How a solo founder used Codex and ChatGPT to launch a fashion brand without engineers | Yana Welinder

Speaker A: Normally I would hire a technical team, like engineers. I didn't. Right. I sort of just came to Codex and um, asked it to build the website. The idea is to use AI really anywhere in the process where that makes sense. Literally. My technical co founder, there's so much

Speaker B: you couldn't do before, practically from a cost perspective, even from an execution perspective that is now totally possible. And so you can like unlock your creativity in a way that wasn't possible before.

Speaker A: Really does unlock so much creativity. A lot of my designs start from a hand drawn sketch. But the other piece of this is I sort of developed the fashion prompt that's behind it and it describes a lot of sort of what goes into a garment. So it has like the, the silhouettes, uh, the proportion or the volume of, of the dress, like kind of like the fabric, how it flows, how it behaves, the construction details, how it moves, even how it sounds. The other piece that is still unsolved and I'm sort of still banging my head against the wall is to get it to create based on my design. And there I'm kind of running humans and AI in parallel. So I am working with human pattern makers, Codex and just saying who's going to get to making my thing fastest.

Speaker B: Welcome to How I AI. I'm Claire Vo, product leader and AI obsessive. Here on a mission to help you build better with these new tools. Today I have Yana Wellander and she is building an AI native fashion startup and she's going to show us how AI can intersect art, creativity and real world production. And why computer use plus software means SaaS really isn't dead. At least not yet. Let's get to it. This episode is brought to you by Merge. Building an AI product is one thing, the hard part is everything around it. Connecting to the tools your team and customers rely on, letting agents take action with the right permissions and keeping everything reliable and cost efficient. Once you're in production, uh, most teams end up piecing that together themselves. So instead of building the product you actually care about, you get pulled into integrations, permissions, routing and all the infrastructure underneath. Merge is the infrastructure layer for production AI. It connects to thousands of tools, gives agents secure ways to act inside them, and optimizes model routing and spend without you building or owning any of it. OpenAI, Dropbox and Ramp already use Merge to move fast and build AI right? Visit merge.devhowaiaiai to start building for free. Yana, thanks for joining How I AI. I'm an art and fashion girl. You know this, there are like five of us AI art and fashion girls on Twitter and we all find each other, but I am one and I love what you're working on. So immerse us in this new thing that you're working on and then we'll talk about how you're using AI in this really unique fashion.

Speaker A: Cool. Yeah, I'm so excited to be here. Thanks for having me. I, uh, am building this AI native fashion brand and um, the idea is to use AI really anywhere in the process where that makes sense. So obviously heavily in the design and production process. But also it's literally my technical co founder and so I, that's, that's what I use it for everything.

Speaker B: And can you show us like it's, it's probably hard for people to conceptualize what like an AI powered fashion brand looks like. Can you just like show us a little bit of kind of like some of the stuff that you're working on and then we can get into how it actually, how you actually got there.

Speaker A: So this is Yana Bana, the, the, the fashion brand. And you can kind of see like every, everything here is built with AI. And so you have some of the different garments that I designed and um, I'll show later that like different ones starts from different, like from different aspiration, from different points. So oftentimes I start from a sketch. You can see that when you hover over some of these. So I start with a hand drawn, humanly manually, old school hand drawn sketch. And then I use AI to turn that into different types of fashion collateral and kind of technical specs and everything along the line to ultimately get to a garment. And I kind of use AI for all the things to visualize it, to create photos, to create videos of some of these garments. There a lot of them kind of allude to different like, um, technical, you know, computer things in a lot of ways. Because I feel like that should be really part of the theme. It should be obvious that uh, what it comes from. And so the fabrics will uh, use a lot of kind of the punch card, like computer punch card, uh, patterns and things like that so that you can really see that and the other, the other way in which it sort of appears. So you can see for example for this like uh, post keyboard, uh, T shirt which I'm wearing myself right now. Um, it also is uh, alluding to the fact that now we are not going to be using keyboards and a lot of this stuff, but can we now have give it a second life essentially and to make sure that it's like obvious the world we live in and the world we're entering.

