When a RAG agent answers wrong, the model is rarely at fault: the right passage never reached the context. This article splits retrieval into three budgets that fail for different reasons — recall, precision, and passage context — and shows what fixes each one: structure-aware chunking, hybrid search with rank fusion, second-stage reranking, and retrieval measured separately from the answer.
A vector index is a copy, and a copy inherits no permissions: the Databricks AI Search documentation states that row and column level permissions are not supported. The two routes an agent takes to the data — RAG and text-to-SQL —, where the access rule lives on each one, the Genie Agent's two credentials, and the metric layer that stops the number from changing.
The memory types of an agent (short/long-term, episodic, semantic, procedural) and how to implement the retrieve/write-back loop in the Microsoft Agent Framework.