How AI agents are evolving RAG systems from keyword search to iterative, reasoning-based search experiences

Summary

The article discusses how AI agents are transforming traditional RAG (Retrieval-Augmented Generation) systems by moving beyond simple keyword search APIs. Unlike conventional search that relies on query understanding and reranking, agents can reason about search results, iteratively refine their queries, and zero in on the best terms to find what they need—similar to how human users search. The piece highlights that agents need simple, understandable tools like keyword search, which they can then reason about, evaluate, and iterate upon to deliver more compelling search experiences.