Ask vs Act: RAG, Tool Use and AI agents

Ask vs Act: RAG, Tool Use and AI agents Series: Part 3 of 5 — CQRS and architecture for AI agents. Reading time: ~6 min. In the previous article we covered CQRS fundamentals and practice in Elixir with Queries and Commands. Here we apply that split to AI agent orchestration: Ask (RAG, read) vs Act (Tool Use, commands). The "Ask vs Act" paradigm: CQRS in AI agent automation Applying the CQRS pattern proves not only beneficial but mandatory in orchestrating workflows driven by AI agents. When dealing with autonomous Artificial Intelligence, the distinction between observing the environment (Perception) and interacting with it (Action) mirrors the Query vs Command split. Treating knowledge retrieval the same way as corporate action execution is a serious mistake. An agent’s architecture must have two distinct ducts, shaped by CQRS. The query side: RAG, reasoning and vector stores When an AI agent needs information to plan its next steps or answer a question, it operates on the read path (