Local LLM file scans strain context

This is not a product announcement, but it captures a real developer workflow problem: brute-forcing huge file dumps into an LLM is usually worse than building a deterministic search/indexing layer first.

• –For 500MB of small files, ripgrep, Python parsers, embeddings, or lightweight RAG should narrow evidence before any model sees context.
• –The useful LLM role is synthesis and gap analysis after exact search, not replacing file traversal.
• –Local models remain attractive for privacy-sensitive code/config audits, but context limits and hallucinated coverage make verification essential.