When to Keep Rejected AI Work as Correction History

Deleting every bad attempt produces a clean folder and a forgetful process. Keeping every attempt produces clutter that obscures the useful lesson. Retain a rejected artifact when it explains a material correction that could recur. Label the defect, its source basis, and the artifact that replaced it. The relevant Owned AI Workbench component is “A second look at the result.” A visible finding gives the rejected artifact a specific lesson instead of an unexplained warning label.

Reader decision: Decide whether to label one rejected artifact with the lesson it preserves.

Published 2026.08.09 · 3 minute read

Give rejected work a strict admission test

An earlier attempt belongs in correction history when all three conditions hold:

The defect affected accuracy, scope, or a consequential decision.
The reason for rejection can be stated from evidence.
Future work could benefit from seeing the boundary.

Discard trivial formatting experiments unless their differences matter to a later choice. The purpose is memory, not accumulation.

Attach the lesson to the evidence

Do not save a rejected file with only “bad” in its name. Record the contested statement, the source examined, the finding, and the replacement.

W3C PROV-O can express derivation relationships between artifacts. The NIST AI Risk Management Framework emphasizes documented risk-management activity across an AI system's use. CommonMark supports durable, readable annotations beside the work.

Together, those ideas support an inspectable correction trail. They do not turn the synthetic statement into real workshop information.

Mark the version a reader should use

The synthetic corrected brief becomes current only after the finding and correction choice identify it as the version to use.

Keep the collection small enough to teach

This approach fits recurring work where the same evidence mistake could return. It adds noise when an abandoned artifact has no identifiable consequence or lesson.

Independent review decides whether a claim is supported. Correction history answers a different question: which rejected result should remain available after that decision?

Connect correction to durable memory

The parent guide, Keep AI Work in Files You Control, explains why the record should survive one session. Mark the Current AI Work Artifact protects readers from choosing the rejected version. Record Provenance for AI-Assisted Work captures the relationships around the correction.