RAG and Embeddings
Vector RAG from the ground up
Vector RAG from the ground up: why an LLM doesn't know your company's documents, how chunking and embeddings turn text into a map of meaning, and how retrieval puts the right pieces back in the prompt. Built around a real use case — consultants asking itenium anything — with four questions the naive pipeline gets wrong, and one that no retriever ever reaches.