Speaker B: And I just want to pause because when I first saw this I was like, what a fun, like little art project. Like I once made this, like, I vibe coded this app which was um, anthropic as an anthropology website because I thought it was very funny. But you're actually bringing these designs to life. Like you are actually wearing this keyboard shirt which is super cool. And so what, you know, I hear a lot of people who are in the creative fields be really fearful of AI because I think it is like displacement in a lot of ways. Like let's, let's all be honest here. There's like videos and sketching and all sorts of stuff that AI can do. And yet if you step on the other side of this, like post keyboard future, there's so much you couldn't do before, practically from a cost perspective, even from an execution perspective that is now totally possible. And so you can like unlock your creativity in a way that wasn't possible before. So I want you to show us step by step kind of what goes into creating a garment like this, creating and imagining a design like this and then actually getting it to production and getting a website like this up.

Speaker A: I think, I think you're absolutely right that it really does unlock so much creativity. A lot of, a lot of my designs start from a hand drawn sketch. But um, the other piece of this is, I sort of kind of developed this, um, technical, uh, it's essentially a stack. But I've, for the purpose of visualizing what it looks like, I have this sort of set up as just like the fashion prompt that's behind it. And it describes a lot of sort of what goes into a garment. So it has the silhouettes, um, the proportion or the volume of the dress, like kind of like the fabric, how it flows, how it behaves, um, the construction details, how it moves, um, even how it sounds, I can show in one of the pieces. It kind of has this really interesting kind of sound as you're walking, uh, in the dress. And I take all of this and put it together in essentially kind of, if we take it out of my flow, uh, you can see that at the core of it there's sort of this prompt that we could take, um, and plug into ChatGPT. Um, and oftentimes when I'm working with this, I will also have an actual sketch of what I want. And I sort of am then defining this in addition to the sketch. But just for the sake of us kind of playing in real time. Um, I just thought it'd be cool to just, um, use prompts to start with. So here we have a sharply tailored waist, defined jacket with exaggerated shoulders, and blah, blah, blah. Right. So now we're putting this in. Oh, I should have told it to make an image, but maybe figure out to do that. Yeah, there we go. Sometimes it's smarter than you think, even on instant. And so now it's going to generate an image. And oftentimes this will give me kind of like a product photo. But usually what I then want to do with this is to then take it to kind of the next level and I will have very specific types of, like, collateral that I want to get out of it. So once we have this ready, I will ask it to generate a Vogue style Runway photo. Oh, there we go. So this is kind of like the product photo of this. So, um, it has these exaggerated shoulders, uh, the waist, a lot of kind of the stuff that I asked it to. And if I had a specific sketch, it would really adhere to my sketch much more so than what was in the prompt. But then if we go to, um, here we say like, now make it into a Vogue, ah, style. Can you tell that I normally do not type anymore? And so I usually just use voice for all these things, so it's just like so hard.

Speaker B: It's easier for our podcast guests. Um, you use voice because they don't have to imagine what you're typing. So she's, you know, you're typing. Make it into a Vogue style photo

Speaker A: of a, um, model walking down the Runway in this outfit. And so then I kind of just like, iterate on this and there's um, I go to photo, um, that's a Runway photo. Then I go to like a, uh, influencer photo. And you kind of see this from a lot of different angles and, and also iterate on it based on kind of what you're seeing now. Make it, you know, red, make it shorter, make it longer, and all those different things. But I usually just start from, from a specific point and then iterate from there.

Speaker B: I have a question for you, which is, um, why ChatGPT and why Image Gen 2 as the, as the model you're using? There's a lot of image gen models out there. Um, why that particular one?

