HOW AGENTIC RAG WORKS

Summary from the TLDR Dev newsletter

Standard RAG is a one-shot pipeline: query in, retrieve, generate. However, it breaks down the moment a question is ambiguous, the answer is spread across multiple sources, or the retrieved chunk looks relevant but isn't. Agentic RAG fixes this by adding an LLM in the middle that can rewrite the query, route to the right source, evaluate whether what came back is actually good enough, and loop again if not.