Quality gate
- Inputs and outputs are schema-validated
- Failures remain visible
- High-impact cases require approval
- Logs support diagnosis
- A person can pause and recover the workflow
OUTCOME / AUTOMATION
Build a bounded AI automation with a human review gate
A working monitored workflow that knows when to stop and hand an uncertain case to a person.
THE HANDOFF
What “finished” contains.
- Finished files
- Working automation
- Input and output contract
- Exception queue
- Run log
- Stop conditions and operator SOP
- Smallest honest proof
- Run at least ten historical cases and document every failure before allowing the workflow to touch live work.
PRODUCTION ROUTE
Four steps to a credible first version.
AI can accelerate production. The route still includes source truth, correction, usability and a final human approval.
- Map the manual route
Document inputs, decisions, exceptions and the exact point where a correct result can be checked.
- Constrain the model
Use structured output, allowed values and explicit refusal conditions instead of a free-form autonomous prompt.
- Add observation
Record inputs, outputs, model version, failures and operator decisions without exposing sensitive data.
- Test historical cases
Run normal, edge and failure examples; route uncertain or high-cost cases to human review.
First-version effort
6–12 hours for a tested bounded workflow
Possible starting stack
An automation platform, a chosen AI model, a data store and an operator review surface.
QUALITY AND EVIDENCE BOUNDARY
Automation begins after the manual route is understood. Uncontrolled autonomy is not a shortcut to reliability.