What is an AI agent evaluation harness?
An AI agent evaluation harness is the test and observability layer that scores an agent’s work step by step, replays any decision on demand, enforces policy at runtime, and logs evidence a risk team will accept. In this 28-minute recording, the engineering lead on our agents practice walks through the exact harness we build on every agentic engagement: LangGraph-backed state machines, multi-step task scoring, deterministic checkpoints, and the audit-evidence log that survived a tier-1 bank’s risk review.
It is the difference between an agent demo that impresses a Friday meeting and an agent program that clears Model Risk Management (MRM) and goes to production.
What does the video cover?
The session focuses on the four things every agent program needs before it reaches pilot review.
| Component | What it answers | Why risk teams care |
|---|---|---|
| Task-level metric definition | What does success mean per agent step, not per prompt | Catches failures buried inside a multi-step plan, not just the final answer |
| Deterministic replay | Can we reproduce any decision exactly | Lets reviewers re-run a flagged decision and see the same result |
| Runtime policy enforcement | Did the agent stay inside its authority | Encodes authority limits, jurisdictional gates, and human-in-the-loop checkpoints |
| Audit-evidence logging | Can we prove what happened, after the fact | Produces a schema MRM and audit teams find acceptable |
The recording shows each one running against a live LangGraph agent, not slideware.
Who should watch this?
This walkthrough is built for the people who have to sign off on an agent before it touches a customer or a ledger: AI engineering leads, heads of data science, MRM and model validation teams, and platform owners in regulated industries. If you have a working agent prototype and a risk review standing between you and production, this is the harness that closes that gap.
Where this fits
This is the harness behind Why AI Agent Pilots Fail and What to Build Instead, and it is part of every AI Agents engagement we run. If you are scoping an agent for production and want the evaluation layer designed in from week one, start with our AI Agents practice page.