INSIGHTS
Evaluation Harnesses for Agent Reliability
Measurement, regression detection, and risk signals for agent systems in production.
Reliability is not a vibe—it is a set of measured properties. An evaluation harness is the bridge between “it ran” and “it was correct enough for this context.” I build harnesses that teams can run in CI and in production shadow mode, so regressions surface before users do.
What to measure
Start with task-level outcomes: did the workflow reach a valid terminal state? Then layer quality metrics: groundedness, citation accuracy, tool-call correctness, latency percentiles, and cost per successful task. Separate “model quality” from “orchestration quality”—both can fail independently.
Add safety-specific metrics where relevant: policy violations blocked, PII exposure attempts, and escalation triggers fired. Those belong in the same dashboards as quality, not in a separate spreadsheet nobody opens.
Golden sets and regression
Curate a frozen set of representative inputs with expected properties—not necessarily single “right” answers for generative steps, but checkable structure: required fields, forbidden actions, maximum cost. Run them on every change that touches prompts, tools, or routing.
Rotate in fresh examples from production (with consent and redaction) so the set does not age into irrelevance. Track pass-rate trends over time; a slow decline often precedes a user-visible incident.
Production signals
Pair offline evaluation with live monitors: escalation rates, human override frequency, and downstream error correlation. When those drift, the harness should tell you whether the model, retrieval, or business rules moved.
Shadow runs—execute new versions beside production without committing outputs—let you compare metrics before cutover. The pattern is standard for services; agents deserve the same discipline.
Ownership and cadence
Name who curates datasets, who approves harness changes, and how often you run full suites versus smoke checks. Without ownership, harnesses rot. Through Jomiko I often embed evaluation criteria in the same release checklist as API contracts.
If you cannot measure it, you cannot ship it with confidence. I help teams wire evaluation into the architecture—not as an afterthought report.
If you want help applying this to your architecture, book a strategy call or an architecture review.
Tags: evaluation · agents · reliability · observability