Databricks research shows multi-step agents consistently outperform single-turn RAG when answers span databases and documents

Databricks published research demonstrating that multi-step agent architectures consistently outperform single-turn RAG systems for complex retrieval tasks. The research shows agents excel when queries require integrating information across multiple databases and documents. The findings provide practical guidance for enterprises designing AI query systems.