TY - GEN
T1 - How Developers Interact with AI
T2 - 2nd IEEE/ACM International Conference on AI Foundation Models and Software Engineering, FORGE 2025
AU - Treude, Christoph
AU - Gerosa, Marco A.
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025
Y1 - 2025
N2 - Artificial intelligence (AI), including large language models and generative AI, is emerging as a significant force in software development, offering developers powerful tools that span the entire development lifecycle. Although software engineering research has extensively studied AI tools in software development, the specific types of interactions between developers and these AI-powered tools have only recently begun to receive attention. Understanding and improving these interactions has the potential to enhance productivity, trust, and efficiency in AI-driven workflows. In this paper, we propose a taxonomy of interaction types between developers and AI tools, identifying eleven distinct interaction types, such as auto-complete code suggestions, command-driven actions, and conversational assistance. Building on this taxonomy, we outline a research agenda focused on optimizing AI interactions, improving developer control, and addressing trust and usability challenges in AI-assisted development. By establishing a structured foundation for studying developer-AI interactions, this paper aims to stimulate research on creating more effective, adaptive AI tools for software development.
AB - Artificial intelligence (AI), including large language models and generative AI, is emerging as a significant force in software development, offering developers powerful tools that span the entire development lifecycle. Although software engineering research has extensively studied AI tools in software development, the specific types of interactions between developers and these AI-powered tools have only recently begun to receive attention. Understanding and improving these interactions has the potential to enhance productivity, trust, and efficiency in AI-driven workflows. In this paper, we propose a taxonomy of interaction types between developers and AI tools, identifying eleven distinct interaction types, such as auto-complete code suggestions, command-driven actions, and conversational assistance. Building on this taxonomy, we outline a research agenda focused on optimizing AI interactions, improving developer control, and addressing trust and usability challenges in AI-assisted development. By establishing a structured foundation for studying developer-AI interactions, this paper aims to stimulate research on creating more effective, adaptive AI tools for software development.
KW - Artificial Intelligence
KW - Developer Tools
KW - Generative AI
KW - Human-AI Interaction
KW - Large Language Models
KW - Software Development
UR - https://www.scopus.com/pages/publications/105011354268
UR - https://www.scopus.com/inward/citedby.url?scp=105011354268&partnerID=8YFLogxK
U2 - 10.1109/Forge66646.2025.00033
DO - 10.1109/Forge66646.2025.00033
M3 - Conference contribution
AN - SCOPUS:105011354268
T3 - Proceedings - 2025 IEEE/ACM 2nd International Conference on AI Foundation Models and Software Engineering, FORGE 2025
SP - 236
EP - 240
BT - Proceedings - 2025 IEEE/ACM 2nd International Conference on AI Foundation Models and Software Engineering, FORGE 2025
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 27 April 2025 through 28 April 2025
ER -