AI coding tools like Replit, Lovable, and Base44 can turn an idea into a working app incredibly fast.
But here's the catch:
AI-generated doesn't mean bug-free.
Authentication breaks. APIs fail. Databases stop responding. A feature that worked yesterday suddenly doesn't work today.
When that happens, repeatedly telling AI to "fix everything" isn't always the answer.
My 5-Step Debugging Approach
- Reproduce the problem
First, find exactly what's broken.
Is it the login? An API request? A database operation? Deployment?
A specific error is much easier to solve than "my app isn't working."
- Read the error
I check the browser console, Network tab, server logs, and API responses.
A simple 401, 404, or 500 can immediately point toward the problem.
- Isolate the cause
Instead of changing the entire application, I narrow the problem down to one component.
Frontend → API → Backend → Database
This prevents unnecessary changes from creating even more bugs.
- Fix, then test
Once the cause is identified, make the smallest effective change and test it.
Fix → Test → Verify → Repeat
Don't assume the app is fixed just because the error disappeared.
- Test production
An app that works in development can still fail after deployment because of different environment variables, credentials, domains, or configurations.
Always test the actual production workflow.
The takeaway
AI makes development faster.
Good debugging makes the result reliable.
My general workflow is:
Reproduce → Inspect → Isolate → Fix → Test → Deploy
If your AI-generated app is stuck with bugs, broken APIs, authentication problems, database issues, or deployment errors, you don't necessarily need to rebuild it from scratch.
Need help?
I provide AI web-app development, debugging, API integration, database integration, and deployment for Replit, Lovable, Base44, and similar platforms.
Replit: View my Replit Gig
Lovable: View my Lovable Gig
**
**: View my Base44 Gig
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