Speaker A: Yeah, so I've done a lot of experimentation with lots and lots of different image models. And what I found was ultimately, um, nanobanana and image 2.0. Really image, uh, uh, 1.5. Was already pretty good at this. Are the best at, ah, following visual directions. And often I'm not doing this usually I'm sort of, as I mentioned, I'm mostly giving them a physic, like a sketch that I want them to turn into a picture. And what image 1.5 did better than not a banana? And Image Images, uh, ChatGPT Images 2.0 does even better. Is it really well follows the sketch. In fact, it follows the sketch sometimes a little bit too precisely. And so you get something that doesn't look like fabric anymore, and you have to kind of be like, no, no, no, no, no. You got to, like, it's got to flow. Like, this is kind of why I have this. This very detailed kind of prompting, um, where I tell it how the fabric should flow, because otherwise it can get into the mindset of, oh, she really wants it to look like paper, you know. But, uh, but the flip side, though, with all the other image models that I've tried, is that they will make it look beautiful and realistic, but it will look very, very different from my design. And obviously, when you're designing fashion, you need it to look new and different. You don't need it to look like the most similar thing that's walked the Runway some other time. And that's usually what you get with a lot of other image models.

Speaker B: What I love. And if you can go back to your prompt, um, flow. What I love about this is this is just okay. So people are gonna be like, I'm not a fashion designer. I don't have any use for this. What I think is the takeaway here generally for folks is write down your process and write down what a definition of complete or good is. You. And I like you. We're a product ladies.

Speaker A: Product people. Yeah, it's a.

Speaker B: At that time, we were like, official product ladies. And you need a spec. Like, your prompt is a spec. And so if you can put into the effort of saying, like, what makes a really good garment, like, what makes a really good photo, what makes a really good illustration, and come up with, like, five things that you can define for the prompt, you can get a really good output of AI. And then what I love, my friend Zach says, what's good for AI is good for humans. Like, let's just say you had. You were going to have a human sketch this out or build this, this is the exact information they would need as well to do a good job. And so whether or not you're doing, like, fashion illustrations or coding right, like this at the Spec. The PRD matters, people like the spec matters. And so getting, forcing yourself to sit down and be a little bit more precise is going to get you that exact outcome that you, that you want. And, um, you know, to be honest, I think that jacket's pretty, pretty rad. I would, I'd wear it. This episode is brought to you by Jira by Atlassian. The teamwork graph in Jira delivers 44% more accurate agent results with 48% less token usage. That's a huge difference when working with AI coding agents like Claude, Cursor, Codex, or Copilot. The hardest part of shipping with AI isn't the code, it's the context. What's the right ticket? What did the specs say? What got decided in Slack? The teamwork graph pulls all of that from across your entire stack from Jira and confluence to GitHub and feeds it directly to your agents before they write a single line. You assign the work, the agent gets everything it needs, and a PR surfaces when it's ready. No digging, no context switching, no broken flow. Same team, smarter agents triumph free@jira.dev. that's J I R A dot D E V. I love it. So you've created this, this image. I also love this idea, taking, like a core image and iterating it through, like, Runway, photo influencer, photo, like, you know, standalone catalog, like photo product, product shot. What do you do next? Like, what's the next part of your flow?

Speaker A: So a lot of what I do is, um, kind of iterate on it. And so I, I have this, like, you know, change the color, change the, you know, change the fabric. Um, and so I have kind of a lot of these different ways to do that. But then the next piece really comes to kind of like, what is the production process? And the production process is going to be very different depending on what I'm doing. And so, um, to give you an idea from one of these. So, for example, I had this, uh, dress that actually did not come from a sketch. It came from. I had this one day where I was just being bombarded with Ruth Asaba's, um, artwork in different places. Like, I went to, I went with my son to this, like, kids event and there was an exhibit across the street that I, like, accidentally. We were just early, so we went and watched it when we were like, a test of MoMA, there's like a permanent exhibit there. Uh, he had a piano recital and the church had one of her pieces hanging literally almost above my head. And I was like, I keep I don't know. And so this is literally from my phone. So I didn't have a sketch. Right. Normally I start from the sketch, but in this case I was like, make a photo of a model walking down the Runway in a dress inspired by Ruth Asavas, uh, loop wired sculptures. And it was important that it had a beige undergarment because otherwise ChatGPT will not like. It's like, no, you're trying to make me make nude pictures, and I don't do that.

Speaker B: Very artistic. Nude picture.

Speaker A: No, I don't do that. Um, actually, I think even here, I tried to make it remove the sculptures in the background. And I was like, we're sorry. This violates our nudity guidelines. Right? This happens all the time.

