/sentences/attention
Measure before optimize.
Measurement must establish a baseline before optimization begins, to avoid scaling noise.
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Optimizing a system without a robust measurement baseline is a recipe for scaling noise. We often rush to improve performance before we understand what normal looks like.
A reliable baseline tells us what the system does today. It registers the background noise, the normal variance, and the failure rates.
Only when we can measure consistently can we know if our optimization made a real difference, or if we just got lucky with a single test run.
What this changes in practice: before attempting to optimize any model prompt or pipeline, run a baseline evaluation on a stable benchmark dataset.