Why Your AI-Built App Breaks in Production

AI coding tools are probably the most impressive thing happening in tech right now. You describe what you want, it builds a genuinely good looking app, and the whole thing just... works. In the preview.

Then you try to put it in front of real users and everything falls apart.

I'm not picking on any specific tool here. This happens with every platform that abstracts away complexity. The abstraction works great until it doesn't. And production is where "doesn't" lives.

The Preview Lie

The preview environment is amazing. It runs your app in a sandboxed world where everything is configured correctly, the database is right there, auth is pre-wired, and network conditions are perfect.

Production is none of those things.

Your users are on slow phones. Your database has actual data in it (not seed data). Your auth tokens expire. Your API has rate limits. Your CDN sometimes serves stale assets.

None of this shows up in preview. All of it shows up in production.

The Usual Suspects

Row Level Security on your database. This one gets people constantly. AI tools set up database tables but don't always configure access policies correctly. In preview, it works because the connection uses a privileged key. In production, your users hit a restricted key and suddenly they can't read their own data.

The fix is almost always adding the right access policies. But figuring out which policies you need requires understanding your data model, and that's the part the AI abstracted away from you.

Auth Redirect URLs. AI tools wire up authentication. But the redirect URLs are set for localhost or the preview domain. When you deploy to your own domain, the redirects break. Users click "Sign In" and get sent to a page that doesn't exist.

Go into your auth provider's dashboard. Add your production domain to the allowed redirect URLs. That's it. Five minutes if you know where to look, three hours if you don't.

Static vs Dynamic Content. AI tools tend to generate pages that fetch data at render time. This works in preview because the server is fast and close. In production, if you're fetching data on every page load, your app feels slow. And if the API is down, your whole app is down.

Consider whether some of your pages could be statically generated or cached. It depends on your use case, but it's worth thinking about before your users start complaining.

Mobile Responsiveness. AI tools generate responsive layouts, but "responsive" in preview and "responsive" on an actual phone are different conversations. Test on real devices before you ship. Or at least use Chrome DevTools with actual device dimensions, not just "responsive" mode.

The Uncomfortable Truth

Here's the thing nobody wants to say: the gap between "AI built it" and "it works in production" is still a gap that requires developer knowledge to cross. Not always a lot of developer knowledge. Sometimes it's 10 minutes of work. But you need to know which 10 minutes.

If you're a vibe coder and you're stuck at this stage, you have two options. Learn the specific thing that's broken (totally doable, just time consuming). Or get someone who already knows to fix it for you.

That second option is what VibeFix exists for. Post your production bug as a bounty. Tell us what's broken, what you expected, what actually happens. A developer will pick it up and fix it.

Your app is 95% there. Don't let the last 5% stop you from shipping. Post a bounty and get it across the finish line.