AI for Developers6 of 30 steps (20%)

Use Continue for a Large Codebase Refactor

Refactoring across many files is error-prone. Continue's codebase awareness helps you do it safely.

Prerequisites

  • Continue installed in VS Code or JetBrains
  • Ollama, LM Studio, or OpenAI connected
  • A codebase with a clear refactor goal

Step 1: Index the codebase

Continue indexes your project for context. Give it a moment to scan. For large repos, you may need to focus on specific folders.

Step 2: Describe the refactor

In the chat: "We're renaming [OldName] to [NewName] across the codebase. Update all references. Preserve behavior. List every file you change."

Or: "Migrate from [old library] to [new library]. Update imports, API calls, and tests. Run tests after."

Step 3: Review changes

Continue will suggest edits. Review each one. Check for: wrong renames, broken imports, missing updates. Accept or reject. Don't blindly apply everything.

Step 4: Use inline edit for targeted changes

For a single file, select the block to change. Cmd+K (Mac) or Ctrl+K (Win). "Replace this with the async version" or "Add error handling here." Faster than full-file edits.

Step 5: Run tests

After applying changes, run your test suite. Fix any failures. Continue can help: "The test X is failing. Here's the error. Fix it."

Tips

  • Break large refactors into smaller steps. "First update the core module, then the consumers."
  • Use local models (Ollama) for privacy if the codebase is proprietary.
  • Always run tests and lint before committing.
In the next step, you will explore the best AI tools for AI code review and refactoring. Browse the options, pick one that fits your workflow, and try it before continuing.

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