mlsanityData to 7 Oct 2026

Plans Work in Mysterious Ways: Evaluating a Plan Mode for Spreadsheet Agents

arXiv 2607.23670 ↗First posted 26 Jul 2026cs.HC cs.AI cs.SEcited by 0

On the map: LLM agents and tool use → Financial trading and forecasting agents

Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Placed in Financial trading and forecasting agents, one of 16 directions in LLM agents and tool use. Builds on 23 of its 48 references that are in the map. First posted on arXiv 26 Jul 2026.

Builds on

23 of 48 references.

Closest ancestors · 2

Same direction, newest first

  1. 2025TableTalk: Scaffolding Spreadsheet Development with a Language Agent13 Feb
  2. 2024SheetAgent: Towards A Generalist Agent for Spreadsheet Reasoning and Manipulation via Large Language Models6 Mar

Other references · 21

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  2. 2023CodePlan: Repository-level Coding using LLMs and Planningcited by 139
  3. 2025Plan-Then-Execute: An Empirical Study of User Trust and Team Performance When Using LLM Agents As A Daily Assistantcited by 54
  4. 2023SheetCopilot: Bringing Software Productivity to the Next Level through Large Language Modelscited by 53
  5. 2023"What It Wants Me To Say": Bridging the Abstraction Gap Between End-User Programmers and Code-Generating Large Language Modelscited by 48
  6. 2025Magentic-UI: Towards Human-in-the-loop Agentic Systemscited by 41
  7. 2022What is it like to program with artificial intelligence?cited by 39
  8. 2024Cocoa: Co-Planning and Co-Execution with AI Agentscited by 38
  9. 2024Improving Steering and Verification in AI-Assisted Data Analysis with Interactive Task Decompositioncited by 29
  10. 2025Beyond Code Generation: LLM-supported Exploration of the Program Design Spacecited by 13
  11. 2024BISCUIT: Scaffolding LLM-Generated Code with Ephemeral UIs in Computational Notebookscited by 12
  12. 2025AI, Help Me Thinkunicodex2014but for Myself: Assisting People in Complex Decision-Making by Providing Different Kinds of Cognitive Supportcited by 12
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  1. 2024AI Should Challenge, Not Obeycited by 11
  2. 2025Why AI Agents Still Need You: Findings from Developer-Agent Collaborations in the Wildcited by 11
  3. 2025Understanding, Protecting, and Augmenting Human Cognition with Generative AI: A Synthesis of the CHI 2025 Tools for Thought Workshopcited by 7
  4. 2024"It's like a rubber duck that talks back": Understanding Generative AI-Assisted Data Analysis Workflows through a Participatory Prompting Studycited by 6
  5. 2025Dango: A Mixed-Initiative Data Wrangling System using Large Language Modelcited by 5
  6. 2023Will Code Remain a Relevant User Interface for End-User Programming with Generative AI Models?cited by 3
  7. 2025The Invisible Mentor: Inferring User Actions from Screen Recordings to Recommend Better Workflowscited by 3
  8. 2024Dynamic Prompt Middleware: Contextual Prompt Refinement Controls for Comprehension Taskscited by 2
  9. 2025From Correctness to Collaboration: Toward a Human-Centered Framework for Evaluating AI Agent Behavior in Software Engineeringcited by 2

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