A field guide to agents that act
A small map for building an agent
Start with the job, then decide what the system may observe and change. The useful distinction is not whether a model sounds conversational; it is whether it selects actions across a workflow.
Name the work
Write down the outcome and the point where a person takes over. OpenAI’s guide describes an agent as a system that manages workflow execution, chooses tools and can recognize completion or return control. For a bounded task, a fixed sequence may be easier to inspect than open-ended planning.
Sources: A practical guide to building agents · Agents
Draw the boundary
List every tool, the data each tool can read, and whether it can write or trigger an external effect. The Model Context Protocol specification separates tool discovery from tool invocation; that interface does not itself grant safe authorization. Apply ordinary identity, access and confirmation controls around consequential actions.
Sources: Model Context Protocol specification · AI Risk Management Framework
Make failure visible
Record the request, selected tool, arguments, result and stopping reason. Give the agent a clear failure path: ask, retry within a limit, or stop. Judge the whole task against expected outcomes, including wrong actions and recovery, rather than judging only the final prose.
Sources: A practical guide to building agents · Agents
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