AI时代开发者需掌握四大领域技能以应对变革
What do professional software developers need to know to succeed in an age of Artificial Intelligence?
- 构建4大能力域：有效使用生成式AI、核心软件工程、邻近工程与非工程知识
- 提炼出12个工作目标与75项任务，覆盖6步开发流程关键节点
- 建议教育与培训聚焦软硬技能，防止技术淘汰
生成式AI已初现提升软件开发效率的迹象，但对劳动力替代与技能退化的担忧仍存。我们对21位前沿使用AI的开发者展开研究，总结出12个工作目标、75项相关任务及对应技能知识，揭示开发者在实际工作中如何运用AI。基于这些发现，提炼出5条核心洞察：成功的人工智能增强型开发者需在四个领域（有效使用生成式AI、核心软件工程、邻近工程、邻近非工程）部署能力，贯穿于六步任务工作流的关键节点。为帮助开发者‘未来化’，在职学习项目与计算机科学学位课程需同时强化‘软技能’与四大领域的技术知识，实现再培训、能力升级并防范技能退化。
原文摘要 · Abstract (English)
Generative AI is showing early evidence of productivity gains for software developers, but concerns persist regarding workforce disruption and deskilling. We describe our research with 21 developers at the cutting edge of using AI, summarizing 12 of their work goals we uncovered, together with 75 associated tasks and the skills & knowledge for each, illustrating how developers use AI at work. From all of these, we distilled our findings in the form of 5 insights. We found that the skills & knowledge to be a successful AI-enhanced developer are organized into four domains (using Generative AI effectively, core software engineering, adjacent engineering, and adjacent non-engineering) deployed at critical junctures throughout a 6-step task workflow. In order to "future proof" developers for this age of AI, on-the-job learning initiatives and computer science degree programs will need to target both "soft" skills and the technical skills & knowledge in all four domains to reskill, upskill and safeguard against deskilling.
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