Stop Evaluating LLMs with “Vibe Checks”

Relying on subjective 'vibe checks' to evaluate LLMs is a core reason enterprise AI projects fail to scale. A decision-grade evaluation scorecard must measure five dimensions: accuracy, reliability, latency, cost, and business decision quality. Building a golden dataset of diverse inputs and expected outputs enables automated regression testing across all five dimensions. The evaluation pyramid spans unit, integration, system, and decision levels — most teams stop at unit. The LLM-as-a-Judge pattern automates nuanced output grading but requires periodic human calibration. Finally, evaluation must continue in production via traffic sampling, dashboards, and automated alerts to catch model drift and data distribution shifts.