Who Will Become the Next Senior? How Generative AI Erodes the Development Pathway in Software Engineering

Generative AI (GenAI) is reshaping software engineering, raising concerns about how the development pathway through which juniors become seniors is being eroded. While macro statistics show a decline in junior hiring and controlled studies demonstrate the effects of AI on individual task performance, the mechanisms through which GenAI reshapes early-career development in real organizational and educational contexts have not been thoroughly examined. Through 14 semi-structured interviews with juniors at the threshold of entering software engineering and senior software engineers in South Korea, analyzed using Reflexive Thematic Analysis, we reveal a foundational pattern of Absorption—GenAI redirects entry-level work into senior–AI workflows—and three consequences: (1) juniors losing the productive struggle through which expertise once developed; (2) the structural reproduction of this loss through collective normalization of GenAI use in university classrooms; and (3) the perceptual asymmetry between seniors and juniors that prevents either side from correcting these dynamics on their own.

Introduction. The advent of generative AI (GenAI) has transformed software engineering at unprecedented speed. Tools like GitHub Copilot, ChatGPT, and Claude now perform substantial portions of code generation, debugging, and documentation that were frequently assigned to entry-level engineers. Concurrently, junior developer hiring has contracted sharply. In the United States, entry-level postings at the fifteen largest U.S. technology firms fell 25% between 2023 and 2024 (Brynjolfsson, Chandar, and Chen 2025), and programmer employment declined 27.5% between 2023 and 2025 (Rak 2025). In South Korea, major technology companies have largely suspended open recruitment of junior software engineers, shifting to experience-based ad hoc hiring (Lee 2025). At the individual level, GenAI clearly accelerates developer productivity (Brynjolfsson, Li, and Raymond 2025; Peng et al. 2023; Cui et al. 2026). At the collective level, however, this raises one underexamined question: if entrylevel work is no longer reaching junior engineers, who will become the next generation of seniors?

Discussion / Conclusion. Absorption and Unprotected Pathway According to our findings, the mechanisms through which GenAI affects the skill development pathways of juniors can be summarized as follows: not only has GenAI taken over the entry-level tasks that previously supported the growth of juniors in the workplace, based on senior participants’ accounts, but the skills that seniors—who currently use GenAI in their work—believe juniors should possess are also being hindered due to juniors’ use of GenAI in university, based on junior participants’ accounts, thereby widening the gap between seniors and juniors. We go one step further to argue that these mechanisms did not arise solely due to the emergence of GenAI, but rather that they have been added onto the already unprotected development pathway of juniors. Senior participants in this study described their own developmental trajectories not as the product of formalized training, but as the incremental accumulation of hands-on work that, in retrospect, was not systematized (Begel and Simon 2008).