Run Coding Agents in PDCA Loops
Use PDCA to structure an AI coding agent run so the work is planned, inspected, and improved instead of accepted blindly.
The control move: run the agent like a small improvement cycle, not like a magic patch machine. PDCA stands for Plan, Do, Check, Act. In a coding-agent workflow, Plan is the human framing: target behavior, files in scope, files out of scope, constraints, and tests. Do is the agent's implementation attempt. Check is your review of the diff, command output, and actual behavior. Act is the next decision: keep, revise, narrow, or revert. This works because agent mistakes are easiest to catch when the unit of work is small. A vague request invites broad edits. A broad edit creates too…
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