Design agent feedback around goals, observations, bounded actions, verification, and correction. Use control-theory concepts to examine stability, observability, and the limits of automation.
Decide which agent observations may become durable memory, procedures, or training data. Build qualification, evaluation, release, and revocation paths that preserve evidence without automatically approving the lesson.
Control which feedback becomes a persistent change and who may approve it. Use promotion manifests, scoped evaluation, traceable release decisions, and tested withdrawal paths.
Prevent retries and corrective actions from amplifying an incident. Define retry ownership, finite budgets, stabilization rules, and reconciliation for actions whose outcomes remain unknown.
Verify the outcome of an agent action beyond the tool response. Separate acceptance, configuration, convergence, and service evidence, then test the conditions that could produce a false success report.
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