Rag Architect

Looking at this one, you're getting help designing retrieval augmented generation systems from the ground up. It walks you through the architecture decisions that actually matter: how to chunk your documents, which embedding model makes sense for your use case, whether you need hybrid search or can get away with pure vector similarity, and how to structure your retrieval pipeline. Useful when you're past the POC stage and need to build something that won't fall apart when you move from a dozen test documents to production scale. The guidance skews practical rather than theoretical, focusing on tradeoffs you'll actually face when implementing RAG rather than just explaining what it is.