The AI to Learn 2.0 framework targets proxy failure, where polished AI outputs mask a human's lack of actual understanding. Researchers propose a deliverable-oriented rubric to distinguish between the final artifact and the user's underlying capability. This provides a concrete method for educators to certify human skill in learning-intensive domains. It solves a critical assessment gap.