An AI agent is a language model placed in a loop with tools. It does not only write a paragraph. It can decide to search, calculate, query a system, read the result, and then take the next step.
The loop
- Goal. The user states the outcome, such as “prepare the figures for this client review.”
- Plan. The model breaks the goal into steps.
- Act. It calls a tool: a calculator, a database query, a search index, or an internal API.
- Observe. It reads the tool’s result.
- Stop or continue. It either returns the answer or takes another step.
Tools versus the model
The model chooses which tool to call and how to phrase the call. The tool does the reliable work. Arithmetic belongs in a calculator. A balance belongs in the core system. A policy quote belongs in retrieval. Leaving those jobs to free-form generation is how agents invent numbers.
Guardrails that matter
- Allow only named tools, not open-ended actions.
- Keep a step limit so a confused loop cannot run forever.
- Require a person to confirm anything that moves money, sends a message, or changes a record.
- Log every tool call so the path can be reviewed.
A practical example
An analyst asks an agent for a client’s year-to-date fee income and a short note on whether it is above last year. The agent queries the warehouse for both years, computes the change with a calculator, and drafts three sentences. It does not invent the fee from memory.
What to remember
- An agent is a model plus tools plus a loop.
- Give precise facts and calculations to tools. Let the model plan and explain.
- Limit what the agent may do, and keep a human on actions that have consequences.
