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How do you evaluate a web-grounded decision API when the right answer changes with the web?

Fourteen of seventeen answers right looks fine until you split by stratum: every recently changed fact was wrong, with near-total confidence. The eval is a dated golden set, stratified by how facts fail on the web, re-verified before every run.

Updated Nov 2026 · Grounded in real Forward Deployed Engineer interview loops and written to a senior-engineer editorial bar.

Fourteen of seventeen answers right looks fine until you split by stratum: every recently changed fact was wrong, with near-total confidence. The eval is a dated golden set, stratified by how facts fail on the web, re-verified before every run.

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FEDITOR'S NOTE

An original exercise using measured calls to Parallel's Decisions API as the worked data, not a reported company interview. Score whether the candidate dates every label, stratifies by fact age, entity ambiguity and evidence availability, reports per stratum rather than one accuracy, and scores unknown as a correct outcome where the web does not establish the fact.

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