Short answer: to rescue a broken Lovable app, do not start by prompting the AI for more fixes. Freeze the current state, write down exactly what is broken, and work through the failures in an order that protects your users first: exposed keys and data access, then login, then deployment, then features. Fix what is cheap and well understood, and rebuild only the part where the foundation is wrong. Each new prompt on a broken app risks breaking two things that worked, so the rescue is mostly about slowing down and making each change checkable.
This guide is for founders and small teams whose app was built with Lovable, Bolt, Cursor or another AI coding agent and now misbehaves. It is practical and general. It cannot diagnose your specific app, and it is not a security audit.
Why AI-built apps break in a predictable way
AI coding agents are very good at getting to a working demo. The demo is a happy path: one user, clean data, nothing hostile. Real use adds the things the demo never needed: many users, bad input, expired sessions, a second device, a stranger poking at the URL.
The failures that follow tend to cluster in the same places, because those are the parts that need decisions the prompt never contained: who is allowed to see which row, where a secret lives, what happens when a login expires, and what is different between your preview and your live site.
The usual failure shapes
| Symptom you see | Likely area | First thing to check |
|---|---|---|
| Login works for you but not for others, or logs people out | Authentication | Redirect URLs, email confirmation settings, session handling, and whether the live domain is allowed in the auth provider |
| Users see each other's data, or see nothing | Database access rules (for example Supabase row level security) | Whether row level security is on for every table, and whether each policy matches the user it is meant for |
| Everything works in preview, fails on the live site | Deployment and environment | Environment variables on the live host, the build log and the domain settings |
| A third-party service fails after launch | API keys | Whether the key is in the browser code, expired, or restricted to the wrong domain |
| Forms look submitted but data never arrives | Writes and error handling | The network tab response, and whether errors are swallowed silently |
| A fix in one place breaks another | Structure | Duplicated logic, no tests, no separation between screens and data access |
| The bill jumped, or a service is rate-limited | Cost and limits | Usage dashboards of each provider, and any call made on every page load |
Use this as a map, not a verdict. The same symptom can have several causes.
Step 0: stop the damage and freeze a copy
Before you change anything:
- Take a copy. If the project is connected to a git repository, make sure the latest state is pushed and tagged. If not, use whatever export or version history the tool provides, and download the files.
- Stop prompting. Every new prompt rewrites code you have not read. Pause the AI until you know what you are fixing.
- Write the symptoms down. For each problem, note what you did, what you expected and what happened, with the time and the account used. A precise symptom is half a fix.
- Note what is live. If real users or real payments exist, decide whether to put up a maintenance page while you work. A short outage is often better than a corrupted database.
- Back up the data. Export the database or take the provider's backup before touching policies or migrations.
Step 1: secrets and keys
Anything that runs in the browser can be read by anyone who opens the site, so start here. Our guide to ten checks before launch for a Lovable or Cursor app goes into this in depth.
- Open the live site, open the developer tools and look in the loaded code and network requests for keys.
- Some keys are designed to be public, such as a Supabase anon or publishable key, or a Stripe publishable key. Others must never be in the browser: a Supabase service_role key, a secret payment key, a private model API key.
- If a secret was exposed, replace it at the provider and delete the old one. Removing it from the code is not enough, because it can remain in git history and in anything already downloaded.
- Move the call that needs the secret into a server function, and have the browser call that.
This step is first because the cost of leaving it is highest and the fix is usually small.
Step 2: database access, the Supabase row level security check
If your app uses Supabase, the public key is safe in the browser only if row level security protects every exposed table. When it does not, anyone with the key can read or change rows.
A test you can run yourself, with two accounts that belong to two different made-up users:
- Create data as user A.
- Sign in as user B and try to read, edit and delete user A's data through the app.
- Try the same with no sign-in at all.
- Repeat for every table that holds user data, including file storage buckets.
If B can see A's data, turn on row level security for the table and write a policy that matches rows to the signed-in user. Then test again, because a wrongly written policy can lock everyone out, which looks like a bug of its own.
This is a check, not a certification. Passing it does not prove the app is secure.
Step 3: authentication
Login problems are rarely mysterious once you look at the settings.
- Redirect and site URLs. The auth provider must list your live domain, not just the preview address.
- Email confirmation. Confirmation links that point at the wrong domain are a common cause of "I signed up and nothing happened".
- Session expiry. Check what happens when a session ends in the middle of using the app. A blank screen is a failure to handle an expected case.
- Password reset. Test it end to end, with a real inbox.
- Roles. If there is an admin area, confirm a normal user cannot reach it by typing the address.
Fix these in the provider's dashboard where you can. Only touch code once you know the setting is right.
