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Agentic RAG and GraphRAG: When Classic RAG Is Not Enough

Classic RAG handles most questions whose answer sits in one place; on multi-hop questions an agent that uses retrieval as a tool found the right source but spent 3 calls, 11 times the tokens and 30 times the time. GraphRAG's first step produced fragmented entities with a small model, and long context with the whole corpus in the prompt tied classic RAG at 7/10.