Speaker B: It's very frustrating. Quick side, you know what? If I showed up to a date with my husband in this gown, I do not think he would be through. I don't think he'd be like, ooh, it's not quite erotic.

Speaker A: It's not exactly. It's not. It's not, um, it's not nudity. It's not, you know, it's not torn. Um, but here we are. And so this one, right? Like, this is. And I think that, um, uh, a lot of garments you would do, like, some garments I will drape, right, like on the model behind me, or some garments, uh, go into. They become, uh, you create a kind of a pattern. And I have different. Some AI processes, some non AI processes that I've done for patterns. But this garment is previously unmanufacturable. And so what I. And I ended up kind of taking this and, uh, also creating a video of it. This is kind of like, you can see a little bit more of what it looks like. But the next step for this particular garment will be to take it and 3D print it. And particularly these kind of big ball pieces will need to be, um, 3D printed. And so I, ah, then went onto Codex and had it helped me create CAD files for these balls. So I first prepped it and had it like. I was like, okay. So I made that into sketch. Then I made these pieces into, uh, kind of more sketch illustrations. Then it didn't do well. It still didn't do well. We had a bunch of back and forth. Eventually it started doing something that was a little bit more similar. Um, I had to do. This is a really, really long process. And then ultimately I had it using, ah, computer use, um, go and build this in 3D software so that I could create, like an MDL file and send send off uh, to 3D prints. So that's the process for this particular garment to sort of to 3D print it.

Speaker B: I have to again like I have to pause because if we're just talking about the creative like generation process again this is now a garment that would have been previously like almost inconceivable to make. Not just because it's difficult to construct. But even if you were like of course we could 3D print that before AI, we could 3D print it after AI. The tedium of creating the CAD models was so onerous that even getting to the point where you could execute on it is, is really hard. And so I just think this moment of like uh, unlocking the previously impossible, whether the impossible was technically impossible or if it was just like practically infeasible is, is super important. The other thing um, that I love bless Computer use and like Codex plus Computer Use. Love you so much because I can just be like I don't need to know how to use this software. Like you go use that software, you do whatever you want. Um, I've gone through this like trough of despair of like SaaS is dead. Maybe like we're never going to touch a website again. You know what like agents are really good at pressing buttons. So like a software is back for. But agents are going to use it. It's very, very kind of like interesting shift I'm seeing.

Speaker A: I think that that's a great point and one, one fascinating piece is that a lot of these things like for actual end product like a CAD file, um, codecs as amazing as it is um is not great at generating a final CAD file if you asked it to do it on its own. But if you use um. Yeah, if you use computer use uh and have it go and do it in a piece of software that's designed for that purpose. And I have both for like actually for 3D printing and there's a uh, ah, fashion um software called clo, um that I've used as well and it generates this like it generates patterns and it then um, fits them on a 3D model. And I tell Codex to go and use this software that I haven't learned how to use myself and it does such a great job at something that it itself couldn't do. So it's sort of like SaaS in combination with Codex works so well on a lot of these things that uh, don't. And I'm sure it's just a matter of time but that's where we are today and I want to do it today. I don't want to wait. I don't want to wait like a year.

Speaker B: I love it so much. Okay, so you like generated an idea. We've sketched it, we've created images, we've even started to prototype the construction of it. How are you getting something built and maybe not the gown, like, maybe this like keyboard shirt that you're wearing. Like, how are we actually getting this manufactured?

Speaker A: Yeah. So for something like that, um, what I've done and I do this a lot is I will go. And now, uh, this same tool becomes my research assistant and I ask it to identify like, um, find 10 US based custom apparel manufacturing companies that are similar to the one that I liked. But I want to see if there's other ones. And then I just like there's a bunch of things I want and I kick off a deep research on, uh, extra high so that it's extra high while doing it and not in that way. Um, and then I get back a bunch of things. But usually so, so for, for a lot of my work I end up like I'm doing something else. So I'm like, I am kicking off this research and then I go and like drape fabric on, on model. Um, or I do like I'm, I'm on my sewing machine doing prototypes. Like I'm doing something else. And so a lot of them kind of the next steps end up being via voice. And so I like, in this case I came back to and I was like, well, do you see the um. Because I'm talking uh, apparel and using voice, right? Like the apparel manufacturers that I asked you to find. Um, now can you like put together the emails that I can, that you can send off to them. But like, you may want to make sure that you get my, my approval to do that. And then I have. And then I use browser used uh, to let it go into superhuman and like set all of these up for me. But I really want to click the send button before just to check its work again.

