The premise is simple: compiled knowledge is more reusable than retrieved fragments.
RAG became the default answer to a straightforward question - how do I give an LLM access to external knowledge?



And the usual architecture is by now familiar.
Take documents, split them into chunks, embed the chunks, store them in a vector database, retrieve...