Humans are Missing from AI Coding Agent Research

Zora Z. Wang; John Yang; Kilian Lieret; Alexa Tartaglini; Valerie Chen; Yuxiang Wei; Zijian Wang; Lingming Zhang; Karthik Narasimhan; Ludwig Schmidt; Graham Neubig; Daniel Fried; Diyi Yang

arXiv · 2608.12355

Humans are Missing from AI Coding Agent Research

Zora Z. Wang·John Yang·Kilian Lieret·Alexa Tartaglini·Valerie Chen·Yuxiang Wei·Zijian Wang·Lingming Zhang·Karthik Narasimhan·Ludwig Schmidt·Graham Neubig·Daniel Fried·Diyi Yang

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Abstract

Recent progress in AI coding agent research has led to rapid improvements in agents' ability to autonomously perform complex software engineering tasks, from editing large codebases to executing long-horizon development workflows. As these systems make strides, however, the primary bottleneck to practical usefulness increasingly shifts away from pure task-solving capability, and toward challenges in how users communicate with, supervise, and trust agents. In this position paper, we argue for a reorientation from autonomous to human-centered coding agents: systems designed not only to complete tasks, but to collaborate effectively with people. We identify four core interaction-level dimensions that characterize the human-agent task-solving loop: task alignment, verifiability, steerability, and adaptability. Finally, we outline concrete research directions to advance these dimensions, including user-involved coding environments, comprehensive verification mechanisms, and principled measures of human-agent interaction quality.

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Zora Z. Wang, John Yang, Kilian Lieret, Alexa Tartaglini, Valerie Chen, Yuxiang Wei, Zijian Wang, Lingming Zhang, Karthik Narasimhan, Ludwig Schmidt, Graham Neubig, Daniel Fried, Diyi Yang. 2026-07-04. Humans are Missing from AI Coding Agent Research. https://arxiv.org/abs/2608.12355

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