RAG answers; an agent acts
RAG finds relevant passages in an approved knowledge base and provides them to a model for a grounded answer. It fits policies, instructions, contracts and technical documentation.
An agent adds tools: creating a record, checking status, triggering a workflow or preparing data in another system. Each tool increases both value and risk surface.
Choose the minimum sufficient autonomy
If users need information, begin with retrieval. If they repeatedly perform the same action after an answer, add an approval-based tool. Increase autonomy only after stable measurement.
- Retrieval: read only
- Prepared action: human approval
- Bounded action: allow-listed operations
- Autonomous loop: low-risk scenarios only
Keep the architecture observable
Both approaches need source versions, request logs and quality criteria. Agents also require records of tool calls, parameters, results and the user identity behind the action.
Choose between RAG and an agent after modelling the process, not from the popularity of a technology label.