Agentic RAG: Let the Agent Search

Agentic RAG improves upon traditional retrieval methods by transforming the process into an iterative search-read-decide loop. This advanced approach equips an AI agent with tools to search documents, read the findings, and decide if it needs to search again to gather more evidence. The agent can then piece together a comprehensive response from multiple sources, much like a human researcher investigating a complex question. While powerful, this method introduces considerations around agent autonomy and tool design, and may not be necessary for tasks that don't require iterative retrieval.