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Proof capture

AI Workflow Sprint Proof Pack

A practical proof-capture checklist for measuring a Workflow Sprint without over-sharing client-sensitive detail.

What to capture before the sprint

Strong proof starts before any build work. Capture the workflow owner, baseline, data boundary, human review point, approved source material and the decision the sprint is meant to support.

  • Name one workflow and one accountable owner.
  • Record the current time, volume, backlog, rework or risk pressure.
  • Write down what material is in scope and out of scope.
  • Confirm the human review role before outputs are used.
  • Agree what evidence will decide scale, improve, pause or stop.

What to capture during the sprint

During delivery, keep proof close to the work. The aim is to show what changed, what remained uncertain and which controls made the test safe enough to inspect.

  • Current-state workflow map and source inventory.
  • Number of sample cases tested.
  • Before and after time or quality evidence.
  • Review notes from the workflow owner.
  • Risk, compliance or IT feedback where relevant.

What can be used publicly

Reusable proof should never expose confidential client details by accident. Named case studies, quotes and metrics need explicit permission; anonymised sector proof can still be useful when naming is not appropriate.

  • Separate internal evidence from external claims.
  • Use anonymised sector examples unless named permission is recorded.
  • Keep caveats beside every metric.
  • Do not imply regulatory approval or autonomous decision-making.
  • Turn approved evidence into a one-page proof asset for similar buyers.
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