What happened
Drawing on 11 years as a 臨床工学技士, the author proposes six fields for AI agent approval logs: when, who, what target (tied to the action's content, per a hackernoon.com point), why it was stopped or held, what action was taken, and how it was restored with a next check date.
Why it matters
Git history tracks what was rolled back but not the reasoning behind it, so without a log format that records the 'why,' teams cannot reconstruct why a change was stopped a week later, the author argues.
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The piece builds on an earlier article by the same author that argued for smaller approval units and keeping a Git-restorable state. Here the focus shifts from where humans stop an agent to how the stopping and rolling back are documented.
The author's hospital background supplies the template: inspection records already require a written reason for each judgment, not just a note that a response happened. Mapping that to AI agents yields six fields, and the author notes that the earlier prescriptions fit into specific fields rather than replacing the log format.
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