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Versioning and Staleness

Know when correctness objects changed and when old evidence may need review.

Versioning and Staleness

Definition

Versioning preserves the exact artifact state used by an earlier decision or evaluation. Staleness is the signal that current evidence, configuration, or interpretation may no longer support the same claim after a related object changes. A stale signal routes review; it does not automatically delete an artifact, invalidate every historical result, or approve a replacement.

Why it matters

Cases, Policies, Rubrics, Benchmark Versions, Harness Versions, and Improvement Session goals can change independently. Named versions keep old evidence interpretable. Staleness helps teams decide which current Datasets, evaluator links, Runs, or customer-owned human review context need attention before being treated as current.

Where it appears in the product

Use the owning object page to inspect its current version and activity. Use Dataset Snapshots and Benchmark Versioning for immutable evaluation boundaries. Use Staleness Detection to identify downstream artifacts affected by a change. Use Conflict Resolution when expert or source evidence disagrees about what the new governed state should be.

Artifacts it affects

Common triggers include changed Case input or materials, revised Policy scope, revised Rubric criteria, changed dataset membership, changed Harness configuration, and superseded source material. The responsible next action depends on the owner: correct a Case, approve a new standard version, refresh coverage, create a new Snapshot, run a new evaluation, or preserve an old result as historical context.

Comparison Directions use a narrower stale signal. Potentially stale is an advisory label for untouched AI-suggested directions, not a versioned approval state and not automatic removal. User-created and user-edited directions remain user-owned even when Teammately considers them while avoiding duplicate suggestions.

Operational check

Name the changed artifact and version, identify which downstream claim depended on it, and decide whether the old evidence remains historically valid, requires qualification, or needs replacement through a new canonical workflow. Never “resolve” staleness by editing a label while leaving the evidence boundary ambiguous.

When the object is a Comparison Direction, also check whether a Potentially stale label is only advisory. Dismiss the label if the team decides the direction still represents a useful boundary.

Worked example

Revised applicability after evaluation

Experts revise a Policy so it applies only when the customer explicitly requests a recommendation. Runs against the old Benchmark Version remain valid evidence under the former applicability rule. The current Dataset and linked Rubrics are reviewed, a new Snapshot and Benchmark Version establish the revised boundary, and new Runs use it. Any customer-owned human review context names both boundaries instead of marking every old result simply “wrong.”

Source confidence

Code-backed: current Policy and Rubric types preserve versioned governance facts, Snapshot routes preserve immutable benchmark evidence, and Comparison Directions expose a deliberately narrower advisory stale label. Cross-object staleness remains a review and routing decision, not an automatic global state transition.

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