AI Code Audits Miss Entire Bug Classes Because They Sample the Same Semantic Space
When AI models audit code they generated, they are constrained to the same semantic neighborhood as generation and systematically miss entire categories of bugs. Rotating audit prompts orthogonally surfaces new bug classes at each pass, but no existing AI coding tool implements this. Large AI-assisted codebases have hidden quality floors that standard review prompts cannot reach.
Signal
Visibility
Leverage
Impact
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Problem descriptions, scores, analysis, and solution blueprints may be updated as new community data becomes available.