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Cursor AI-Generated Code Not Working

Cursor helped you build fast. Now every change breaks something else, the AI keeps suggesting fixes that don't work, and you're stuck in a loop of errors you don't fully understand. A Codersarts engineer fixes the broken code and puts guardrails in place so AI-assisted development moves forward again.

AI-generated code usually stops working for predictable reasons: the AI edits parts of the code without seeing the whole system, invents functions or library features that don't exist, mixes outdated and current patterns, and has no tests to catch what it breaks. Each fix attempt adds more code on top of the problem, which is why error loops get worse. An engineer who reads the full codebase can find the actual cause and stop the cycle.




Typical symptoms

Error loops, features breaking after each AI edit, code that won't build, duplicated logic, unfamiliar errors

Most common causes

Limited AI context, invented APIs or outdated patterns, conflicting edits, dependency drift, no tests

How we fix it

Find the last working state, fix root causes across files, consolidate duplicated code, add tests and AI project rules

Turnaround

Same-day diagnosis; most fixes in 24–48 hours

Price

Live Debug from $20; fixed-price quote for the full fix



Signs Your AI-Generated Code Has This Problem

  • Every new AI edit fixes one issue and breaks another

  • The AI keeps suggesting the same fix for the same error

  • The build or type check fails with errors in files you didn't change

  • Imports reference functions or packages that don't exist

  • The same logic exists in several slightly different versions

  • A feature worked last week, and nobody knows which change broke it

  • You're afraid to ask the AI for new features



Why AI-Generated Code Stops Working

AI coding assistants are excellent at writing code for a clearly described task. Problems appear as the project grows, because the assistant works from a limited view of the codebase and doesn't remember every earlier decision.


1. The AI doesn't see the whole system

Assistants work from the files and context they're given. Changes that look correct in one file can break assumptions in another, and earlier decisions get overwritten.


2. Invented or outdated code

AI models sometimes use functions, options, or package features that don't exist, or patterns from older versions of a framework. The code looks plausible but fails at build time or runtime.


3. Conflicting edits pile up

Each prompt adds code without removing what came before. Over time the project collects duplicated components, competing approaches to the same problem, and dead code that still runs.


4. Dependency drift

Accepting suggestions that add or upgrade packages can introduce version conflicts that break other parts of the app.


5. No safety net

Without tests, type checks, or version control discipline, there's no fast way to know what a change broke or to return to the last working version.



How We Diagnose the Broken Code

  1. Find the last working version. Use version history to identify when features broke and which changes caused it.

  2. Run full checks. Build, type check, and lint the whole project to expose every error, not just the visible one.

  3. Find invented and outdated code. Check imports, function calls, and framework patterns against real library versions.

  4. Map duplicated logic. Identify competing implementations of the same feature.

  5. Review dependencies. Check for conflicting or unnecessary package versions.

  6. Trace the failing feature end to end. Follow the data through frontend, backend, and database.



How We Fix It

Root cause

Fix

Changes breaking other features

Fix the root cause across all affected files and restore consistent behavior

Invented or outdated code

Replace it with correct, current library and framework usage

Duplicated logic

Consolidate into one implementation that the rest of the app uses

Dependency conflicts

Pin compatible versions and remove unused packages

No safety net

Add type checks, focused tests for key flows, and a clean version control workflow

AI repeating mistakes

Add project rules and documentation that guide the AI toward your structure and conventions


You can keep using Cursor. We leave the codebase in a state where AI-assisted changes are much less likely to break existing features.



Example Fix


Situation: A founder built a customer onboarding app with Cursor. After a week of changes, sign-up and billing both broke, and asking the AI to fix them created new errors each time.


Cause: Three different versions of the user profile logic existed across the project, one using an outdated authentication pattern, and a suggested package upgrade conflicted with the payment library.


Fix: Restored a working baseline from version history, consolidated the profile logic into one module, corrected the authentication code, pinned compatible package versions, and added tests for sign-up and billing plus project rules for the AI.


Result: Sign-up and billing worked again, and the founder continued building new features with Cursor without breaking those flows.



How to Keep It From Happening Again

  • Commit working versions often so every AI change can be reviewed and reverted.

  • Add tests for your most important flows before asking the AI for big changes.

  • Give the AI project rules describing your structure, libraries, and conventions.



What You Get

  • Root cause explained in plain language

  • Broken features fixed and tested

  • Consolidated, cleaner code for affected areas

  • Tests and AI project rules to prevent repeats





Frequently Asked Questions


Why does Cursor keep breaking my code? 

The AI edits code with a limited view of the whole project, so changes can conflict with other files. Without tests, those breaks aren't caught until something stops working.


Why is the AI stuck repeating the same fix?

 It's often fixing a symptom while the real cause sits in another file, an outdated pattern, or a dependency conflict it can't see. An engineer reviewing the whole codebase breaks the loop.


Is it better to rebuild my app from scratch? 

Usually not for a specific broken feature. If the entire app is unstable or insecure, a project rescue audit is the better next step.


Can I keep using Cursor after the fix? 

Yes. We add tests and project rules so AI-assisted changes are safer and more consistent with your codebase.


Do you fix code from other AI tools too? 

Yes. We fix code written with Cursor, Windsurf, GitHub Copilot, Claude, ChatGPT, Lovable, Bolt, and similar tools.



Related Problems

  • AI-built app you can't ship

  • Lovable app not deploying

  • Bolt.new app throwing errors

  • Supabase auth not working

  • React state not updating



Break the AI Error Loop

Share the error or the feature that stopped working. Get a diagnosis and a fixed price.

Get Help Now




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