The fastest way to fix a broken Lovable app is to stop prompting and start reading. Export your project to GitHub, open the actual code, and find the real error message instead of asking the AI to guess again. Most "stuck for three days" situations are one specific bug that repeated prompting keeps papering over with new code, which creates two more bugs.
Why prompting more usually makes it worse
Lovable regenerates code around your request. When you say "fix the login," it rewrites the login and anything touching it. If the actual bug is a database rule or an environment variable, the rewrite does not fix it, but it does change working code you did not ask it to touch. After ten fix attempts you have ten layers of half-related changes and no idea which one broke what. This is why apps that "worked yesterday" degrade the more you try to repair them.
The diagnostic order that actually works
Work through these in order. In our audits, the bug is found at one of these steps far more often than in the app code itself:
- Browser console first. Open developer tools, reload the page, read the red errors. The real failure is usually named there, word for word.
- Check Supabase logs. If your app uses Supabase, the dashboard logs show failed queries and permission denials that never appear in the UI.
- Row Level Security policies. The single most common Lovable failure: data reads or writes silently blocked by RLS. If data appears for you but not for other users, it is almost always RLS.
- Environment variables and keys. Preview works, published site does not: that pattern is usually a missing or wrong key in the deployed environment.
- Third party services. Stripe, email, maps: check their dashboards for declined requests before blaming the app.
When can I fix it myself?
If the console shows one clear error and the app worked before a specific change, you can usually fix it yourself: revert to the last working version in GitHub history, then reapply your change in smaller steps. Lovable connects to GitHub, and version history is the most underused rescue tool it has.
When is it time to bring in a developer?
Bring in a developer when any of these is true: user data is exposed or wrong, payments are involved, the same bug returns after every fix, or you have real users and every hour down costs you. A senior engineer reading the code finds in an hour what prompting cannot find in a week, because the AI can only see the code it wrote, not the system around it.
What does it cost to have someone fix a Lovable app?
A focused audit of an AI-built app typically runs a few hundred to fifteen hundred dollars fixed price, and most rescues are stabilized inside a week. That is usually cheaper than the revenue lost while the app is broken, and far cheaper than a rebuild.