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Adoption · Operating decision guide

Can the operations team run the AI workflow without its builder?

Otomat editorial · Revised 4 November 2026

Ask a primary operator and a backup to handle a new case, reject a bad input, and restore a known version without the builder touching the controls.

  • Let the backup drive
  • Interrupt a plausible task
  • Restore service and preserve the record

Let the backup drive

Use an approved test environment and an unfamiliar case. Hand the backup the runbook and the same permissions they will have on shift. The builder observes silently. Note every time the operator needs a private chat, undocumented credential or verbal cue. Each interruption identifies a dependency.

Interrupt a plausible task

Suppose a supplier sends an amended document while a draft is awaiting approval. Can the operator identify the stale source, stop the action and route it for review? A correct answer pasted into chat is weaker evidence than a visible hold in the actual workflow. Do not introduce faults into a live customer process for this exercise.

Handover witness sheet
DecisionEvidence to bringWhat would change the decision
Normal caseAccepted output, role and versionBuilder intervention means the step was not independently completed.
ExceptionDenied action plus a trace to the reviewerA notification with no receiving owner leaves the task unresolved.
RecoveryKnown version restored; safe task passes againA rollback command without a verified result is still an open test.

Restore service and preserve the record

Return to the approved version and run a known safe task. Keep the version, access role, timestamps and exception notes together. If the primary succeeds and the backup needs privileged help, record partial handover and retest with a fresh case.

Use the working tools

Blank templates are ungated. Adapt them to the workflow; inputs are not submitted.

  • Open the operating charter

Sources and limits

These are Otomat’s proposed operating methods and original decision artifacts. External references inform risk management; they do not certify this method or establish client results. Linked sources were selected for this review; their live revision dates may change.

  • NIST AI Risk Management Framework: risk management context

For anonymous documentation and proposal patterns, see delivery evidence and its boundaries.

Related decisions

  • AI training that proves independent task performance
  • AI-agent permissions: define the data and action boundary

Bring a workflow to the discussion

Share the business goal and constraints through the mandate process. Do not send sensitive production data in the initial brief.

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