, “This is what they said, like, what do you think?” basically. And if there was an easier way to do that, that would be really helpful. I think one of the constraints is. It would work if it was its own interface. It would be even better if it was inside of ChatGPT somehow. That's probably going to be really hard to do, but just sort of thinking, maybe the minimal thing is like real-time transcription. That's really easy to either get into ChatGPT or to just have GPT give some sample questions or some thoughts like in real time as things are happening that could help push us in new and interesting directions.

Geoffrey Litt (00:17:09)

Okay. So two thoughts, first of all, at a meta level, we should get ChatGPT in on this brainstorming session in a second, because one really important thing is that the moment for Chat to get involved is not like when the idea is fully formed. This is a huge part of my philosophy on this stuff is that ChatGPT is a muse, not an oracle. So it's not like we will craft the perfect app pitch and then bring it to ChatGPT. And then in one shot, it will generate the perfect app and then we're done. It's like a designer or or an engineer: the earlier you bring them in, the more they can contribute to the ideas and the more context they build up.

And so, we should do that. Second brief thought is, this is actually getting to one of the hardest parts of this process that I think least-well served by ChatGPT currently, which is you asked me, “Could we like do this? How hard would it be?” And, I'm a programmer. And so I have a lot of context in my head for helping to assess very quickly, like on a scale of 1-to-10, how feasible is what you're thinking of and, I think one of the biggest challenges that Chat isn't as good at yet is helping people who aren't programmers figure out how hard is this going to be? Is it even possible? And so when I build these apps for myself, currently there's a lot of that background knowledge I have feeding into the process and helping it along. And so one thing I'm excited to explore in the future is, can we make these tools better at basically telling you, “Actually, Dan, that's not a good idea. I get it. It would be cool, but it's just going to be too much work. How about, let's try this other thing instead. That's what senior engineers do, right? So, That's the process going on right now in my head.

Dan Shipper (00:18:53)

I think you're totally right. And it's something that I see in my course as well. People just go into these… people get grand visions, they have these big ideas, right? And that's what motivates people to build stuff. And I'm constantly sort of like being, “Okay, your practice is to figure out what is the core smallest thing you can do and just do that. And, and use that as a stepping stone to build the more complicated thing later.” But the big failure mode for people is they try to do something way too big at the beginning. And then, and then they're like, “Well, this isn't going to work” or whatever. And they just get lost in this rabbit hole and finding, finding that little small thing that's useful to start, even if it's not your big vision is like the best way to build stuff.

Geoffrey Litt (00:19:33)

And it's classic lean startup sort of iterative agile thinking. And the really cool thing is Chat can lower those iteration cycles so much. So, I was prototyping a game at a hackathon earlier this year and I was just trying to have fun at this hackathon. I wasn't trying to work hard and I wanted to prototype different ways the game could feel. And so I would just say to Chat, what if it, “What if the car moved this way?” And then I'll go off and talk to people, and come back five minutes later. I have a new game. I play it. And I'm like, “Oh that, that sucks. Let's do this other way.” And so I think, it's doubly important when using ChatGPT to realize the superpower you have now is that iterations are fast. It's not that Chat always has the right answer. It's that getting a new alternative is much faster. And so your goal as a person driving it is to take advantage of that, iterate really quickly and try a bunch of stuff really fast and then respond to it yourself and sort of see where it goes. So I think we should try that. One thing we could try is just starting with a very minimally scoped app that has like a clock on it or something. And then we'll see that working and sort of like, we'll have more ideas riffing on that and sort of we'll just go from there or something.

Dan Shipper (00:20:48)

Let's do it. I love it. Okay, let's do it. So here we are. We're in Chat. And we're going to get started coding this little app. And I want to point out, I got super excited about this whole real time transcription thing and I think you're kind of like, “That's probably a little too big to do live in—I don't know—we have like 30 or 40 minutes.” So I think that's just, that's just such a really important thing to note is that this happens all the time in programming. It's a normal thing to be like, I've got this amazing thing.

And then to be like, “No, no, we got it. We got to pare it back to like something that's useful that we can do in the time we have. And then we can add more later.”

Geoffrey Litt (00:21:28)

Yes. And so I think we should start with a super small thing and expand out from there. And that's something that, by the way … What I'm always thinking about with my system prompts for Chat and tools around this stuff long term is people don't just need help programming. They need help with product management and scoping and coming up with the right ideas to solve the problem and design. And ChatGPT can help with all that stuff too. And that's really important to remember.

Dan Shipper (00:21:56)

So lead us off. So how are we going to get started? What are we trying to build? Or maybe like, maybe the first step is trying to figure out what we're building with ChatGPT. Tell us how to get started.

Geoffrey Litt (00:22:06)

Okay, so we're just going to use this custom GPT. I actually just threw this together and put in a system prompt that I like. Maybe I'll show that before we get started using it. So you get a bit of behind the scenes. So here's what this bot basically does. It's a helpful AI coding assistant. Make sure to follow the user's instructions precisely because coding is a domain where sort of details matter. And I give it essentially a very specific opinionated stack for the code it's going to output.

