What reviewers should catch
Human review is most valuable when it targets specific risks: invented facts, policy overreach, wrong tone, broken structure, missing uncertainty, and commitments the company has not approved.
- Check source-grounding before checking polish.
- Mark the failure type so future prompts and guardrails improve.
- Escalate repeated failures back to evaluation, not just individual correction.
When review can be lighter
Internal summaries, labels, and low-risk drafts may use sampling review after the agent has shown stable performance. Customer-facing and regulated outputs should require stronger review gates.
A useful metric
Track repair time per output. If review takes almost as long as writing from scratch, the workflow is not yet ready for automation.
How to reuse the method
evaluation methodology can become a small internal evaluation. The point is not to create the largest task set. The point is to cover real work, real risk, and real output formats.
- Define unacceptable failures first.
- Prepare representative samples next.
- Compare candidates with one shared rubric.
What evidence to keep
Save the input, prompt version, model version, run date, raw output, human rating, and failure tags. This makes future retesting and stakeholder review much easier.
Pre-launch checklist
Before using this method in production, run a small retest with real inputs, edge cases, and a plan for what happens when the agent fails.
- Is there a clear human-review rule?
- Are model version and evaluation date recorded?
- Which outputs are not allowed to be sent or written automatically?
- Is there a fallback path when the agent fails?
A practical next step
If you are evaluating this method, start with ten real samples: three normal cases, three edge cases, two high-risk cases, and two cases with strict language or formatting requirements. Run two or three candidate agents and compare quality, repair time, and critical failures.