
Agentic RAG vs Traditional RAG: When Agents Should Control Their Own Retrieval
Traditional RAG retrieves documents and hopes the top-k chunks contain the answer. Agentic RAG wraps that retrieval step inside an autonomous agent that can reformulate queries, check multiple sources, grade its own results, and decide when it has enough information to respond. This post breaks down the architecture of both approaches, shows where traditional RAG fails, and maps out when the added complexity of agentic RAG is worth it.