React, TypeScript, Tailwind. This is a very popular set of technologies. It's one that I have a pre existing template for in Replit, which is this online coding platform. And I tell it, generate all the code in a single file. So basically, it's going to give us some code. And as we'll see, we'll just be able to copy-paste it into Replit and see what it does. So this is really important to constrain what it's doing in a particular technical way to get an output that we can work with easily. I'll note by the way, copy-pasting code from ChatGPT to other IDEs is not the best workflow in the world. It's obviously not how these tools should work in the future. Just a duct taped-together way that you can do it right now that I like to use for quick experimentation.

Now let's talk a bit about the workflow. So, I think this might be the most important part of the prompt, so you get an initial idea from the user question two is, or part two is absolutely critical. Ask the user for clarification on parts of their idea that are underspecified. So we'll see this play out in a second: We're going to ask it to make an app and our idea is going to be vague. And what we don't want is for Chat to just run ahead and make up a bunch of stuff and guess what we mean.

We want to be in a conversation where it's going to ask us for help and clarification, and we're going to clarify what we mean together. Then once ambiguities are resolved, we're going to proceed, we'll make a plan for how the code is going to work first. That helps to generate correct code, and then it's going to write the code. Okay, so that's the basis.

Dan Shipper (00:24:16)

That's really good. So I'm curious, how well in your experience is this? How good is this at following this workflow once you have it in your custom instructions for this GPT?

Geoffrey Litt (00:24:28)

I've done a bunch of iterations on this prompt over time. My experience has been that asking clarifying questions—it's really good at that. I'm always amazed at how helpful its clarifying questions are. The hardest task that it's not so good at is knowing when to ask you to clarify something or whether to just fill it in itself. I try to resolve that by saying if there's some minor ambiguities, just make assumptions about what the user means and tell the user how you're filling them in. But sometimes it'll just barge ahead too quickly and other times it'll be too conservative and asking for too much input from me. It's like if you're an employee and you have a. a manager and you're trying to figure out what are the things I need to ask them about versus I can just go do myself. It's that dynamic, right?

Dan Shipper (00:25:17)

That makes sense. I'm super curious to see how this goes.

Geoffrey Litt (00:25:20)

Alright, let's see how it goes. So, I'm going to kick us off with my goal, which is, I'm going to say, “I'm appearing as a guest on a podcast. I want an app that I can have open while I'm on the show to help me keep track of time and remember what I want to say.

Okay, so, great. We're getting clarifications live and I'm starting to read them and think through my answers, right? So time-tracking. Maybe I'll just keep going and answer these questions. Okay. Thanks. Okay, great. So we got answers. let's go through one by one and, I'm going to think through my answers to these questions.

So first, time-tracking, it's saying, do I need a simple stopwatch or a countdown timer? So I'm just going to say, I want a progress bar. Or I'll say digital clock plus progress bar. going from 9:00 a.m. to 10:30 a.m. Now, one really neat thing is we don't need the app to have a place to set the time start and end because it's an app literally just for this one appearance on this show and I'm with you today this morning from 9 to 10:30 a.m.

So that's going to be hard-coded into the app, right? That's part of the ephemeral software. We don't need extra stuff. Preload notes or add and edit notes during the podcast. I guess preloading is fine. And by the way, I'm using—

Dan Shipper (00:26:57)

We have a Notion link with notes. It'd be cool if it could display that.

Geoffrey Litt (00:27:02)

Oh yeah. Should it be able to show the Notion link? Or do you copy-paste in markdown from the Notion? What do you think?

Dan Shipper (00:27:09)

I mean, ideally it shows the notion, it shows the Notion like in an iframe or something.

Geoffrey Litt (00:27:14)

Okay. So, it's funny. You just used the word iframe, so that revealed that you are thinking on the technical side of this too, right? And I think we might want to linger there for a second. And this is another instance of what I said earlier, where having background knowledge about programming is a huge accelerant to this process right now. And the reality is, this workflow we're doing, in my experience, doesn't work that well for people who have zero programming experience yet. I want to build tools that help get us there in the future, but it's interesting.

So let's say we have our notes in Notion. Maybe we could show those, embed those somehow, or copy-paste them. I'll let Chat sort of make a call on how to sort of proceed with that. Styling or layout preferences? I like giving it a vibe here. One vibe I had in my mind is I kind of like the Keynote presenter mode. So I could just say like “simple, dark keynote presenter mode, vibes,”

Dan Shipper (00:28:27)

I like that. Cause I feel like when you give it vibe, it kind of knows to be fuzzy about it rather than like very direct.

Geoffrey Litt (00:28:32)

Yeah, for sure. By the way, quick meta note, I'm using the numbers here, which is just a great shortcut for responding directly to each of the things without too much time,

Dan Shipper (00:28:42)