Guide · 6 min read
How to fix a Lovable or Bolt app that broke in production
Short answer
AI-built apps break in production because the tool optimized for a demo, not a maintainable system. To fix one: freeze changes, reproduce the failure, audit input validation, error handling, database queries, and security, fix the root cause, then add tests and monitoring before you ship again. If the structure is sound, this takes days to a couple of weeks — a full rebuild is rarely necessary.
Tools like Lovable, Bolt, Cursor, v0, Replit, and Windsurf are genuinely good at getting you to a working demo fast. The trouble starts when real users and real data arrive. The app that looked finished starts throwing errors, slowing down, or behaving differently every time — and no one on the team is sure why, or feels safe changing the code.
This is not a sign you did something wrong. It is the predictable gap between a demo and a production system. Here is why it happens and exactly how to close the gap.
Why AI-built apps break in production
AI coding tools write code that passes the happy path. They tend to skip the unglamorous parts that keep software standing up:
- ✱No input validation — real users enter data the demo never did.
- ✱Missing error handling — one failure crashes the whole flow.
- ✱Unindexed database queries — fast with 10 rows, slow with 10,000.
- ✱Weak or missing security rules — data that should be private is not.
- ✱No tests — every change risks breaking something that worked.
How to fix it: 6 steps
Stop shipping and take a snapshot
Freeze new features and back up the code and database. You cannot fix a moving target, and you need a safe point to roll back to.
Reproduce the failure
Find the exact steps, inputs, or data that trigger the break. Most 'random' production bugs are a specific edge case the demo never hit.
Audit the risky layers
Check the four places AI tools cut corners: input validation, error handling, database queries and indexes, and auth/security rules.
Fix the root cause, not the symptom
A crash is usually downstream of a missing check or a bad query. Patch the cause so the same class of bug stops recurring.
Add tests and monitoring
Write a test for every bug you fix, and add error logging so the next issue shows up in a dashboard instead of a customer complaint.
Ship behind a safety net
Deploy to a staging copy first, then production, with the ability to roll back instantly. Stability comes from a repeatable process, not luck.
Fix or rebuild?
Most of the time, fixing is faster and cheaper than starting over. Rebuild only if the data model is fundamentally wrong or security is broken throughout — everything else is usually a contained set of fixes. A short code audit tells you which situation you are in before you spend money either way. See how we approach it in AI website & app rescue and code audits.
Want us to take it over?
Send us the broken build. We audit the code, stabilize it, and make it production-ready — for a fixed quote, about half agency cost.
Send us the broken build