Rag Engineer

This is your go-to for building retrieval systems that actually feed useful context to LLMs. It focuses on the unglamorous but critical stuff: semantic chunking that respects document structure instead of arbitrary token counts, hybrid search combining BM25 with vector similarity, and hierarchical retrieval for better precision. The sharp edges section is genuinely helpful, calling out real problems like fixed-size chunking breaking sentences and the mistake of skipping reranking. If you're building anything that needs to retrieve relevant information from a knowledge base before generating responses, this gives you practical patterns to avoid the common pitfalls that lead to hallucinations.