From RAG to agents: architecting grounded AI

Retrieval-augmented generation solved the hallucination problem for many knowledge use cases. Agents extend it with tools, memory and multi-step planning.

Start with retrieval quality: chunking, hybrid search and re-ranking matter more than model choice.

Add tools deliberately, each with strict schemas, permissions and audit logging.

Orchestrate with frameworks like Google ADK or Bedrock Agents, and keep humans in the loop for consequential actions.