Key takeaways
- AI coding tools like Cursor, Lovable, Bolt, v0 and Replit are great at getting a demo working for one user, but they tend to skip security, error handling, database design and scalable architecture.
- Warning signs: bugs you cannot trace, AI fixes that create new bugs, new features breaking old ones, unclear data security, and slowdowns as data grows.
- A proper rescue starts with an audit, then stabilizes, secures, strengthens and re-architects only the parts that cannot scale. It is not a rewrite from zero.
- Most rescues take two to six weeks. Get a scoped audit first so you know what is wrong and what it costs before committing.
To fix an app built with Cursor, Lovable, Bolt, v0 or Replit, start with a code audit, not more prompts. An engineer maps what is fragile and what is dangerous, then you stabilize the bugs, close the security holes, clean up the code, and rebuild only the parts that cannot scale. Most rescues take two to six weeks and keep the product you already have.
You described what you wanted, an AI tool wrote the code, and a few days later you had a working app. Then real users showed up and it started breaking. That is not a sign you did something wrong. It is what happens to most apps built purely with AI coding tools, and it is fixable.
Why AI-built apps break
AI coding tools are very good at one thing: getting a demo working for a single user. They are much weaker at the parts that make software survive real use. They tend to skip security, proper error handling, database design, and any architecture meant for more than a handful of people at once.
The research points the same way:
- Security. Veracode tested more than 100 language models on 80 coding tasks and found that the generated code introduced a security flaw from the OWASP Top 10 in 45% of cases (Veracode 2025 GenAI Code Security Report).
- Bugs. CodeRabbit compared 470 open-source pull requests and found AI-co-authored ones carried about 1.7 times as many issues as human-only ones, with more logic errors and more security findings (CodeRabbit, December 2025).
- Messier code. GitClear's analysis of 211 million changed lines found an eightfold rise in duplicated code blocks during 2024, and it was the first year copy-pasted code outnumbered refactored code (GitClear via LeadDev).
- Real exposure. In 2025 a researcher scanned 1,645 apps from Lovable's public showcase and found 170 whose database tables could be read or written by anyone, because row-level security was missing (CVE-2025-48757).
These are vendor studies with their own methods, so treat the exact numbers as indicators. The pattern is consistent, though: the code looks finished, and underneath it is fragile.
The signs your app needs a rescue
| What you see | What is usually behind it | What fixes it |
|---|---|---|
| Works in the demo, breaks with a few real users | No handling for concurrent users, errors or slow responses | Error handling, load testing, fixing the hot paths |
| Asking the AI to fix a bug creates two new ones | Duplicated, tangled code with no tests | Refactoring the core paths and adding tests around them |
| You are not sure user data is safe | Missing database access rules, secrets in the frontend | A security pass: access rules, key rotation, server-side secrets |
| New features break old ones | No structure separating parts of the app | Splitting the code into clear modules |
| The app slows down as data grows | Unindexed queries, everything loaded at once | Database and query review, pagination, caching |
None of these mean you built the wrong product. They mean the foundation needs professional attention before you grow further.
How a professional rescue works
A good rescue does not start by throwing everything away. It starts with an audit: an engineer reads the codebase and maps what works, what is fragile, and what is dangerous. The work then falls into four buckets.
Stabilize. Fix the bugs that are breaking things now and get the app to a reliable baseline.
Secure. Close the security holes, lock down the APIs and database access rules, move secrets off the client, and make sure user data is actually protected. For apps on Supabase, that starts with checking row-level security on every table.
Strengthen. Clean up duplicated code, add error handling and tests around the core paths, and put in monitoring so problems surface before users report them.
Re-architect where needed. Where the foundation genuinely cannot scale, rebuild that part properly. This is targeted, not a full rewrite.
Most rescues take two to six weeks depending on how much has to be fixed. You keep the progress you made and come out with software you can trust.
What it costs
It depends on the state of the code, and the range is wide: light stabilization can be a few thousand dollars, while a serious re-architecture costs more. The important step is a scoped audit up front, so you know what is wrong and what it will cost before committing to anything. Sprout's audits start from $1,500, with the fixes quoted afterwards. For comparison, building a new MVP from scratch typically costs 15,000 to 60,000 dollars, as we break down in how much it costs to build an MVP.
The takeaway
Building fast with AI was the right move. It got a real product in front of real users far sooner than the old way. But AI tools optimize for the demo, not for production, so the app that got you here usually needs a professional pass before it can carry real growth. Get it audited, fix what is fragile, and keep your head start. Sprout rescues AI-built apps, turning fragile prototypes into production-ready software.