Speaker B: Like something that is just so tedious. And you know, if, if I was like, you're, you're, you're much more diligent at this than I am. But if I was like, oh my gosh, I have this vision. We're gonna make, we're gonna make these keyboard shirts. They're gonna be amazing. And then I'd be like, how can I make it? And they're like, I have to like look up vendors. I would just practically give up because it feels so boring. But so Boring. You can, if you can get that work off to somewhere again, like the next step and the next step and the next step you're going to end up with is this like incredible business. And so I just am like so inspired by people like you that take AI and create like a niche and like can, can then take that and build out a business where maybe one wouldn't, wouldn't have been available or possible before. Um, I just think is, is, is super cool. Okay, so you're doing this vendor outreach. You're actually going to get this thing, this thing produced. Side note, for all the cool girls out there, um, when they're ready, we all want one. Put me on the, put me on the. Pre order, pre order.

Speaker A: There actually is. I'm gonna, I'm gonna, I'm gonna be that person. But you can pre order it.

Speaker B: Amazing. Perfect. Okay. And then last kind of, kind of flow you have is like again going back to like pre orders and how to actually run this business. How are you using it to like be your technical co founder and all this?

Speaker A: That's. I gotta say that that's probably like my favorite piece because this, I mean apart from the fact that it is like there's so much AI in this, but it's basically like an um, AI native, like Everlane or something, right? Like normally I would hire a technical team, like engineers. I would have possibly have it. I probably wouldn't. Let's be real. I wouldn't have a technical co founder, but I could have had a technical co founder. I'm a solo founder girl. This is just my nature.

Speaker B: It's the, it's the life.

Speaker A: But, uh, I would hire engineers. Um, and I didn't. I had it build this website. Um, and I did it and I sort of just came to Codex and asked it to build the website. There's a lot of pieces here that aren't just like a static website in that you can obviously pre order things. And I could add stripe to it, which is like in prior lives have been like a tedious big exercise. But I can go back and kind of show you the stripe flow. But adding that was just like a second. Um, I had to create databases to be able to track votes as people are voting on these different garments. Um, so I can kind of figure out which are the most popular ones to bring to life. And so I had to do that, um, in an earlier phase of this, I had to create a separate dashboard for me to track the votes in real time. Um, and so I did that. Now I really just like, I just use voice and I'm like, oh, hey, um, how many votes do I have for this thing now? Right? So like why would I even have a dashboard? Um, so I don't do that but like just to kind of show you like the stripe flow as an example of like, yeah, I came here and I was like, oh yeah, I use browser to add stripe to my site. It was like, I don't know. You're like, I'm not signed in. I'm like, no, you got to sign in my own in app browser. I'm like, no, no, no, you got go to mine. I'm already signed up there. And then I was like, yeah, you got to do it. I'm like, no, you can do it. You know this like back and forth. It's like, no, no, you can do it. Um, uh, and yeah, this is it. And then I had done, um, everything's uh, added and now pre order is live. This is like a very, very fast process and literally whenever I like need to change something about the process, I can really just come here and just list out all the things I want to change and it goes off and it finds the result project. Um, it finds uh, the repository in GitHub and does all the things I will say. Like this weekend, uh, my son built his own ah, websites using like ChatGPT sites. And I'm sort of just like sitting there going like do I should. I really like do I want to migrate off of Vercel? Do I really want like, you know, like is this, is this a whole new like now, like now a 9 year old can have his technical co founder like do this or like build, build a company for him. Right? Like just, it's, it's just so cool to see this all uh, evolve.

Speaker B: You know your, your nine year old and my nine year old are going to be best buds. We can create like a, like a codex club for fourth graders.

Speaker A: We should totally do that.

