The article explores the shifting dynamics of design careers in the context of AI advancements, particularly the rise of Large Language Models (LLMs). It highlights a growing concern among designers regarding their professional identities, emphasizing a trend toward generalization in the field. This shift contrasts with the previously dominant focus on hyper-specialization, which has created silos that hinder communication and collaboration among design disciplines. The author cites a piece from the Nielsen Norman Group that suggests a resurgence of the UX generalist role as AI tools take over various tasks, potentially allowing designers to diversify their skills. However, the author argues that while generalization may seem beneficial, it risks superficiality and stifles innovation. Designers may rely too heavily on AI, delegating responsibilities without truly understanding the underlying principles. This reliance can lead to a disconnect where designers produce outputs without the necessary depth of knowledge or expertise. The article warns that such a scenario could create professionals who are superficially skilled but lack a comprehensive grasp of their craft, ultimately undermining the quality of design work. The author reflects on the effects of hyper-specialization in the design field, which has led to fragmented communication and a lack of cross-disciplinary understanding. They highlight three major axes of specialization: communication, empirical-scientific, and technical. These divisions contribute to a production line mentality that isolates expertise, creating barriers to effective collaboration. The emergence of AI presents both opportunities and challenges, prompting professionals to reconsider their roles and the potential implications for their careers.