The AI to Learn 2.0 framework targets proxy failure, where polished AI outputs mask a human's lack of actual understanding. It introduces a maturity rubric to distinguish between artifact and capability residuals in learning-intensive domains. This approach helps educators certify human skill despite generative tools. Practitioners can now better audit AI-assisted deliverables for genuine competence.