Speaker B: Um, this is a very sorry. We are doing San Francisco, uh, Silicon Valley momming stuff right now. I just want to, I want to like go back to one thing because ripped from the headlines Codex prompting. I too am like, hey, Codex, do this thing. And it's like, nah, no thanks, I can't. And m. I'm like, no, I'm pretty sure you can. And then like yes you can. Like I'm pretty sure you can. It's like, you're right, I can. I um, I'm gonna post about this later but I have this like smart Light bulb. You can see it's on my, on my thing. And I was like hack it. And it was like no, I really shouldn't. I was like, you can do it. And I was like done. So, so just be a little bit insistent. Uh, yes. You know, and, and you can get, get stuff done. This has been so, so fun. Again, just like recapping for folks. A business that I think like would probably be inconceivable before AI fully stacked from the creative process, creating images, creating videos, imagining product ideas all the way through like hardcore manufacturing and sourcing vendors to just like being able to voice note your virtual CTO and update anything you need to do and have your engineering team on demand in ChatGPT. Pretty incredible. I want to get through some lightning round questions and then we're going to get, get you out of here. You know my first question for you is like, what is the hardest part of this? Like what is still maybe like what is still hard? What isn't solved? What where are you still feeling friction?

Speaker A: So I'd say it's kind of two things. One is that uh, like getting it to really do, getting image models to do really unique things per your vision while still making it realistic, that has been really really hard. I feel like I've solved it like I've kind of cracked that nut, but it still is. And every now and again I'm sort of still get something that is really two dimensional or whatever and I have to really refine it. Um, the other piece that is still unsolved and I'm sort of still banging my head against the wall is to get it to create patterns. So to get uh, get it to create actually accurate patterns based on my design. And there I'm kind of running humans and AI in parallel. So I am working with human pattern makers uh, and codecs and just saying who's going to get to making my things fastest most accurate to my vision. Um, and so uh, that's been really cool to see. I'm not there yet with either actually with either uh, flow.

Speaker B: Okay. I love it. All right. And then my last question that I ask everybody, speaking of like when it's hard and when it fails you and not getting there quite yet, which is how do you prompt AI when it's not working? What's your. Are you nice? Are you nice mom or a mean mom?

Speaker A: I can be both but I think I'm mostly a nice mom. Uh, and the reason is that ah, I find that I get better output. So uh, like, I mean I am very direct and I'm sort of like, yes, you can, uh, you go do that. I'm not just like, oh, yeah, I'm going to do this for you. Um, but I will be very polite. I will still say please and thank you. Um, and I do think that it's because it's trained on body of text. And so if it sees four text outputs that is rude and mean, it will kind of get in the mind frame of that part of the Internet. Right. Versus kind of more professional business context. And then it will deliver something that's a little bit more what I want it to be. So that's that I do it for selfish reasons, not because I'm afraid of the future. AI Overlords.

Speaker B: Perfect. Well, this has been super, super fun and inspirational and just like a breath of fresh air in terms of a new use case, a creative space that we haven't seen before and something sort of like manifesting the world. So where can we find you and how can we be helpful to you?

Speaker A: You can find me on X. Mostly I am Yanabana on X. I am now Yana Bana at X. Um, I changed my handle to match the brand. Um, uh, but yeah, in terms of just like, helpfulness is getting feedback on all this stuff. Like you can come to Yanabana and vote on, um, the garments that you like. Um, so I can get feedback on what, what's working for people and what's not. Like, I'm all about user feedback and customer input. Um, and yeah, uh, tell me what you like.

Speaker B: I love it. Well, I love poppy love. Let's smash that like button. It is very cool.

Speaker A: Awesome. Uh, thank you. Uh, I'll let you know when that one is ready to go available for purchase.

Speaker B: Perfect. Well, thank you so much for joining. How iai.

Speaker A: Thanks for having me.

Speaker B: Thanks so much for watching. If you enjoyed this show, please like and subscribe here on YouTube or even better, leave us a comment with your thoughts. You can also find this podcast on Apple Podcasts, Spotify or your favorite podcast app. Please consider leaving us a rating and review which will help others find the show. You can see all our episodes and learn more about the show@howiaipod.com See you next time.