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AI Coding Agent Caught Silent Gap in Product Spec Before Any Code Was Written

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A developer running paired AI coding experiments found that a minimal product requirements document for a task app specified High/Medium/Low priority badges but never explained how a task could be set to High or Low. An unassisted Claude Code agent built the app as specified, defaulting every task to Medium and leaving no way to change priority — a flaw invisible to casual testing since Medium is a valid value. A second build using a structured 'grilling' pre-coding pass called GuardianKane caught the ambiguity before any code was written, prompted a deliberate design decision, and locked it into a browser test. The gated build passed an explicit-priority test that the baseline failed, not because it was smarter, but because it was forced to resolve the gap upfront. The experiment highlights how one-shot AI builders tend to satisfy a spec as literally written rather than flag missing requirements, a behavior the author argues any engineer — human or AI — exhibits when told simply to 'build this.'

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