I tried to vibe-code my way to a SaaS… and failed
Last summer, the idea for my SaaS, Xolora, started to take shape. Around the same time, the concept of vibe coding was blowing up. As a non-technical founder, it sounded like a dream come true. No coding experience? No problem, just let AI handle it.
The beginning was incredibly promising. Using Emergent made me feel unstoppable. I was seeing my idea come to life.
But then, reality hit.
The moment the architecture required deeper complexity the magic completely faded. I stopped building and started drowning. I spent days stuck in endless debugging loops, trying to explain to an AI errors that I didn’t even understand myself. I was burning precious time, and honestly, the Vercel deployments and GitHub conflicts became a nightmare. The vibe-coded version was far from a real, stable product. In fact, it was embarrassing.
It was a tough pill to swallow, but it made me realize that AI is a powerful assistant, but it doesn’t replace structural software engineering when you're building a scalable product.
Instead of giving up, I decided to pivot my approach. I teamed up with a professional developer. Now, we are rebuilding Xolora properly to actually deliver the value that solopreneurs and small business owners need, without the fragile vibe-code foundation.
For the other non-technical founders here: Have you managed to launch a complex SaaS purely on vibe-coding, or did you hit the same wall? At what point did AI stop being enough for you?
Replies
Just launched Ligara — a creator platform I built entirely with Lovable in 4 days with zero coding experience. Lovable has been incredible for going from idea to live product fast. Happy to share my experience if anyone's curious.
@janetbuilds I think any vibe-coding tool is incredible for going from idea to live product fast. The issue is that vibe-coded software usually isn't GDPR compliant (and I am based in the EU) and it's harder to scale. Like it's most likely to crash if 200 users are using it at the same time (unless you explicitely prompt it to be scalable).
Wow, thank you for sharing this experience! And loved that you pivoted and it was a happy ending post.
@heyitsirenechan Thank you! I'm also glad I pivoted. :)
I think there’s some framing that’s needed here. If you started your project 6 months ago that’s very different from the model/orchestration/tool landscape of 2 months ago. So 6 months ago that wall would have been much harder to “scale” 🤷♂️🤣
Another fundamental paradox is that agentic infra development is changing so quickly that it’s potentially advantageous to iterate on architecture, “ontology”, schema, and more abstract aspects than go straight to coding, ie it might be better to delay some key decisions than to rush into building. This can set you up to spend less time chasing your tail. For example, I’ve been spending a lot of time thinking about observability and governance tools and that landscape is pretty immature relative to what agents can do. So achieving “scale” depends on exactly what you’re doing. That thing that saves you a month of work might release next month so the entire month you spent sorting out problem X might have been better spent on Y etc. Architecture work and development roadmap refinement can result in serendipitous delays, dead ends that save you from coding useless components, endless debugging loops, etc. Maybe the problem you’re trying to solve improves with the next model upgrade. Maybe you needed to switch models or orchestration platforms. Developers won’t magically know how this looks.
You could need a team of engineers to deploy something “at scale” but depending on who you talk to and their particular expertise you’re going to get varying opinions so it’s still valuable to research with AI and constantly seek more information. I wouldn’t be so quick to defer to a developer as a default solution that can solve all of your problems as complex tools usually require teams, and a single developer isn’t a silver bullet. Learning to use agents with access to calling tools like Jira/ClickUp and GitHub/Bitbucket has been huge for me. I’ve also added Slack to my workflow and these are all necessary prerequisites to managing complex tasks between people and AI.
I have no technical coding background but I had a pretty good experience using Claude chat to discuss what I wanted and have Claude create the code. First thing Claude asked was for me to install Node.js and VS Code and Electron, so we could structure the app. I haven't launched the product yet, but I have been using it for a few weeks and I am happy with the result.
The useful split here might be “prototype spec” vs “production spec.” Vibe coding is very good at turning a rough product idea into something you can react to, but it’s easy for non-technical founders to mistake that artifact for the real system.
Before rebuilding with a developer, I’d preserve the parts the prototype clarified: the workflows users understood, the screens that made the value obvious, the language beta users repeated back, and the edge cases that broke trust. That becomes much better source material for the professional build than a blank rewrite from memory.
This may be a stupid question, but what exactly is vibe coding?