mlsanityData to 14 Oct 2026

The Impact of AI on Developer Productivity: Evidence from GitHub Copilot

arXiv 2302.06590 ↗First posted 13 Feb 2023cs.SEcited by 274

Not on the map. Why?

Cited by 68 in LLM agents and tool use, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Generative AI tools hold promise to increase human productivity. This paper presents results from a controlled experiment with GitHub Copilot, an AI pair programmer. Recruited software developers were asked to implement an HTTP server in JavaScript as quickly as possible. The treatment group, with access to the AI pair programmer, completed the task 55.8% faster than the control group. Observed heterogenous effects show promise for AI pair programmers to help people transition into software development careers.

Key facts. Cited by 274 papers in the map (data through 14 Oct 2026). First posted on arXiv 13 Feb 2023.

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 23; 2024: 49; 2025: 68; 2026: 134.

274 papers.

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  1. 2023Can large language models provide useful feedback on research papers? A large-scale empirical analysiscited by 200
  2. 2023GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Modelscited by 176
  3. 2025AI Agents vs. Agentic AI: A Conceptual Taxonomy, Applications and Challengescited by 169
  4. 2023Sociotechnical Safety Evaluation of Generative AI Systemscited by 157
  5. 2025Measuring the Impact of Early-2025 AI on Experienced Open-Source Developer Productivitycited by 101
  6. 2025The Invisible Leash: Why RLVR May or May Not Escape Its Origincited by 97
  7. 2025Which Economic Tasks are Performed with AI? Evidence from Millions of Claude Conversationscited by 96
  8. 2024From LLMs to LLM-based Agents for Software Engineering: A Survey of Current, Challenges and Futurecited by 86
  9. 2023"It's Weird That it Knows What I Want": Usability and Interactions with Copilot for Novice Programmerscited by 64
  10. 2023Computing Education in the Era of Generative AIcited by 52
  11. 2024The Widening Gap: The Benefits and Harms of Generative AI for Novice Programmerscited by 48
  12. 2026Code as Agent Harnesscited by 47
38 more
  1. 2025Magentic-UI: Towards Human-in-the-loop Agentic Systemscited by 43
  2. 2026SWE-chat: Coding Agent Interactions From Real Users in the Wildcited by 43
  3. 2024Can LLMs Replace Manual Annotation of Software Engineering Artifacts?cited by 42
  4. 2025Multilingual != Multicultural: Evaluating Gaps Between Multilingual Capabilities and Cultural Alignment in LLMscited by 39
  5. 2025Ambig-SWE: Interactive Agents to Overcome Underspecificity in Software Engineeringcited by 38
  6. 2023LLMs for Science: Usage for Code Generation and Data Analysiscited by 34
  7. 2023Ecosystem Graphs: The Social Footprint of Foundation Modelscited by 32
  8. 2026Scientific production in the era of Large Language Modelscited by 32
  9. 2026Agentic Much? Adoption of Coding Agents on GitHubcited by 32
  10. 2024The RealHumanEval: Evaluating Large Language Models' Abilities to Support Programmerscited by 30
  11. 2024Towards AI-Native Software Engineering (SE 3.0): A Vision and a Challenge Roadmapcited by 30
  12. 2025RefactorBench: Evaluating Stateful Reasoning in Language Agents Through Codecited by 30
  13. 2023The Shaky Foundations of Clinical Foundation Models: A Survey of Large Language Models and Foundation Models for EMRscited by 29
  14. 2024An Empirical Study on Usage and Perceptions of LLMs in a Software Engineering Projectcited by 28
  15. 2023LORD: Low Rank Decomposition Of Monolingual Code LLMs For One-Shot Compressioncited by 26
  16. 2024Beyond Code Generation: An Observational Study of ChatGPT Usage in Software Engineering Practicecited by 25
  17. 2025Speed at the Cost of Quality: How Cursor AI Increases Short-Term Velocity and Long-Term Complexity in Open-Source Projectscited by 24
  18. 2026How AI Impacts Skill Formationcited by 24
  19. 2024Learning Agent-based Modeling with LLM Companions: Experiences of Novices and Experts Using ChatGPT & NetLogo Chatcited by 23
  20. 2023Are Large Language Models a Threat to Digital Public Goods? Evidence from Activity on Stack Overflowcited by 22
  21. 2024AI-Augmented Predictions: LLM Assistants Improve Human Forecasting Accuracycited by 21
  22. 2024On Mitigating Code LLM Hallucinations with API Documentationcited by 21
  23. 2023An Automated Survey of Generative Artificial Intelligence: Large Language Models, Architectures, Protocols, and Applicationscited by 20
  24. 2023Is AI the better programming partner? Human-Human Pair Programming vs. Human-AI pAIr Programmingcited by 20
  25. 2024Can Large Language Models Serve as Data Analysts? A Multi-Agent Assisted Approach for Qualitative Data Analysiscited by 20
  26. 2025Professional Software Developers Don't Vibe, They Control: AI Agent Use for Coding in 2025cited by 20
  27. 2024Prompts Are Programs Too! Understanding How Developers Build Software Containing Promptscited by 19
  28. 2025Working with AI: Measuring the Applicability of Generative AI to Occupationscited by 19
  29. 2024The Use of Generative Search Engines for Knowledge Work and Complex Taskscited by 18
  30. 2023GPT is becoming a Turing machine: Here are some ways to program itcited by 16
  31. 2023User Experience Design Professionals' Perceptions of Generative Artificial Intelligencecited by 16
  32. 2025DeepCode: Open Agentic Codingcited by 16
  33. 2024Data Authenticity, Consent, & Provenance for AI are all broken: what will it take to fix them?cited by 15
  34. 2025VeriThoughts: Enabling Automated Verilog Code Generation using Reasoning and Formal Verificationcited by 15
  35. 2025From Code Foundation Models to Agents and Applications: A Comprehensive Survey and Practical Guide to Code Intelligencecited by 15
  36. 2024The Impact of Large Language Models on Open-source Innovation: Evidence from GitHub Copilotcited by 13
  37. 2024Rethinking Software Engineering in the Foundation Model Era: From Task-Driven AI Copilots to Goal-Driven AI Pair Programmerscited by 12
  38. 2025HICode: Hierarchical Inductive Coding with LLMscited by 12

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