Software engineers are increasingly relying on AI tools like DORA's AI products, with 90% of tech professionals using them to boost productivity. While AI automates tasks like testing and code generation—enabling even novices to prototype via vibe coding—it also introduces instability, as software delivery instability rises with more AI use.

A Multitudes study found engineers merged 27.2% more code packages but logged 19.6% more after-hours work, signaling burnout risks. The pressure to leverage AI for efficiency is pushing developers to work longer, often during breaks, as companies expect higher output without mandating tool use.

Anthropic research revealed AI-assisted developers scored 17% lower on post-task quizzes, particularly in debugging. Overreliance on AI may hinder skill growth, as engineers skip deeper problem-solving, risking long-term expertise gaps.

As AI redefines productivity, workplaces must balance efficiency gains with safeguards against burnout. Without structural support, the tech could exacerbate stress, turnover, and skill stagnation, undermining the very innovations it promises.