Generative Artificial Intelligence (GenAI) models are achieving remarkable performance in various tasks, including code generation, testing, code review, and program repair. The ability to increase the level of abstraction away from writing code has the potential to change the Human-AI interaction within the integrated development environment (IDE). To explore the impact of GenAI on IDEs, 33 experts from the Software Engineering, Artificial Intelligence, and Human-Computer Interaction domains gathered to discuss challenges and opportunities at Shonan Meeting 222, a four-day intensive research meeting. Four themes emerged as areas of interest for researchers and practitioners.
@article{arxiv.2602.07412,
title = {Forecasting Developer Environments with GenAI: A Research Perspective},
author = {Raula Gaikovina Kula and Christoph Treude and Xing Hu and Sebastian Baltes and Earl T. Barr and Kelly Blincoe and Fabio Calefato and Junjie Chen and Marc Cheong and Youmei Fan and Daniel M. German and Marco Gerosa and Jin L. C. Guo and Shinpei Hayashi and Robert Hirschfeld and Reid Holmes and Yintong Huo and Takashi Kobayashi and Michele Lanza and Zhongxin Liu and Olivier Nourry and Nicole Novielli and Denys Poshyvanyk and Shinobu Saito and Kazumasa Shimari and Igor Steinmacher and Mairieli Wessel and Markus Wagner and Annie Vella and Laurie Williams and Xin Xia},
journal= {arXiv preprint arXiv:2602.07412},
year = {2026}
}