Proof after generation

When code is abundant, explanation is scarce.

AI can create plausible behavior quickly. The durable asset is knowing what was accepted, rejected, challenged, and proven.

Control problem

Generated behavior without evidence becomes operational folklore.

A screen exists. A rule exists. A workflow branch exists. The hard question is whether anyone can still explain why it exists, who accepted it, and what reality has challenged it.

Proof after generation

Evidence should survive the prototype.

  1. Generated behaviorCandidate intake workflow
  2. Accepted behaviorSupervisor approval must move earlier
  3. Reality CheckPermission model and document-store probe
  4. Production telemetryException path monitored after release
  5. Traceable decisionWhy the rule exists remains inspectable

Accepted is not the same as deliverable.

A Build to Learn artifact can be persuasive and still be wrong. It may express the right business flow while hiding architectural risk, security obligations, data quality gaps, integration failure, accessibility constraints, auditability, performance, or operational support.

This is why RDD does not stop at stakeholder acceptance. Accepted behavior is useful evidence, but it must be challenged before it becomes production confidence.

Orphaned behavior is the new waste.

Orphaned behavior

A dashboard persists because it was easy to generate and nobody remembers who needed it.

Evidence-backed behavior

A supervisor queue persists because Evidence E-031 ties it to observed work and a delivery decision.

Code still matters. It simply becomes less credible when separated from the evidence that explains and validates it.

Reality Checks are records too.

Check RC-029

Settlement adjustment auditability

Objective
Prove the accepted workflow can retain before/after settlement evidence.
Acceptance criterion
Every adjustment carries actor, reason, source document, and timestamp.
Method
Audit scenario review with compliance and data engineering.
Status
Passed with one data lineage risk
The point is not to trust the prototype. The point is to learn from it, challenge it, and carry forward what survives.

Return to the method

See how proof starts in Build to Learn and is challenged through Reality Checks before delivery hardens.