Your model is live at a customer. What do you monitor, and how do you catch drift before the customer does?
Models don't crash, they decay quietly while dashboards stay green. The four-layer monitoring stack, data vs concept drift with PSI numbers, and the label-lag problem that makes naive accuracy monitoring useless.
Updated Aug 2026 · Grounded in real Forward Deployed Engineer interview loops and written to a senior-engineer editorial bar.
Models don't crash, they decay quietly while dashboards stay green. The four-layer monitoring stack, data vs concept drift with PSI numbers, and the label-lag problem that makes naive accuracy monitoring useless.
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.
