Part 3A: Enterprise RAG Architecture & Codebase Vector Indexing
Answer-first: Off-the-shelf “plug-and-play” vector search solutions fail on enterprise codebases because they treat source code like narrative prose. A production Enterprise Codebase RAG combines layout-aware AST symbol parsing, Hybrid Search (Dense Embeddings + Sparse BM25 via Reciprocal Rank Fusion), and Cross-Encoder Reranking, achieving sub-400ms retrieval latencies and raising code search precision from 54% to 92.4%. 📖 Bản tiếng Việt (Vietnamese Edition) | ← Series Hub | Next Chapter: Part 3B: AI Automation for Internal Operations → ...