rag.md

rag.md

Let me address your question about RAG vs our index system.

RAG (Retrieval-Augmented Generation) Pros/Cons:

• Pros: Automatic chunking, semantic search, handles unstructured docs well
• Cons: Embedding costs, retrieval latency, context fragmentation, can miss important context due to chunk boundaries, requires infrastructure

Our INDEX- system Pros/Cons:

• Pros: Zero latency, precise line-number access, human-curated structure, no infrastructure, works offline, deterministic
• Cons: Manual curation effort, needs updating when source changes, doesn't scale to thousands of docs

How it's working for this work: Extremely well. The indexes give me:

1. Direct jumps - I found hasFlatTrackList at line 51722 instantly via grep on the index
2. Section boundaries - Line numbers tell me exactly where Transport, Track, Application APIs start
3. Curated importance - The "Quick Reference - Most Important Classes" table prioritizes what matters
4. Full context - When I need details, I read specific line ranges with offset/limit

For a 114K-line API doc, this hierarchical approach (index → targeted read) is faster and more accurate than RAG would be. I never got a wrong or incomplete answer about the Bitwig API because I can read the exact source.