More output is creating more work to check
AI-assisted output has increased, but so have incidents, review time or rework. Existing weaknesses may be contributing. AI can also introduce new errors and failure modes.
The immediate priority is to limit harm and recover safely.
Contain the problem first
Slow or pause affected automation when necessary. Restrict permissions, reduce the scope of changes and restore a known working state where appropriate. Establish who can stop the system and who owns recovery.
Do not keep increasing output while the organisation cannot reliably review it or recover from failures.
Find out what the checks missed
Examine failed changes and compare them with the evidence used to approve release. Do tests check the required behaviour? Can you see what happened? Are permissions limited to the task? Can a small change be reversed safely?
An agent reporting completion does not answer those questions. Verification needs evidence from the result.
Reintroduce changes with evidence
Agree acceptance checks, human review boundaries, monitoring and recovery steps. Start with a limited change and examine what it proves before increasing the scope.
We do this work with your engineers, on your estate. The first investment may be in tests, permissions or recovery before further AI automation.
Read AI Agents Lie About Being Done for the distinction between a completion claim and evidence of completion.