Latest / The Indie Hacker Podcast with Fexingo: Solo Developers, SaaS Side Projects, and Independent Tech / How One Solo Dev Uses AI to Build SaaS Products in Days
Transcript
- Lucas: There's this narrative floating around that AI will replace software developers. But what I'm seeing on the ground is something much more interesting — solo developers using AI as a force multiplier to build SaaS products in days, not months. Luna: Days? That sounds almost too good to be true. Are we talking about full-featured products or just MVPs? Lucas: Full-featured, with real paying customers. Let me give you a specific example. There's a solo developer, goes by the handle 'CodeSolo' on Twitter, who built an expense-tracking app specifically for freelancers. He used GPT-4 to generate the initial codebase and Claude for refining the user interface. The entire thing took him about ten days from idea to launch. Luna: Ten days. And it's actually working? How much traction did he get? Lucas: He launched on Product Hunt and made twelve thousand dollars in the first month. That's not just a hobby project — that's a viable business. And he's not alone. I've been tracking a handful of solo founders who are doing similar things. The common thread is that they already know their users deeply before they write a single line of code. AI doesn't replace that understanding. Luna: So the AI is handling the grunt work — boilerplate, CRUD operations, basic front-end components. But the founder still needs to define the product vision and validate the market fit. Lucas: Exactly. And that's actually a great segue into something I want to mention. If you're finding this conversation useful, and you appreciate that we keep this show ad-free, you can support us at buy me a coffee dot com slash fexingo. It's a small way to help us keep doing episodes like this. And honestly, we're just grateful for the community that's forming around this show. Luna: Yeah, it really does make a difference. We hear from listeners who say these episodes have helped them start their own projects, and that's exactly why we do this. Lucas: So back to CodeSolo. One of the key things he did was write extremely detailed specifications before asking the AI to generate code. He'd describe the exact data model, the user flows, edge cases — everything. That level of preparation is what made the difference between getting usable code and getting a jumbled mess. Luna: That makes sense. The AI is only as good as the prompt. If you give it vague instructions, you'll get vague code. But if you treat it like a junior developer who needs crystal-clear requirements, it can churn out solid work. Lucas: Right. And he didn't just accept the first output. He did multiple iterations, often asking the AI to refactor or optimise specific sections. He said the real time-saver was not having to write every line from scratch, but he still had to review everything carefully. Luna: I imagine there are pitfalls, though. Security vulnerabilities, licensing issues with generated code. How do these solo devs handle that? Lucas: That's a great question. CodeSolo mentioned he runs all ai generated code through a static analysis tool before deploying. He also avoids using AI for anything that handles sensitive data like authentication or payment processing — he writes those parts himself. It's about knowing where to trust the AI and where to rely on your own expertise. Luna: So the AI is more for the 'front-end scaffolding' and 'back-end logic that isn't security-critical'. That seems like a smart division of labour. Lucas: Exactly. And I think this is where the 'solo developer using AI' narrative gets interesting. Traditionally, a solo developer might take three to six months to build a SaaS product from scratch. Now, with AI, they can compress that to a few weeks. But the bottleneck shifts from coding to everything else — marketing, customer support, sales. Luna: Which are skills that many developers don't have. So the advantage goes to those who are not only good at using AI but also good at the business side. Lucas: Precisely. And that's why I think we'll see a new breed of solo founders who are 'full-stack' in a broader sense — they can code with AI, but they also know how to find customers, write copy, and build a brand. The ones who rely solely on AI to generate code without understanding the business will likely struggle. Luna: Let's talk about another example. I came across a developer who built a simple invoicing tool for freelancers using AI. He said it took him about two weeks, and he's now at five hundred dollars a month in recurring revenue. Not huge, but it's growing. Lucas: That's exactly the kind of thing I'm talking about. The barrier to entry is lower than ever, but the competition is also higher. Because if anyone can build a SaaS in two weeks, then differentiation comes from niche focus and customer experience, not just features. Luna: So what's your advice for a solo developer who wants to start using AI to build their side project? Where should they begin? Lucas: First, identify a very specific problem for a very specific audience. Don't try to build the next Salesforce. Build something for, say, freelance graphic designers who need to track project expenses. Then, before writing any code, write out the full spec as if you're giving it to a contractor. Be obsessive about detail. Luna: And then use AI to generate the initial codebase, but plan to spend as much time refining and testing as you would if you wrote it yourself? Lucas: Exactly. The AI gives you a head start, but it doesn't eliminate the need for quality assurance. And importantly, learn to read the code it generates. If you don't understand what it's doing, you're going to run into problems down the line. Luna: What about the risk of ai generated code being similar to existing products? Could there be copyright issues? Lucas: That's a real concern. The legal landscape is still evolving. Some developers I've talked to avoid using AI for core proprietary logic. They use it for generic things like form validation, database queries, UI components. The unique business logic they write themselves. That way, even if the AI's training data included similar code, the final product is distinct. Luna: So the key is to use AI as a tool, not a crutch. And to always maintain ownership and understanding of your codebase. Lucas: Yes. And I think the developers who thrive in this new era will be the ones who combine AI acceleration with strong product sense and marketing chops. The ones who treat AI as a junior developer they can delegate to, but who still oversee the architecture and the user experience. Luna: It's an exciting time. We're seeing a democratisation of software creation, but also a raising of the bar for what it means to be a solo founder. Lucas: Absolutely. And I'm curious to see how this evolves over the next year. Will we see a wave of micro-SaaS businesses started by non-technical founders using AI? Or will the technical founders who embrace AI have an edge because they can debug and optimise more effectively? Luna: I think it's the latter, at least for now. Understanding the fundamentals of software engineering still matters, even if you're not writing every line manually. Lucas: I agree. And on that note, we'll keep tracking these stories. If you have a story about using AI to build a product, we'd love to hear from you. You can find us on Twitter at Fexingo. Thanks for listening.