AI coding agents often fail in production environments due to a 'Forced Continuity Defect,' as they operate on continuous calculus principles while software relies on discrete, cliff-like logic. Unlike smooth transitions, software has abrupt changes like overflows or fatal errors, which LLMs struggle to predict. This inherent misunderstanding of discrete system behaviors leads to unexpected crashes at critical moments, even with extensive training data.
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