8 min readUpdated September 22, 2026
How AI agents use tools
The loop that turns a language model into something that takes actions: tool descriptions, arguments, results, retries, and where supervision belongs.
AI Agents
An AI agent uses a model to choose actions through available tools. Follow the request-and-result loop and learn where human approval belongs.
Where should I start with ai agents?
Start with the guide that matches your question or the error you can see. Each guide below names the problem, gives checks you can run, and links to related reading.
How do you separate a proposed action from a completed one?
An agent saying 'I will save this' is not a storage receipt. In an illustrative workflow, the model requests a save, the tool times out and the interface still announces success. The reliable check is whether the action was accepted and the result can be read back, not whether the generated explanation sounds confident.
- 1Identify the tool the agent would need and the permissions it holds.
- 2Inspect success, rejection and timeout results before displaying completion.
- 3For a state-changing retry, use supported idempotency controls and check whether the original action completed.
Where should a person approve the action?
Put approval before an external write, purchase, deletion or public post, not after it. Give the person the actual destination and payload to review. A tool limit can also bound how many actions the agent attempts. The guide below explains the request-result loop; it does not promise that every agent or connected service enforces these protections automatically.
Read the ai agents guides
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