AI Is Making It Harder for Junior Developers to Get Hired (www.finalroundai.com)

October’s layoff numbers and a new Harvard analysis together show a structural shift in hiring driven by generative AI: TrueUp counted ~20,657 tech layoffs in October 2025, and a Harvard study of 285,000 U.S. firms (62 million workers, 2015–2025) found that once companies adopt generative AI, junior employment falls ~9–10% within six quarters. The change isn’t mostly mass firings but a freeze on entry-level hiring — after late 2022, adopters hired roughly five fewer junior workers per quarter — and it spans tech, finance, healthcare, manufacturing and services. Routine onboarding tasks (debugging, testing, data wrangling) are increasingly automated, letting senior engineers plus AI tools replace the throughput previously provided by junior teams. For the AI/ML community this matters beyond headcount: it’s eroding the apprenticeship pipeline that produces future engineers who understand systems end-to-end, maintain models, and steward safety and robustness. Short-term efficiency (one senior + AI doing work of several juniors) masks a long-term talent shortfall, weaker institutional knowledge, and fewer people learning how models fail in real-world settings. Recruiters and managers now hire for immediate control and productivity rather than potential, so mitigating strategies — structured apprenticeships, funded mentorship, open-source entry points and policy incentives to preserve entry-level roles — will be critical if the field wants to avoid a future with powerful tools but too few experienced people to guide them.