Understand the workflow.
A data warehouse can contain more text than a team can inspect by hand. The useful question is often consistent and narrow: identify sentiment, apply a domain label, or extract a repeated signal.
Define the quality bar.
Define the label set before evaluating the model. Review rare categories and disagreement rows separately. Agreement between models is a diagnostic signal; it is not ground-truth accuracy.
Improve the route.
Use reviewed examples and corrections to train a specialist for the repeated labeling task. Compare it with frontier controls, inspect failures, and refine the rubric where labels are ambiguous.
Keep frontier capability.
Spend frontier capability on hard cases, adjudication, rubric repair, and control sampling. Let the specialist handle the portion that has a stable definition.