Comparison
Agent vs Retrieval-Augmented Generation
Agent and Retrieval-Augmented Generation are both common AI/LLM terms but cover different ideas. Here is a quick side-by-side.
When you would reach for Agent
Agent comes up when the question is fundamentally about agents & tools.
Claude Code — coding agent that edits files, runs commands, runs tests.
When you would reach for Retrieval-Augmented Generation
When the model needs information that is not baked into its weights — fresh, private, or domain-specific.
"Chat with your PDFs" — Notion, Glean, ChatGPT custom GPTs.
Frequently asked
What is the difference between Agent and Retrieval-Augmented Generation?
Agent: An AI agent is an LLM-driven system that decides which actions to take, executes them via tools, observes the results, and iterates until a goal is met. Retrieval-Augmented Generation: RAG retrieves relevant documents from a corpus at query time and includes them in the prompt, letting an LLM answer with up-to-date, source-cited, private information without retraining.
When should I use Agent vs Retrieval-Augmented Generation?
Agent is the right concept when you are focused on agents & tools. When the model needs information that is not baked into its weights — fresh, private, or domain-specific.
Are Agent and Retrieval-Augmented Generation the same thing?
No. Agent is agents & tools; Retrieval-Augmented Generation is agents & tools. They are related but address different parts of the AI stack.