AI重塑软件工程权力结构，资深者掌控主导权，新人需引导。
From Junior to Senior: Allocating Agency and Navigating Professional Growth in Agentic AI-Mediated Software Engineering
- 通过三阶段研究对比新手与老手使用AI的差异
- 组织政策限制了编码自主性，资深者靠详细指令保持控制
- 适合关注AI时代职业成长与团队协作的开发者
新手以AI为天然工具入门，资深者则在职业生涯中适应AI。AI不仅改变编码方式，更重塑了工作中的决策权分布。我们通过三阶段混合方法研究：结合ACTA与5位资深者的德尔菲法、10名新手的AI辅助调试任务，以及另5位资深者对新手提示历史的盲审。研究发现，软件工程中的自主权主要受限于组织政策而非个人偏好；资深者通过详尽的任务分解保持控制，而新手则在过度依赖与谨慎回避间挣扎。资深者凭借过往经验有效引导现代工具，并具备指导新人早期AI融合发展的独特优势。基于研究结果，我们提出三项实践建议，聚焦于在代码编写、学习和导师指导中持续保留人类主导权，尤其当AI日益自主时。
原文摘要 · Abstract (English)
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.
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