RAG vs Agents: When to Use Which (With Real Examples from Our Stack)
TL;DR — RAG answers from documents. Agents take actions. Most real systems use both: RAG provides context, agents act on it. The hard part isn’t picking one — it’s knowing which layer of your problem belongs to which pattern. Why This Comparison Matters Right Now Two things happened in the last six months that make this comparison less academic than it used to be. First: coding agents crossed a quality threshold around November 2025. Simon Willison’s five-minute PyCon talk describes it as the moment agents went from “often-work” to “mostly-work” — usable as daily drivers, not just demos. The “best model” title changed hands five times between Anthropic, OpenAI, and Google in a single month. ...