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LLM Evaluation Plan Template for AI Products
A structured template for planning and running LLM evaluations. Covers test case design, metric selection, and automated and human evaluation methods.
Updated 2026-05-09
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Frequently Asked Questions
How many test cases do I need?+
For an initial evaluation, aim for 200-500 test cases across all categories. For ongoing monitoring, sample 50-100 production outputs per week for human review. The exact number depends on your use case complexity. More categories and edge cases require more test cases.
Should I use automated metrics or human evaluation?+
Both. Automated metrics give you speed and scale. You can run them on every prompt change. Human evaluation gives you accuracy and nuance. It catches quality issues that automated metrics miss. Use automated metrics for rapid iteration and human evaluation for final quality gates.
How do I handle subjective quality dimensions like tone?+
Create a rubric with specific, observable criteria. Instead of "tone should be professional," define what professional means: "no slang, no exclamation marks, uses complete sentences, addresses the user formally." Calibrate raters by having them all score the same examples and discussing disagreements.
How often should I re-run the full evaluation?+
Re-run the full evaluation suite when: the model provider releases a new version, you make significant prompt changes, you observe quality degradation in monitoring metrics, or at least once per quarter as a routine check. ---
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