The Three RAGs
RAG is no longer one thing. By 2026, the term has fractured into three fundamentally different architectures: Pipeline RAG, Agentic RAG, and GraphRAG. Each solves a different class of problem. Each fails in predictable ways when applied to the wrong one.
Pipeline RAG is the canonical baseline: embed documents, store vectors, retrieve the top-k chunks, feed them to a model. It is optimized for single-hop, document-centric questions and low-latency requirements. The architecture assumes one search is enough. When that assumption holds — roughly 80% of enterprise queries — Pipeline RAG is fast, cheap, and good enough. When it does not hold, the system has no mechanism to recover. [1]
Agentic RAG replaces the static pipeline with a state machine. Instead of one retrieval pass, an autonomous agent decides when and how to retrieve, evaluates the results, and iterates if necessary. It plans, retrieves, reasons, critiques, rewrites, and reflects in loops until confident or until budget runs out. The power is self-correction. The risk is "self-correcting" into elaborate hallucinations without external verification. [2]
GraphRAG augments or replaces vector retrieval with a knowledge graph — a structured representation of entities and the typed relationships between them. Instead of matching query embeddings to chunk embeddings, the system traverses a graph: Symptom X is linked to Drug Y, which interacts with Condition Z. Multi-hop reasoning becomes explicit path traversal rather than hoping the right chunks land in the context window. [3]
Each architecture excels in its lane. The interesting question in 2026 is what happens when you need all three at once.
Where Vector Search Breaks Down
Vector similarity search finds documents that are semantically near the query. That works well for questions like "What is our refund policy?" or "Summarize this contract clause." It fails for questions that require reasoning across relationships.
Consider a compliance analyst asking: "Which suppliers share board members with companies under OFAC sanctions?" The answer is not in any single document. It lives in the connections between supplier records, corporate filings, and sanctions lists. A vector search will retrieve documents that mention sanctions and documents that mention board members, but it has no mechanism to traverse the relationship chain that connects them.