Retrieval-augmented generation is an excellent tool for knowledge lookup. It is the wrong tool for enforcing architectural decisions. The distinction matters — and most teams building AI coding workflows haven't confronted it yet. When teams first encounter the problem of governing AI-generated code, RAG is the intuitive answer. You have a set of architectural decisions — ADRs, style guides, internal wikis, team conventions — and you want your AI coding assistant to respect them. RAG can retrieve relevant documents and inject them into the prompt. Problem solved, apparently. It isn't. The mismatch between what RAG provides and what architectural governance requires is deep, and fixing it requires a different kind of system entirely. What RAG is actually good at RAG excels when the task is: given a query, find the most semantically relevant passages from a corpus and surface them to the model. It works well for: Documentation lookup — "How does our auth middleware work?" retrieves the relevant design doc.…