Rag

Sometime in early 2025, “prompt engineering” stopped being the term people used and “context engineering” took its place. Like most renamings in this field, it was half marketing and half a genuine shift in what the work actually is. The marketing half is noise. The genuine half is worth understanding, because it names a real engineering problem that I spend a meaningful fraction of my time on. This post is about the real part: what context engineering is when you treat it as engineering rather than as a LinkedIn phrase. ...

RAG is architecturally simple: chunk documents, embed them, store in a vector DB, retrieve the top-k on query, pass retrieved context to an LLM, return answer. The demo takes an afternoon. The production system takes months, because “works on the demo documents” is nowhere near “answers correctly 95% of the time across the full document corpus.” This post is about the gap between those two states. ...