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The AI forgets how my app works and breaks other features

VC-08CursorClaude CodeLovableUpdated October 2026By

Quick verdict

Partly fixable yourself. Write a knowledge file and shrink each task.

How serious
Medium
Fix it yourself?
Partly, some steps need a developer
Typical cost
$49–$800 one-off check, or $1,500–$15,000 for cleanup (prices)
Top rated for Cursor
Afterbuild Labs · 10.0/10

What you see. Every new feature the AI adds breaks an older one, and it rewrites code it already wrote.

Why it happens

AI tools do not remember your app between sessions. Each chat starts with a context window, a limited working memory that holds your messages and the files it reads. Anthropic's own guidance says performance degrades as that window fills and the model may start forgetting earlier instructions. Lovable, Cursor and Claude Code all hit this wall on apps with many files.

So the agent reads a few files, guesses how the rest works, and writes code that duplicates or contradicts what exists. Over weeks you get two copies of the same component, three ways of fetching users, and fixes in one copy that never reach the others. Each platform offers a standing instructions file for exactly this: Project settings → Knowledge in Lovable, .cursor/rules or AGENTS.md in Cursor, and CLAUDE.md in Claude Code. Most vibe coded apps never fill one in.

Fix it yourself

  1. Write a short map of your app: what it does, the main tables, where sign-in and payments live, and which files must not change. Keep it under a page.
  2. Lovable: paste it into Project settings → Knowledge. Cursor: save it as AGENTS.md in the project root. Claude Code: run /init and edit the CLAUDE.md it creates.
  3. Start a new chat per task. Claude Code recommends /clear between unrelated tasks, and Cursor recommends a new chat when you switch features.
  4. Ask for one feature per prompt and name the files allowed to change. Add a line such as do not touch authentication or payments.
  5. Before approving, ask the agent what existing code the change shares with other features, as Lovable's debugging guide suggests.
  6. Ask the agent to list duplicate components and dead files, then remove them in a separate, tested step.

When to get an engineer

If the codebase already has several copies of the same logic, a knowledge file will not fix the past. An engineer can map the app, remove duplicates and add tests around the flows that make money, so the AI has guardrails. That cleanup and hardening costs $1,500–$15,000 and takes 1 to 8 weeks depending on size. A one-off check first, at $49–$800, tells you which it is. See codebase too messy to continue.

Top-rated companies for Cursor apps

Ranked by our score: published prices, scope of work, AI tools named, timing and a low-risk first step. How we score.

  • 1Afterbuild Labs10.0/10Best for: A check before launchFree first step · from $49
  • 2Redlab10.0/10Best for: A full rescue by one team that keeps buildingFree first step · from $490
  • 3Vibe Code Rescue (Lev Arakelyan)9.0/10Best for: A one-off check and a cleanupFrom $299

All 58 Cursor companies, ranked

Check these

CODE-02Medium

The flows that make money have tests

Sign-up, checkout and the core action. A few end-to-end tests catch most regressions from new prompts.

CODE-03Medium

Dead code and duplicate components are removed

Search for components with near-identical names. Three versions of one button means three places to fix every bug.

CODE-01High

The code lives in a Git repository you own

Connect GitHub or export the project. If the builder account is lost, the product should not be.

CODE-04Medium

Dependencies are current and audited

Run npm audit. Critical advisories in packages you ship should be fixed before launch.

Questions

Is a bigger model the answer?

Not by itself. The limit is the context window and how much of your app fits in it. A clear knowledge file, smaller tasks and fewer duplicate files help more than switching models.

How long should the knowledge file be?

Short. Cursor says keep rules under 500 lines, Lovable allows 10,000 characters, and Anthropic warns that a bloated CLAUDE.md gets ignored. Include only what the AI cannot infer from the code.

Sources: Claude Code: Best practices; Cursor: Rules; Lovable: Workspace and project knowledge; Lovable: Debug and improve your app.