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FrontierCode exposes a large gap between what current AI models can produce and what open-source maintainers would actually accept, with even the top-ranked model scoring only 13.4% on the hardest subset — a concrete signal that existing benchmarks have been overstating model readiness for production codebases.
Practitioners building with AI coding agents should evaluate success by software quality and usability — not lines of code or generation speed — as raw output becomes trivially cheap to produce.