Design a retrieval-augmented generation (RAG) system that actually returns grounded, correct answers — chunking, embeddings, retrieval, generation, and evaluation. Use when building RAG/search-over-docs, when a RAG system gives wrong or ungrounded answers, or asked "design a RAG pipeline", "why is my RAG bad", "chat over my documents". A comprehensive, end-to-end skill.
