How do you evaluate report and deck agents when accuracy misses the real problem
Weekly_Quarter_7875 · reddit · 2026-07-28
A builder asks how to evaluate agents that generate decks or reports, where simple accuracy metrics miss the point. They compare three approaches: LLM-as-judge with a rubric, small human review sets, and mechanical regression checks for obvious failures.
The hardest problem is consistency: the same input can produce ten different structures, and that instability may matter more than factual correctness because users can’t build trust in outputs that change shape every run. The post asks whether a locked rubric judge is good enough, or whether a better metric exists for “would a human use this untouched.”
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