Are we measuring AI coding ability wrong?

Current AI coding benchmarks rely on pass/fail metrics that overlook code quality aspects like readability, fragility, and maintainability. The author proposes five programmatic views—reliability, verbosity, complexity, specialization, and writing clarity—to better evaluate AI-generated code beyond simple scores.