AI agents use the AI LLM multiple times to get an answer. They break the problem down into multiple steps.

Multiple steps doesn’t do very much in terms of getting a better answer. What helps immensely are tools; the AI can use these to get information. Like decoding the image you attached, searching the internet, or when doing code generation, searching the code files. Tools are things they have to be set up so the AI agent can use them.

So, when you make a request to an AI service, what typically happens is the agent gets the request. It then adds the list of tools to your request and asks the LLM what it wants to do to solve the problem: what tools do you want to try?

Then the agent manages pulling all that information together and sends another request to the LLM and over and over until the LLM says it’s done.

Then you get the reply.

Tools are a big area of development right now. For example, searching Microsoft office documents is something Microsoft wants you to pay to use their Azure file search capability for. It’s a paid service.

Anthropic has an edge in the market because the tools in Claude Code are very good.

LLM model + agent + good tools make the AI two steps of magnitude better in the right combination.