Writing Effective Evals Playbook

This playbook turns the chapter patterns into an operating loop: design, offline validation, pilot, production monitoring, and refresh. Because apparently shipping an LLM system once and never measuring it again remains frowned upon by reality.

Eval lifecycle from design through production refresh.

Five-minute triage

Good: The failure is tied to a named slice, a versioned dataset, and a threshold someone agreed to before the run.
Bad: The team debates whether the aggregate score feels fine, a famously precise scientific instrument.
Ugly: The production trace is partial, the user label is ambiguous, and the rollback owner is in a different timezone.

Lifecycle	Good pattern	Bad shortcut	Ugly escalation
Design	Risk-backed hypothesis	Metric shopping	Stakeholders disagree on failure
Offline	Golden and stress sets	One borrowed benchmark	Leakage suspected after launch
Pilot	Canary with thresholds	Big-bang deploy	Sample too small for confidence
Production	Drift and slice monitoring	Dashboard worship	Judge drift requires relabeling

Writing Effective Evals Playbook

Writing Effective Evals Playbook

Five-minute triage

Pattern menu by lifecycle