Source: https://www.codebuff.com/docs/advanced/large-projects

Working with Large Projects

In general, Codebuff works quite well in larger projects. For example, we've pulled Codebuff into the VSCode repo (millions of lines of code) and have had no issues in our testing. That said, if you're noticing Codebuff getting stuck/forgetting context too soon or using a ton of credits, here are some tips to help you mitigate those issues.

Directory-Based Approach

When working with large codebases, you can start Codebuff from specific directories to maintain focus:

bash

cd backend

codebuff

Or equivalently without changing directories:

bash

codebuff --cwd backend

This helps Codebuff concentrate on relevant files and provide more targeted assistance.

Knowledge Organization

For large projects:

Create separate knowledge.md files in key directories, like so:

text

services/

auth-service/
```
knowledge.md

src/
```
user-service/
```
knowledge.md

src/
```
api-gateway/
```
knowledge.md

src/
```
Focus each knowledge file on its directory's specific concerns
Link related concepts across knowledge files
Keep root knowledge.md for project-wide concepts

Effective Communication

When working with large codebases:

Be specific about file locations
Reference related files explicitly
Break large changes into smaller, focused requests
Use the --max mode for better context understanding by loading more files

Performance Tips

Leverage your .codebuffignore and .gitignore files to exclude irrelevant directories
Start in subdirectories when possible
Break large refactoring tasks into smaller chunks
Let Codebuff handle file discovery instead of listing all files

What models do you use? Codebuff vs Claude Code

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