Abstract
<jats:p>AI coding tools are now firmly embedded in engineering teams toolkits. What is still up for debate is what this means for how engineers grow and whether the productivity gains come with a cost. This chapter draws on experience leading larger teams through the shift to AI, and it looks closely at one tension that kept showing up along the way: the AI tools accelerating output today may be quietly eroding the foundational skills teams will need when things go wrong. A framework is offered for thinking about which skills to protect, which to build through AI collaboration, and which to hand off entirely. It covers hiring, career development, team dynamics, and the harder question of what makes an engineer valuable when AI can generate the code. This chapter does not seek to reassess the merits of AI adoption but instead aims to support engineering managers in navigating the transition while preserving long-term capability alongside near-term productivity gains.</jats:p>