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Production-to-eval loop

Turn real failures into immutable framework-native regression artifacts with governance — not silent copy-paste from production into a Softprobe DSL.

Steps

  1. Observe — Online policy or manual selection identifies a failed production trace (or session)
  2. Annotate (optional) — Humans attach scores to the relevant observation (span); see Annotation
  3. Snapshot — Capture evidence with consent, redaction, sensitivity tags
  4. Propose — Candidate FrameworkDefinition (or runner/env/gate) change with derived_from lineage — still framework-native files
  5. Review — Human or independent policy approves exact digests
  6. Publish — Immutable FrameworkDefinition joins the regression pack
  7. Activate — WorkflowVersion / gate references updated in an authorized action
  8. Gate — Next agent build must pass the expanded workflow

Authorization

ActionWho
ProposeHumans, AI agents (with audit)
Approve / publish / activate gateConfigured human or policy — not self-approval by proposing agent
RollbackServer RBAC with immutable audit

Approval binds exact content digest; any mutation invalidates it.

Relationship to Testing

Java record/replay cases in Testing remain separate. Eval artifacts may reference trace IDs as lineage without merging replay mock semantics into eval workflows.

See Evaluation loop.

Zero code changes · Full-context visibility · Cost optimization