How do you design the triggers and cadence for retraining a fleet of production models?
Retrain too often and you burn money and risk regressions; too rarely and the model rots. The strong answer is a layered trigger policy with guardrails, not one cron job. Here is how to set the cadence.
Updated Sep 2026 · Grounded in real GenAI, LLM, and AI/ML engineering interview loops and written to a senior-engineer editorial bar.
Retrain too often and you burn money and risk regressions; too rarely and the model rots. The strong answer is a layered trigger policy with guardrails, not one cron job. Here is how to set the cadence.
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.
