Running more AI agents can look productive without moving the work forward. Nate explains how to give agents useful assignments, recognize what deserves your attention, and stop recurring jobs once their purpose has passed.
The practical test is whether the results help you make a decision or solve the central problem. From checking a painting estimate to questioning a weekly update nobody reads, the examples show why more output is not always more progress.
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