If your AI system isn't producing outputs at the level you're expecting, you might be looking at some serious complications down the line. When automation systems scale up and machine learning models become more sophisticated, small flaws in output generation can cascade into major operational failures. The difference between a properly calibrated AI response and a faulty one could be the gap between smooth operations and catastrophic breakdowns as these technologies become more integrated into critical systems. It's worth double-checking your model outputs—especially if you're betting on them for anything important.