Lovable stuck in an error loop and can’t fix it: what to do
When Lovable or Bolt fixes one thing and breaks another, stop asking for the same fix. Go back to the last version that worked, isolate the error, read the logs and investigate in a mode that does not touch the code. If the error still comes back, move the code to GitHub and have someone read it.
Heartscale’s recommendation: after two failed attempts, revert to the last good version, bookmark it and connect GitHub before asking for another fix. If the error touches login, payments or database data, have someone read the code before the next change.
Every attempt costs credits, and repeating the same prompt rarely changes the outcome. The steps below use features the platforms document themselves.
Why the AI gets stuck in a loop
Four causes tend to show up together.
The AI’s memory has a limit. Bolt’s documentation calls it the context window: the working memory that holds your project files and everything you sent in the chat (Managing project context). When it fills up, Bolt keeps only recent messages and can forget older ones. The docs warn that an oversized context can cause errors, slower responses and lower-quality results.
Duplicate code. Instead of fixing a function, the AI sometimes writes a second version of it in another file. The fix lands in one copy and the bug stays in the other. Bolt recommends removing unused files and splitting files longer than about 700 lines, testing after each change.
No tests. Without automated tests, nothing warns you that today’s fix broke yesterday’s screen. You find out by clicking around, and so does the AI.
The cause sits outside the code the AI edits. A missing secret, a database policy that blocks writes or an external service that is down all surface as an error on screen. The AI rewrites the screen and the error stays. The “new row violates row-level security policy” error is a common example. Our Supabase RLS guide explains how to fix it.
Step 1: stop at the second attempt
If the same fix failed twice, a third try tends to repeat the same path. Count the cost before you push on:
- Lovable: the Try to fix button shows up on the activity card when there is a build error. Your account has 10 free fixes, shared with fixes from the Security view, and each one comes back 24 hours after use. After that, Try to fix consumes credits (Troubleshooting).
- Bolt: every automatic attempt uses tokens. Bolt advises against clicking Attempt fix over and over and suggests researching the error when automatic fixes fail (Maximizing token efficiency).
Step 2: go back to the last version that worked
Bolt recommends using version history instead of asking the AI to undo a change. The same applies on Lovable.
On Lovable (Version history):
- Click History in the top bar, or open the menu next to the chat input and choose Project → History.
- Click a version to see how it looked, without changing the project. Back to latest returns to the current one.
- Find the last one that worked and click Revert. Confirm.
The chat has shortcuts too (Chat). Undo latest edit, under the latest response, reverses the most recent change. Edit message, on one of your messages, opens Revert and resend: the project returns to its state before that message and runs the rewritten prompt.
Three warnings from the docs:
- reverting restores code and redeploys Edge Functions, but does not undo database data. Records created and migrations run after that version stay in place;
- reverting does not refund credits;
- very old versions show “Cannot revert this far back in history”.
Once you reach a good version, mark it with Bookmark in history. It becomes your safe point.
On Bolt (Rollback and backup): open Version history (clock icon), click the version, then Restore this version, and confirm with Restore version. The docs say restoring does not change your Bolt or Supabase databases, and version history restores without using tokens.
Step 3: investigate without letting the AI touch the code
Both builders have modes that talk without editing files.
Lovable: in the mode picker next to the chat input (or with Alt+P / Option+P), choose:
- Chat, to discuss the app. Each message usually costs a fraction of a credit and draws on your daily chat allowance first;
- Plan, to investigate and write a plan you approve before any code is written. Each message costs one credit, plus any research it runs, and the docs say Plan mode never modifies your code (Plan mode).
Bolt: click Plan in the bottom-right corner of the chatbox. When the plan is right, Implement this plan switches to Build Mode (Plan Mode). If Bolt gets stuck or stops responding, type /clear and click Clear context. That resets the chat memory and keeps your files.
One useful question in these modes: “List the files that handle this and tell me whether any code is duplicated.” It exposes the cause of the loop before anything changes.
Step 4: isolate the error and read the logs
The AI fixes better when it gets the exact error. Before your next prompt, gather:
- The error text, copied, not summarized.
- The steps to trigger it: which screen, which button, which user.
- What you expected and what happened.
- Since when: the first version in history where the error shows up.
Where to find the logs:
- Browser console: CTRL+SHIFT+I on Windows or CMD+OPTION+J on macOS, Console tab. Bolt suggests asking the AI to add debug logging, reproducing the error in a separate tab and pasting the output into the chat (Troubleshooting).
- Lovable Cloud: in the project toolbar’s More menu, open Logs (Lovable Cloud).
- Images: on Lovable, Take a screenshot and Draw mark the exact spot on screen.
Tackle one problem at a time, described in one complete message. Lovable recommends sending what would be several rapid follow-ups as a single request.
Step 5: move the code to GitHub
With the code on GitHub, every AI change becomes a commit showing what changed, line by line. You can see what changed between the good version and the broken one, and someone else can read and run the project outside the platform.
- Lovable: Project settings → Git → GitHub, then Connect. Lovable creates a new repository, private by default, and syncs both ways, one branch at a time (GitHub).
- Bolt: click the GitHub icon in the top-right corner, then Log in to GitHub and Install & Authorize. Bolt commits your changes and pulls updates from GitHub every 30 seconds (GitHub).
Connect GitHub before the next error. It keeps the history the chat does not show.
In our reviews, we open the GitHub diff between the last good version and the first one with the error. In that diff we look for duplicate functions, missing secrets and database policies that block writes.
When to call in a code reviewer
If the steps above do not solve it, get someone to read the code. The signs:
- the error comes back after you revert and ask again, with the exact error;
- the failure involves login, payments or personal data;
- the fix requires a database change, and reverting does not undo data;
- nobody knows what each part of the code does anymore.
If the problem seems to be with the platform itself, Lovable points paid plans to support at lovable.dev/support. For your app’s code, the path is a review. See also Is Lovable secure? for the risks that often come along.
Do it yourself or hire help?
You can follow steps 1 to 5 without technical help. The table sums up when it pays to bring in a team.
| Situation | Path |
|---|---|
| A new error on one screen, and going back to the good version fixes it | Follow steps 1 to 5 and bookmark that version |
| The same error comes back after you revert and ask again with the exact text | Have someone review the code on GitHub |
| The failure involves login, payments or personal data | Stop pushing in the chat and get a review before the next publish |
| The app has real users, the fix touches the database and nobody on the team reads code | Request a Heartscale diagnostic |
Request a Heartscale diagnostic
The AI took your app as far as it could. Our team reads the code on GitHub, finds the cause of the loop and lists what needs to change, by severity and with a price for each fix. See our code review for AI-generated apps service. We do not promise a timeline before reading the code.
The launch-price diagnostic costs US$ 19 (was US$ 79) and is credited toward the fix if you go ahead. We only work on apps whose owners can prove they own them.