KM4BI

Are Your AI Agents Doing Real Work—or Just Performing Productivity? Four Principles for Managing Them

Agent productivity depends on the human work they create and the attention they consume, not just their output.

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Count the work after the output

A deliverable matters only if someone can use it. Include the time needed to read, verify, and make decisions about it. When an estimate affects a price or commitment, asking the agent to show its calculations helps focus review on what matters.

Explore before committing

Agents can investigate different explanations for a problem, but their proposals are not decisions. If the available data cannot explain why customers leave, conversations with those customers may provide the missing evidence.

Stop work when its purpose expires

A recurring update can continue long after the underlying decision has changed. Set a time limit or explicit stopping rule up front so temporary curiosity does not become permanent overhead.

Protect human attention

A coordinating agent should understand a person’s commitments and priorities, then surface only what genuinely deserves attention. More agent output cannot replace the human choice of what is worth pursuing.

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