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This study investigates whether "Plan Mode" features, common in advanced agentic tools, effectively translate to iterative end-user environments like spreadsheet applications. The research finds that while upfront planning does not improve task outcomes for non-technical users, it significantly enhances their perception of the tool's creativity support and collaboration capabilities. These findings offer critical insights into designing human-AI interaction patterns specifically tailored for generalist programming contexts rather than just technical developers.
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Plans Work in Mysterious Ways: Evaluating a Plan Mode for Spreadsheet Agents

arXiv2 min de cititArticolul și perspectiva sunt în engleză.

arXiv:2607.23670v1 Announce Type: cross Abstract: Plan Modes have become standard features in agentic programming tools, allowing users to gain transparency and control by working with the agent to develop a plan before task execution. However, it remains unclear whether the benefits of this feature translate to end-user programming environments such as spreadsheets. Since spreadsheet programmers tend to work iteratively and care less about technical correctness, upfront planning may not fit into their workflows as easily. In this paper, we build a prototype of a Plan Mode for spreadsheet programming and evaluate it against a non-planning baseline through a within-subjects user study (N=24). We found that despite similar task outcomes with both tools, using Plan Mode led to a reduction in refinement and a better perception of the tool across dimensions of creativity support and human-machine collaboration. We discuss the implications of these results for the future design of Plan Modes, and for the broader role of human-AI planning in end-user programming.

Abstract:Plan Modes have become standard features in agentic programming tools, allowing users to gain transparency and control by working with the agent to develop a plan before task execution. However, it remains unclear whether the benefits of this feature translate to end-user programming environments such as spreadsheets. Since spreadsheet programmers tend to work iteratively and care less about technical correctness, upfront planning may not fit into their workflows as easily. In this paper, we build a prototype of a Plan Mode for spreadsheet programming and evaluate it against a non-planning baseline through a within-subjects user study (N=24). We found that despite similar task outcomes with both tools, using Plan Mode led to a reduction in refinement and a better perception of the tool across dimensions of creativity support and human-machine collaboration. We discuss the implications of these results for the future design of Plan Modes, and for the broader role of human-AI planning in end-user programming.

Human-Computer Interaction (cs.HC); Artificial Intelligence (cs.AI); Software Engineering (cs.SE)

arXiv:2607.23670 [cs.HC]

(or arXiv:2607.23670v1 [cs.HC] for this version)

https://doi.org/10.48550/arXiv.2607.23670 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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