Your A/B test has interference between users (marketplace, social network). Why does it bias results and how do you fix it?
Standard A/B math assumes one user's treatment does not affect another's outcome. In marketplaces and social networks that assumption breaks and your estimate is biased. The signal is naming SUTVA and the right randomization unit. 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.
Standard A/B math assumes one user's treatment does not affect another's outcome. In marketplaces and social networks that assumption breaks and your estimate is biased. The signal is naming SUTVA and the right randomization unit. 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.
