How big should a golden set be?

Start small but diverse; grow with failure analysis, not random volume.

Blog · AI

LLM evaluation playbook for product teams

Published 2026-02-02 · 10 min read

Golden sets, online metrics, human review, and regression gates—how to evaluate LLM features like mature software.

Curate representative tasks with expected properties—not only “happy answers.” Include refusal cases and ambiguous prompts.

Track task completion, human edits, escalation rates, and cost per successful task.

Block releases when offline metrics regress; pair with shadow traffic for risky changes.

How big should a golden set be?: Start small but diverse; grow with failure analysis, not random volume.

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