Indexes a Python codebase at function granularity using AST chunking and FAISS, skips
unchanged files via file hashing on re-index, and compares two embedding models side by
side on the same query. grep finds text; this finds intent — and the re-index/hashing
logic is the same pattern real production search tools use to stay fast on large repos.
Demonstrates embeddings + vector search applied to a problem every engineer already has — a concrete talking point for Developer Productivity or Platform Engineer roles.