Agent Evaluation at Scale — How to Test and Measure Agentic AI Performance

What you will learn

Background

Why agent evaluation is harder

The four pillars of agent evaluation

Pillar 1 — Task Success

Pillar 2 — Tool Usage Quality

Pillar 3 — Reasoning Coherence

Pillar 4 — Cost-Performance Trade-offs

Building your evaluation pipeline

Step 1 — Build the golden dataset

Step 2 — Define success criteria per pillar

Step 3 — Choose your evaluation method

The five core metrics

Benchmarks to calibrate your expectations

The three pitfalls that kill evaluation efforts

Pitfall 1 — Evaluating on synthetic data

Pitfall 2 — Metrics that don't map to business outcomes

Pitfall 3 — Treating evaluation as a one-time setup

Putting it all together

Summary

References