Evolution of Medical AI: Understanding the transition from Narrow AI to Agentic systems and the resulting implications for clinical workflows, administrative automation, and patient-provider interactions. Cognitive Frameworks for Augmentation: Utilizing the "Centaur vs. Cyborg" behavior models to distinguish between human-led and system-led tasks. Students will apply the DEFT-AI (Diagnosis, Evidence, Feedback, Teaching) framework to bridge the "Leap of Faith" required when incorporating AI outputs into clinical decision-making. Safeguarding Professional Expertise: Identifying and mitigating the "Shortcut Trap" and the associated risks of "deskilling." The curriculum emphasizes maintaining foundational diagnostic skills in an environment of high-level automation. Ethics and Accountability: Navigating various criteria for trustworthy AI, addressing historical and representative bias in training data, and defining the professional responsibility of the physician as the ultimate accountable party in the AI-human clinical team.