RAG Is Not an AI Agent

Short summary

RAG retrieves external knowledge to help an LLM answer questions accurately, while AI agents reason, plan, and take multi-step actions to solve problems. RAG follows a fixed retrieve-generate-respond pipeline, whereas agents use a dynamic reasoning loop with tool selection, evaluation, and retry logic. The most capable production systems combine both—agents decide what to do, and RAG supplies the right information to do it well.

• •RAG = LLM + external knowledge for accurate Q&A; no decision-making or action execution
• •AI agents = LLM + planning + tools + state for multi-step reasoning and task completion
• •Production systems should combine both: agents orchestrate actions while RAG provides trusted knowledge

Generated with AI, which can make mistakes.