AI Operations · Glossary
Annotation Workflow
The Annotation Workflow is the structured process by which domain experts label production traces against authored evaluation criteria, generating the labelled corpus that feeds the autonomous improvement loop.
The autonomous improvement loop requires fuel. The fuel is labelled production traces. The workflow that produces them is the Annotation Workflow.
The workflow is structured. Traces are sampled against authored sampling rules. Domain experts review samples, label outcomes against the evaluation criteria, and flag candidate refinements. Co-Pilot consumes the labelled corpus, surfaces patterns, and drafts refinement proposals for the Human Governance Gate.
The workflow is not bulk labelling. Bulk labelling produces noise. The Annotation Workflow is selective: traces are routed to the domain experts whose authoring scope covers the policies and routines in question. The labels feed the policies the labeller owns.
Without the Annotation Workflow, the autonomous improvement loop runs on whatever traces happen to be visible. With it, the loop runs on the traces that matter, labelled by the people accountable for the underlying policies.