GraphRAG or Agentic RAG? Choosing Based on Your Retrieval Bottleneck

A DEV Community article argues that choosing between GraphRAG and agentic RAG should depend on where a system's real problem lies, not on which approach is trendiest. It describes basic RAG as suited to simple fact lookup, advanced RAG as a way to improve retrieval quality through hybrid search and rerankers, GraphRAG for relationship-heavy multi-hop questions, and agentic RAG for tasks needing planning, tool use, and iterative loops. The author advises teams to start with advanced RAG and climb the architecture ladder only when metrics such as recall@k, groundedness, and task success show a gap. The piece notes that graphs add indexing and modeling cost while agents add latency and evaluation difficulty. It also stresses ongoing monitoring, since a degrading RAG system can mislead users before teams notice.