open-world-evaluations

This paper argues that traditional benchmarks both overestimate and underestimate frontier AI capabilities, and proposes 'open-world evaluations'—long-horizon, real-world tasks assessed qualitatively—as a complementary approach. The CRUX project is introduced, with a demonstration where an AI agent successfully published an iOS app to the App Store with minimal intervention.