The DF score measures the operational pain of deploying software and AI systems by combining deployment speed, failure frequency, and rollback rates into one reliability metric. A high score signals brittle pipelines, weak testing, operational debt, and poor production readiness—problems that increasingly prevent enterprises from successfully scaling AI despite strong underlying models.