Optimizing Long Context Windows for Complex Codebase Analysis and Refactoring

Cursor's .cursorrules file is the secret weapon for stopping the LLM from hallucinating when you're deep in a 100k+ line codebase. Most people just dump their whole project into the context window and wonder why the AI starts suggesting deprecated API calls or missing imports. The reality is that "long context" doesn't mean "perfect recall"—the middle of the context window often gets blurred (the "lost in the middle" phenomenon).

To actually make complex refactoring work without breaking your build, I've shifted from "letting the AI find the files" to "curating the context map."

If you are doing a cross-module refactor—say, changing a data schema that affects five different services—don't just use @Codebase. It's too noisy. Instead, I create a temporary refactor-map.md file. I list the exact files involved and the logic flow:

# Refactor Scope: User Auth Migration
- Source of Truth: `src/auth/session.ts`
- Affected Consumers: 
  - `src/api/middleware/auth.ts` (needs update to JWT validation)
  - `src/store/userStore.ts` (update state persistence)
  - `src/ui/hooks/useUser.ts` (update return types)

Then, I reference this file explicitly: @refactor-map.md Please update the session logic across these files. This forces the AI to focus its attention mechanism on the specific dependency graph rather than guessing which files are relevant.

For the actual refactoring prompts, I've found that "incremental verification" beats "one-shot massive changes." If you ask Claude 3.5 Sonnet to refactor four files at once, it'll likely miss a type definition in the third file. My workflow now looks like this:

1. The Analysis Phase:
Ask for a plan first, but demand a "diff-style" explanation of changes before any code is written.

Analyze @refactor-map.md and tell me every single line that needs to change. 
Format as: [File] -> [Line X]: Change A to B. 
Do not write the code yet.

2. The Execution Phase:
Apply changes file-by-file. This prevents the context window from getting cluttered with "half-finished" versions of the code.

3. The Type-Check Loop:
Since I'm using TypeScript, I keep a terminal open with tsc --watch. The moment the AI pushes a change that breaks a type, I copy the error directly back into the chat. This is faster than asking the AI to "check for errors."

A major gotcha with long context is "context drift," where the AI starts following a pattern it invented five prompts ago rather than the actual codebase standards. To fix this, I add a "Strict Style" block to my .cursorrules:

{
  "style_guide": {
    "naming": "use camelCase for variables, PascalCase for components",
    "patterns": "Prefer functional components over classes",
    "error_handling": "Always wrap async calls in try-catch with custom AppError"
  }
}

This keeps the output consistent even when the conversation history gets long. By treating the context window as a curated workspace rather than a dumping ground, I've cut my "fix-the-AI-fix" loop time by about 40%.