Step 4: deployment and environment
"It works in preview" is a statement about one environment.
- Compare environment variables between preview and live. A missing variable is a common reason for a feature that fails only after launch.
- Read the build log for warnings that were ignored.
- Check the custom domain, certificate and any redirect rules.
- Confirm the live site is running the version you think it is. Make a visible change, deploy it and look.
- Check that error pages exist and do not reveal technical details.
Our free website security headers check can tell you what the live site sends to browsers.
Step 5: errors, logs and tests
An app that fails silently cannot be fixed with confidence.
- Add visible errors for failed saves and failed logins, so the user and you can see them.
- Log server errors somewhere you can read.
- For each bug you fix, write down the steps that reproduced it, and re-run them after every change.
- If the fix is important, add an automated test that fails when the bug returns. Even a handful of tests changes how safe the next change is.
Step 6: features, in order of value
Only now go back to the visible features. Rank them by what the business needs this week: payment, sign-up, the one workflow people came for. Fix one, test it, commit it, then move to the next. Resist the urge to ask the AI for three changes in one prompt.
When you do use the AI to help, give it a narrow task, ask it to explain what it will change before it changes it, and read the result before you accept it.
Fix or rebuild?
This is the real decision, and neither answer is always right.
| Lean toward fixing when | Lean toward rebuilding when |
|---|---|
| The data model is sound and the problems are in settings, keys or a few screens | The data model is wrong and every screen works around it |
| The code is readable and the same logic is not copied in many places | Every feature has its own copy of the logic and no one can say which is current |
| Problems are isolated: one fix does not break others | Each fix breaks something else |
| You can reproduce each bug and test the fix | Bugs appear and disappear without a pattern |
| The app is small and the fixes are enumerable | The app has outgrown what the tool can hold in its head |
A middle path is often best: keep the design, the screens and the content, and rebuild only the layer that is wrong, usually the data access or the authentication, behind a clear boundary. The screens you like do not need to be thrown away because the plumbing under them is.
Whichever you pick, get the decision in writing with a list of what will be done, what will not, and how you will know it worked. A rescue with no end condition can become open-ended work.
When to get help
You can run Steps 0 to 4 yourself with patience. Consider outside help when:
- The app holds payments, health information or other sensitive data.
- You found something you cannot explain, such as users seeing each other's data.
- You have been going in circles for more than a few days.
- The business needs a date, and the app is the blocker.
Devaland offers AI app rescue for apps built with Lovable, Bolt, Cursor and similar tools. The page, read on 8 November 2026, describes a fixed-price diagnosis at 390 EUR excluding VAT, a written report delivered within 5 working days after access is received, and a fixed price for each fix. The report is yours to use with any developer. It also says that if the app cannot be taken, for example because it turns out to be fintech or to hold health data, the diagnosis is refunded in full. Check the page for current terms before you decide, because prices and scope can change.
A one-page triage list
- Copy the project and back up the data.
- Stop prompting until you know the problem.
- Write each symptom with steps to reproduce.
- Check keys in the browser, then rotate anything exposed.
- Test database access with two accounts and with none.
- Check login, redirects, confirmation and reset.
- Compare preview with live: variables, domain, build, version.
- Make errors visible and logged.
- Fix features one at a time, with a test or a written check.
- Decide: fix, rebuild the broken layer, or rebuild the whole thing.
Frequently Asked Questions
How do I rescue a broken Lovable app? Freeze a copy and back up the data, then stop prompting. Write down each symptom, then work in order: exposed keys, database access rules, login, deployment, error handling and only then features. Fix one thing at a time and check it before moving on.
What is the Lovable app rescue process? A sensible rescue is a triage followed by a decision. The triage finds what is broken and how serious it is, and the decision is whether to fix, rebuild one layer or rebuild everything. A good process ends with a written list of what was done and what was not.
Why does my Lovable app work in preview but not live? Usually the live environment differs: missing environment variables, a domain not allowed in the auth provider, a failed build or an older version still being served. Compare variables, read the build log and confirm the deployed version with a visible change.
Is my Supabase data exposed in my Lovable app? It can be if row level security is off or wrong on a table the app exposes. Test with two user accounts and with no sign-in, on every table and storage bucket. This is a check, not proof of security.
Should I rebuild or fix my AI-built app? Fix when the data model is sound and the problems are settings, keys or a few screens. Rebuild the broken layer when every fix breaks something else or the data model is wrong. Rebuilding the whole app is rarely the only option.
How much does an AI app rescue cost? It depends on the provider and the app. Devaland's page, read on 8 November 2026, lists a diagnosis at 390 EUR excluding VAT, with each fix quoted separately at a fixed price. Check the page for current terms.