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Where human approval belongs in an AI workflow

Human judgment

For engineering and governance leaders

Automation is most useful when people retain the decisions that change scope, accept material risk, or release work into production.

Put approval at consequential boundaries

A person should approve the question being asked before a broad review begins. After findings arrive, a person decides which risks block launch, which can be accepted, and which need more evidence. A release decision should remain visible and attributable.

These checkpoints do not require a person to repeat every automated step. They protect changes in authority: widening scope, accessing sensitive systems, accepting risk, merging code, deploying, or declaring work complete.

Ask for evidence that fits the decision

An approval is only useful when the reviewer can see what changed and why. Give the reviewer the relevant finding, source evidence, proposed action, test result, and known limitation. Keep the request narrow enough that a real decision is possible.

Launch Check supports the first decision by presenting prioritized findings. The planned Mission Control conversion service will carry selected findings into tracked missions. Human approval remains part of deciding what enters that workflow and when the mission is complete.