Build guide

How to build an AI agent

Build an AI agent by defining one clear job, mapping the needed inputs and tools, setting approval points, and testing against real examples. Start with a narrow workflow. Measure whether it completes the job accurately, safely, and with less human effort.

Reviewed August 29, 2026

1. Define the job and the finish line

Write the job in one sentence. Name the trigger, required inputs, result, and person who reviews it. A clear finish line makes tool choice and testing much easier.

2. Choose the model and tools

Pick a model that can handle the task and budget. Add only the tools the agent needs, such as search, a database, email drafts, a CRM, or code access.

3. Add instructions and examples

Give the agent clear rules, expected output, and a few examples of good work. Include what it must never do without review.

4. Put review before risky actions

Require approval before sends, purchases, account changes, or other actions that are hard to reverse. Log the inputs, tool calls, and result so failures can be traced.

5. Test real and difficult cases

Use routine examples, missing data, conflicting instructions, and tool failures. Check the quality of the result and the agent's behavior when it cannot finish.

6. Measure the job

Track completion rate, review time, corrections, cost, and failures. Improve the weak step before adding more work.