RAG Is Simpler Than You Think
Summary
RAG Is Simpler Than You Think outlines six approaches to retrieval-based AI, from MVP full-text search to full embedding. It covers decision factors such as data freshness, corpus characteristics, query patterns, scale, and team capabilities, and then presents six recipes: MVP with full-text search; agentic query rewriting; hybrid sparse plus dense reranking; on-the-fly embedding; pre-embedding with hot and cold tiers; and full pre-embedding. It also discusses multi-intent queries and a practical decision tree for choosing the right approach, including cost and latency considerations.