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How do you design consent and data-retention policy for data that feeds ML training?

Consent and retention decide whether you can legally train on data and how long you keep it. The signal is purpose limitation, granular consent, enforceable TTLs, and a story for deleting data already baked into a model. Here is the answer.

Updated Aug 2026 · Grounded in real Applied AI Engineer interview loops and written to a senior-engineer editorial bar.

LEARN THE BACKGROUND

These lessons teach the material this question tests, in order and from the beginning.

Agent Engineering·Seeing inside a runSign in12mWhat to keep, what to drop, and what you must not store at allFull traces are the most useful thing you can keep and the most expensive, and they are a copy of your customers' data in a second system. Sampling that keeps the runs worth having, retention that survives a slow complaint, and the redaction that has to happen before anything is written.

UP NEXT ON YOUR JOURNEY

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