AI Agents Start With One Task: How to Build Them
If you are considering an agent that reads email, drafts documents, or compares schedules, begin with one repetitive task whose output a person can review. The core method is to allow only classification and drafting at first, then expand permissions or add agents after consistent evaluation records show that the tested scope meets acceptance criteria. The confusing part is that an agent is more than a model or a detailed prompt. Its inputs, decision rules, output structure, tool permissions, approval points, and execution records all affect whether it works safely. Choose the right structure for the work Use one-off chat for questions and brainstorming, and a fixed workflow when every step follows the same sequence. An agent becomes useful when the next action must change according to the goal and current situation. Autonomy is therefore a task requirement, not a goal to maximize. The article examines four practical roles. A coordination agent can classify email and prepare re...