An AI vulnerability analysis circulated by former OpenAI engineer Andrej Karpathy reignited debate about which occupations are most exposed to automation and what universities should teach. Karpathy’s visualization—based on Bureau of Labor Statistics categories and later removed by the author—showed high‑pay professions scoring worst for exposure, prompting career‑services and curriculum teams to reassess how they prepare students for rapid automation. Separately, reporting that a majority of resumes are screened by automated systems has academic implications: career centers must teach students to translate credentials into machine‑readable formats and emphasize uniquely human skills. Campus employers relations, alumni networks, and placement offices are weighing changes to internships, microcredentialing, and experiential learning to keep graduates competitive.