I spent years building RAG systems at Redis, and now I spend my days building agents at Arcade. So I get this question a lot: “Should I build RAG or an agent?” The honest answer is that they aren’t competitors - they solve different problems. RAG is about search. Agents are about action.

RAG Makes Models Better at Answering

Retrieval Augmented Generation does one thing extremely well: it gives a model the right context at inference time. You embed your knowledge, retrieve the most relevant pieces for a query, and stuff them into the prompt so the model can answer with information it was never trained on.

If your problem is “the model needs to know something it doesn’t” - your docs, your tickets, your codebase - RAG is the right tool. (If you want the deep dive on the retrieval half, I wrote a whole post on vector embeddings from the basics to production.)

Agents Make Models Capable of Doing

An agent’s job isn’t to answer better - it’s to act. Send the email, open the PR, update the CRM, schedule the meeting. The moment your requirement contains a verb that changes the state of some external system, you’ve left RAG territory and entered agent territory.

And the hard part of acting isn’t reasoning - it’s everything around the tool call:

  • Tools have to be real. A tool is code: it needs to be packaged, versioned, and tested like code, not bolted on as an afterthought.
  • Authorization is the wall most agents hit. To act as a user across services, the agent needs scoped, per-action permission - the problem Arcade exists to solve.

How to Choose

A simple heuristic:

  • Need the model to answer using your knowledge? Build RAG.
  • Need the model to do something in the world? Build an agent - and give it secure tools.

The most capable systems use both: retrieval for what the agent should know, and secure tool calling for what the agent should do.

I expanded on this argument on the Arcade blog: RAG vs AI Agents: Why Search Isn’t the Same as Action.

For more about Arcade check out the website at https://www.arcade.dev/ and the GitHub https://github.com/arcadeai/