Juniors enter as AI-natives, seniors adapted mid-career. AI is not just changing how engineers code-it is reshaping who holds agency across work and professional growth. We contribute junior-senior accounts on their usage of agentic AI through a three-phase mixed-methods study: ACTA combined with a Delphi process with 5 seniors, an AI-assisted debugging task with 10 juniors, and blind reviews of junior prompt histories by 5 more seniors. We found that agency in software engineering is primarily constrained by organizational policies rather than individual preferences, with experienced developers maintaining control through detailed delegation while novices struggle between over-reliance and cautious avoidance. Seniors leverage pre-AI foundational instincts to steer modern tools and possess valuable perspectives for mentoring juniors in their early AI-encouraged career development. From synthesis of results, we suggest three practices that focus on preserving agency in software engineering for coding, learning, and mentorship, especially as AI grows increasingly autonomous.

翻译：初级工程师以AI原生代的身份进入行业，高级工程师则在职业生涯中期适应了AI技术。AI不仅改变了工程师的编程方式——更重塑了谁在工作中及专业成长过程中掌握能动性。我们通过三阶段混合方法研究，呈现了初级与高级工程师关于使用具身AI的叙述：结合5名高级工程师的德尔菲法进行ACTA分析、10名初级工程师的AI辅助调试任务，以及另外5名高级工程师对初级工程师提示历史的盲审。研究发现，软件工程中的能动性主要受组织政策而非个人偏好所制约：经验丰富的开发者通过精细化委派保持控制力，而新手则在过度依赖与谨慎回避之间挣扎。高级工程师凭借前AI时代的基础直觉来驾驭现代工具，并拥有指导初级工程师在早期AI赋能职业发展中所需的宝贵视角。基于结果综合，我们提出三项实践建议，重点关注在编码、学习与指导环节中维护软件工程的能动性——尤其是在AI日益自主化的趋势下。