用智能开发工具加速音乐软件创作，降低门槛并提升兼容性。
Case Studies and Reflections on Agentic Software Engineering for Rapid Development of Digital Music Instruments
- 用AI辅助重构经典音乐软件，实现跨平台原生插件化。
- 三例实践表明开发效率显著提升，且代码可维护性增强。
- 适合非程序员音乐人与独立开发者快速构建音频应用。
本文探讨了智能软件工程（ASE）在创新音频软件开发中的应用。针对数字音乐乐器开发中存在的持久性、互操作性及入门门槛高等问题，文章回顾了近期ASE进展，指出其有望降低开发门槛并提升软件寿命与兼容性。随后通过三个案例展示：案例1将Laurie Spiegel的Music Mouse重写为原生插件；案例2将Pachet的Continuator系统从Python移植至原生插件；案例3使用OpenGL为现有tracker sequencer开发全新3D界面。作者基于自传式记录的提示日志与开发快照，分析人类开发者在过程中的体验，总结出有效实践，并建议未来对非程序员音乐人开展方法评估。
原文摘要 · Abstract (English)
The article explores the use of agentic software engineering (ASE) in the development of innovative audio software. It begins with a review of background work that lays out the challenges of longevity, interoperability and barriers to entry in digital music instrument creation, explaining recent developments in ASE and highlighting the possibility that ASE can lower barriers to entry and facilitate creation of interoperable software with greater longevity. Following that, we present case studies wherein we used ASE technology in three distinct ways to develop audio software in the C++ language with the JUCE framework. In case study 1, we re-implement Laurie Spiegel's `Music Mouse' software as a native plugin. In case study 2, we translate Pachet's `Continuator' system from Python into a native plugin. In case study 3, we develop a new 3D user interface for an existing `tracker' sequencer using OpenGL. We describe the experiences of the human developer in the case studies via autoethnographic discussion of the prompt logs and snapshots of the software as it was developed. We identify effective practice for ASE use in this domain and suggest future steps for the work involving evaluation of the method with non-programmer musicians.
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