RAG Is Simpler Than You Think

Most teams over-engineer Retrieval-Augmented Generation by jumping straight to embeddings and vector stores, even when simple keyword queries like “reset my password” dominate. Rafael outlines decision factors—data freshness, corpus churn, query type, query volume, and team expertise—and recommends starting with a pure BM25 full-text search (e.g., Elasticsearch or Postgres) for low-complexity, fast (<10 ms) retrieval before adding embeddings.