TableTalk: Scaffolding Spreadsheet Development with a Language Agent
On the map: LLM agents and tool use → Financial trading and forecasting agents
Abstract (arXiv)
Spreadsheet programming is challenging. Programmers use spreadsheet programming knowledge (e.g., formulas) and problem-solving skills to combine actions into complex tasks. Advancements in large language models have introduced language agents that observe, plan, and perform tasks, showing promise for spreadsheet creation. We present TableTalk, a spreadsheet programming agent embodying three design principles -- scaffolding, flexibility, and incrementality -- derived from studies with seven spreadsheet programmers and 85 Excel templates. TableTalk guides programmers through structured plans based on professional workflows, generating three potential next steps to adapt plans to programmer needs. It uses pre-defined tools to generate spreadsheet components and incrementally build spreadsheets. In a study with 20 programmers, TableTalk produced higher-quality spreadsheets 2.3 times more likely to be preferred than the baseline. It reduced cognitive load and thinking time by 12.6%. From this, we derive design guidelines for agentic spreadsheet programming tools and discuss implications on spreadsheet programming, end-user programming, AI-assisted programming, and human-agent collaboration.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Placed in Financial trading and forecasting agents, one of 16 directions in LLM agents and tool use. Builds on 41 of its 96 references that are in the map. First posted on arXiv 13 Feb 2025.
Builds on
41 of 96 references.
References · 41
- 2023GPT-4 Technical Reportcited by 18,132
- 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,355
- 2023Toolformer: Language Models Can Teach Themselves to Use Toolscited by 4,072
- 2023Reflexion: Language Agents with Verbal Reinforcement Learningcited by 4,064
- 2023Self-Refine: Iterative Refinement with Self-Feedbackcited by 3,317
- 2023Tree of Thoughts: Deliberate Problem Solving with Large Language Modelscited by 3,155
- 2023A Survey on Large Language Model based Autonomous Agentscited by 2,203
- 2024SWE-agent: Agent-Computer Interfaces Enable Automated Software Engineeringcited by 1,628
- 2023The Rise and Potential of Large Language Model Based Agents: A Surveycited by 1,422
- 2024AutoCodeRover: Autonomous Program Improvementcited by 272
- 2022Grounded Copilot: How Programmers Interact with Code-Generating Modelscited by 216
- 2023REFINER: Reasoning Feedback on Intermediate Representationscited by 203
29 more
- 2024Large Language Model-Based Agents for Software Engineering: A Surveycited by 173
- 2022Language Models as Agent Modelscited by 131
- 2022A Survey of Deep Learning for Mathematical Reasoningcited by 124
- 2022Programming Is Hard -- Or at Least It Used to Be: Educational Opportunities And Challenges of AI Code Generationcited by 97
- 2022Reading Between the Lines: Modeling User Behavior and Costs in AI-Assisted Programmingcited by 91
- 2023The Metacognitive Demands and Opportunities of Generative AIcited by 85
- 2023A Large-Scale Survey on the Usability of AI Programming Assistants: Successes and Challengescited by 75
- 2023Comparing Code Explanations Created by Students and Large Language Modelscited by 63
- 2023"It's Weird That it Knows What I Want": Usability and Interactions with Copilot for Novice Programmerscited by 62
- 2023How Novices Use LLM-Based Code Generators to Solve CS1 Coding Tasks in a Self-Paced Learning Environmentcited by 55
- 2023Sensecape: Enabling Multilevel Exploration and Sensemaking with Large Language Modelscited by 48
- 2024"We Need Structured Output": Towards User-centered Constraints on Large Language Model Outputcited by 46
- 2024Need Help? Designing Proactive AI Assistants for Programmingcited by 42
- 2021SpreadsheetCoder: Formula Prediction from Semi-structured Contextcited by 41
- 2024Cocoa: Co-Planning and Co-Execution with AI Agentscited by 38
- 2021TabularNet: A Neural Network Architecture for Understanding Semantic Structures of Tabular Datacited by 36
- 2020Towards Unified Dialogue System Evaluation: A Comprehensive Analysis of Current Evaluation Protocolscited by 35
- 2023Investigating and Designing for Trust in AI-powered Code Generation Toolscited by 34
- 2024AutoDev: Automated AI-Driven Developmentcited by 24
- 2024MetaReflection: Learning Instructions for Language Agents using Past Reflectionscited by 19
- 2023FLAME: A small language model for spreadsheet formulascited by 15
- 2023InstructExcel: A Benchmark for Natural Language Instruction in Excelcited by 14
- 2025The AI Agent Indexcited by 14
- 2024ReviewFlow: Intelligent Scaffolding to Support Academic Peer Reviewingcited by 12
- 2022Understanding Skills for OSS Communities on GitHubcited by 9
- 2023A Qualitative Study on the Implementation Design Decisions of Developerscited by 7
- 2018Towards a Theory of Software Development Expertisecited by 5
- 2024Requirements are All You Need: The Final Frontier for End-User Software Engineeringcited by 5
- 2019Explicit Programming Strategiescited by 1
Built on by
Citing papers per year: 2025: 2; 2026: 3.
5 papers.
- 2025Understanding User Experiences of Computer Use Agents: Design Space and Opportunities for Building Agent UX Prototypescited by 2
- 2026Auditing and Controlling AI Agent Actions in Spreadsheetscited by 1
- 2025Automating Complex Document Workflows via Stepwise and Rollback-Enabled Operation Orchestrationcited by 0
- 2026A Benchmark and Framework for Evaluating Next Action Predictions in Spreadsheetscited by 0
- 2026Plans Work in Mysterious Ways: Evaluating a Plan Mode for Spreadsheet Agentscited by 0
- 2026Plans Work in Mysterious Ways: Evaluating a Plan Mode for Spreadsheet Agents26 Jul 2026
- 2026A Benchmark and Framework for Evaluating Next Action Predictions in Spreadsheets11 Jun 2026
- 2026Auditing and Controlling AI Agent Actions in Spreadsheets22 Apr 2026
- 2025Automating Complex Document Workflows via Stepwise and Rollback-Enabled Operation Orchestration4 Dec 2025
- 2025Understanding User Experiences of Computer Use Agents: Design Space and Opportunities for Building Agent UX Prototypes6 Oct 2025
Similar, not cited
Close in wording, no citation either way
- 2026TabClaw: An Interactive and Self-Evolving Agent for Spreadsheet Manipulation and Table Reasoning
- 2024SheetAgent: Towards A Generalist Agent for Spreadsheet Reasoning and Manipulation via Large Language Models
- 2026Spreadsheet-RL: Advancing Large Language Model Agents on Realistic Spreadsheet Tasks via Reinforcement Learning
- 2026SheetCompass: Hierarchical Relation Graphs for Agentic Spreadsheet Reasoning
- 2026SpreadsheetBench 2: Evaluating Agents on End-to-End Business Spreadsheet Workflows
- 2026Towards Robust Real-World Spreadsheet Understanding with Multi-Agent Multi-Format Reasoning
- 2025SheetBrain: A Neuro-Symbolic Agent for Accurate Reasoning over Complex and Large Spreadsheets
- 2026Beyond Rows to Reasoning: Agentic Retrieval for Multimodal Spreadsheet Understanding and Editing