Rubric evaluation is how teams move from “vibes-based” LLM testing to repeatable AI quality checks.
Traditional assertions work when output is exact. GenAI outputs are open-ended, so quality needs a scorecard: dimensions, scoring scale, and clear score descriptions.
Use rubrics when you need to evaluate tone, factuality, empathy, compliance, conciseness, safety, or any behavior that cannot be checked with a simple string match.
Save this if your team is building LLM apps and needs a cleaner way to measure quality.
Follow @devengoratela for practical AI engineering breakdowns.
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