The customer can't randomize, every user must get the new model. How do you measure whether it worked?
Enterprise reality: legal, fairness or ops constraints kill the A/B test, but the exec still demands proof of impact. The quasi-experimental toolkit, and the honest caveats, that let you answer anyway.
Updated Aug 2026 · Grounded in real Forward Deployed Engineer interview loops and written to a senior-engineer editorial bar.
Enterprise reality: legal, fairness or ops constraints kill the A/B test, but the exec still demands proof of impact. The quasi-experimental toolkit, and the honest caveats, that let you answer anyway.
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.
