I have been thinking a lot about agent loops lately.

Not just prompts. Loops.

Plan. Act. Inspect. Revise. Verify. Continue.

That sounds powerful, and it is. But the more I use AI systems this way, the more I think the missing product skill is not only designing the loop. It is designing the stopping rule.

When should the agent keep going?

When should it ask for more context?

When should it run another check?

When should it stop because the work is good enough?

When should it stop because the problem is unclear?

When should it stop because the next step requires human judgment?

A loop without a stopping rule can create a lot of activity that feels like progress.

It can revise, reformat, re-run, re-check, and re-plan forever. That may look productive, but it can also hide the absence of a clear quality bar.

The human job is not to prompt every step.

But the human still has to define what good means.

That is the part I want to get better at: not only asking AI to do work, and not only building loops that can continue without me, but designing loops that know when continuation is no longer the right answer.

The future is not just autonomous agents.

It is accountable loops.

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This writing reflects my personal perspectives on product management, AI, and content discovery. It does not represent the official position of my employer or any affiliated organization.