Guide

Evaluation harness guide for agentic AI

How to build evaluation harnesses for agentic AI workflows: golden sets, regression checks, and confidence thresholds.

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Production Signals
Reference only
67% Cycle Time Reduction (target)
94%
Accuracy Rate (target)
$ 1.2 M
Annual Savings (target)
4-6 wks Target to production
3 Approval gates
100% Audit traceability

Reference data shown for format only. Results vary by workflow, data access, and approvals.

Why evaluation matters

Why evaluation matters

  • Without regression tests, you cannot prove improvement.
  • Golden sets keep behavior stable as models change.
  • Confidence thresholds reduce unsafe automation.
What to include

What to include

  • Golden test sets
  • Edge case coverage
  • Human review sampling
  • Quality metrics aligned to KPIs
  • Weekly regression cadence
Operational use

Operational use

  • Tie evaluation output to approval gates.
  • Stop changes that fail acceptance thresholds.

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