A very practical breakdown of RAG for business use cases. I especially liked the emphasis on data quality, permission-aware retrieval, hybrid search, and evaluation rather than treating the LLM itself as the main solution.

The point about starting with a focused workflow and measurable business metrics is particularly valuable. RAG implementations often succeed or fail based on retrieval quality, governance, and source freshness—not just model selection.

Great guide for teams looking to move from an AI proof of concept toward a production-ready RAG architecture.