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Many AI benchmarks use algorithmic scoring to evaluate how well AI systems perform on some set of tasks. However, AI systems often produce code that scores well but isn’t production-ready due to issues with test coverage, formatting, and code quality. This helps explain why AI tools show less productivity improvement than expected despite strong performance on coding benchmarks.
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