Shadow testing is underrated. Though even shadow testing has a blind spot. If your candidate model has side effects (like triggering downstream API calls or writes), you can't truly "shadow" it without extra isolation. Learned this the hard way.
Shadow Testing Candidate Models: Addressing Side Effects in AI Deployment
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