What is CUPED, why does it shrink experiment variance, and how does it compare to stratification and regression adjustment?
CUPED can halve the sample size an A/B test requires without touching validity. The signal is explaining why subtracting a pre-experiment covariate reduces variance yet never biases the estimate. Here is the answer.
Updated Sep 2026 · Grounded in real GenAI, LLM, and AI/ML engineering interview loops and written to a senior-engineer editorial bar.
CUPED can halve the sample size an A/B test requires without touching validity. The signal is explaining why subtracting a pre-experiment covariate reduces variance yet never biases the estimate. Here is the answer.
Lead with where the obvious approach breaks, because that is the judgment they are screening for — most candidates jump straight to the happy path and lose the room.
Then walk the failure back through the pipeline in order, naming the one metric the customer's exec sponsor actually cares about before you propose the fix.
