Pepe Alonso, a vice president of education for the AI Club at UC Berkeley’s Haas School of Business, is turning job displacement concerns into a teaching pathway. After AI technologies reduced the need for the engineering work he was doing, he enrolled in an AI master’s program while applying for an MBA—then built his candidacy around a perceived curriculum gap. Alonso’s teaching role spans business and technical courses. The article describes him as slated to teach a module in Haas’s Fundamentals of AI class, lead an elective, and co-instruct a section in an EECS course—reflecting an emerging hybrid pedagogy that mixes product and engineering context. The article frames the approach as a response to how internships and roles increasingly request machine learning experience rather than generic AI familiarity. It also situates the move in the Bay Area credentialing ecosystem, where applicants see MBA signaling as necessary even alongside technical depth. For higher education leaders, it signals how AI competency is reshaping classroom design, faculty expectations, and cross-department instruction in professional programs.