Agentes de Codificação de IA como Prática Colaborativa: Implicações para Equipes de Desenvolvimento de Software
Resumo
Agentes de codificação baseados em Modelos de Linguagem de Grande Escala (LLMs) vêm transformando a engenharia de software ao atuarem de forma autônoma em fluxos colaborativos antes exclusivos de equipes humanas. Embora a literatura os avalie predominantemente por métricas técnicas, como qualidade do código e acurácia, seus impactos sobre a colaboração permanecem pouco compreendidos. Este artigo investiga como esses agentes reconfiguram práticas colaborativas em equipes de desenvolvimento de software, com foco em comunicação, coordenação, cooperação e workspace awareness. Para isso, realizamos um estudo qualitativo exploratório baseado na análise temática de dez threads públicas de pull requests no GitHub analisadas à luz do Modelo de Colaboração 3C e da teoria de Workspace Awareness. Os resultados mostram que agentes de IA assumem papéis colaborativos, reconfigurando mecanismos de interação e awareness, e apontam oportunidades para ampliar modelos colaborativos para a Engenharia de Software de sistemas agênticos.
Palavras-chave:
Agentes de codificação de IA, Colaboração humano-IA, Modelo de Colaboração 3C, Engenharia de software
Referências
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Miku Watanabe, Hao Li, Yutaro Kashiwa, Brittany Reid, Hajimu Iida, and Ahmed E. Hassan. 2026. On the Use of Agentic Coding: An Empirical Study of Pull Requests onGitHub. ACMTrans. Softw. Eng. Methodol. (2026). DOI: 10.1145/3798166
Leon Banh, Florian Holldack, and Gero Strobel. 2025. Copiloting the Future: How Generative AI Transforms Software Engineering. Information and Software Technology 183 (2025), 107751. DOI: 10.1016/j.infsof.2025.107751
Tuomas Bazzan, BenjaminOlojo, PrzemysławMajda, Thomas Kelly,Murat Yilmaz, Gerard Marks, and Paul M. Clarke. 2024. Analysing the Role of Generative AI in Software Engineering — Results from an MLR. In Systems, Software and Services Process Improvement. Springer Nature Switzerland, Cham, 163–180.
Virginia Braun and Victoria Clarke. 2006. Using Thematic Analysis in Psychology. Qualitative Research in Psychology 3, 2 (2006), 77–101. DOI: 10.1191/1478088706qp063oa
Laura Dabbish, Colleen Stuart, Jason Tsay, and Jim Herbsleb. 2012. Social Coding in GitHub: Transparency and Collaboration in an Open Software Repository. In Proceedings of the ACM 2012 Conference on Computer Supported Cooperative Work (CSCW ’12). Association for Computing Machinery, New York, NY, USA, 1277–1286. DOI: 10.1145/2145204.2145396
Clarence A. Ellis, Simon J. Gibbs, and Gail Rein. 1991. Groupware: Some Issues and Experiences. Commun. ACM 34, 1 (1991), 39–58. DOI: 10.1145/99977.99987
Hugo Fuks, Alberto B. Raposo, Marco A. Gerosa, and Carlos J. P. Lucena. 2005. Applying the 3C Model to Groupware Development. International Journal of Cooperative Information Systems 14, 2–3 (2005), 299–328.
GitHub, Inc. 2026. About GitHub Copilot Coding Agent. GitHub Docs. [link]
Erving Goffman. 1955. On Face-Work: An Analysis of Ritual Elements in Social Interaction. Psychiatry 18, 3 (1955), 213–231. DOI: 10.1080/00332747.1955.11023008
Carl Gutwin and Saul Greenberg. 2002. A Descriptive Framework of Workspace Awareness for Real-Time Groupware. Computer Supported Cooperative Work (CSCW) 11, 3–4 (2002), 411–446. DOI: 10.1023/A:1021271517844
JundaHe, Christoph Treude, andDavid Lo. 2025. LLM-BasedMulti-Agent Systems for Software Engineering: Literature Review, Vision, and the Road Ahead. ACM Trans. Softw. Eng. Methodol. 34, 5, Article 124 (2025), 30 pages. DOI: 10.1145/3712003
Eirini Kalliamvakou, Georgios Gousios, Kelly Blincoe, Leif Singer, Daniel M. German, and Daniela Damian. 2016. An In-Depth Study of the Promises and Perils of Mining GitHub. Empirical Software Engineering 21, 5 (2016), 2035–2071. DOI: 10.1007/s10664-015-9393-5
Dilan Karolita, John Grundy, Tanjila Kanij, Hourieh Khalajzadeh, and Jennifer McIntosh. 2023. Use of Personas in Requirements Engineering: A Systematic Mapping Study. Information and Software Technology 162 (2023), 107264. DOI: 10.1016/j.infsof.2023.107264
John D. Lee and Katrina A. See. 2004. Trust in Automation: Designing for Appropriate Reliance. Human Factors 46, 1 (2004), 50–80. DOI: 10.1518/hfes.46.1.50_30392
Chamith Madusanka. 2026. How We Integrated Claude Code Into Our GitHub Workflow. Medium. [link]
Clifford Nass and Youngme Moon. 2000. Machines and Mindlessness: Social Responses to Computers. Journal of Social Issues 56, 1 (2000), 81–103. DOI: 10.1111/0022-4537.00153
Angshuman Rudra and Manan Agrawal. 2025. Composable AI Stack for Intelligent Agents: Modular Orchestration Using Context Routing, Memory, and Tools. In 2025 International Conference on Computer and Applications (ICCA). IEEE, 1–6. DOI: 10.1109/ICCA66035.2025.11430973
Isabella Seeber, Eva Bittner, Robert O. Briggs, Triparna de Vreede, Gert-Jan de Vreede, Aaron Elkins, Ronald Maier, Alexander B. Merz, Sarah Oeste-Reiß, Nils Randrup, Gerhard Schwabe, and Matthias Söllner. 2020. Machines as Teammates: A Research Agenda on AI in Team Collaboration. Information & Management 57, 2 (2020), 103174. DOI: 10.1016/j.im.2019.103174
Margaret-Anne Storey and Alexey Zagalsky. 2016. Disrupting Developer Productivity One Bot at a Time. In Proceedings of the 2016 24th ACM SIGSOFT International Symposium on Foundations of Software Engineering (FSE 2016). Association for Computing Machinery, New York, NY, USA, 928–931. DOI: 10.1145/2950290.2983989
Christoph Treude andMarco Aurelio Gerosa. 2025. HowDevelopers Interact with AI: A Taxonomy of Human-AI Collaboration in Software Engineering. In 2025 IEEE/ACM Second International Conference on AI Foundation Models and Software Engineering (FORGE). IEEE, 236–240. DOI: 10.1109/Forge66646.2025.00033
Rasmus Ulfsnes, Nils Brede Moe, Viktoria Stray, and Marianne Skarpen. 2024. Transforming Software Development with Generative AI: Empirical Insights on Collaboration andWorkflow. Springer Nature Switzerland, Cham, 219–234. DOI: 10.1007/978-3-031-55642-5_10
Yanlin Wang, Wanjun Zhong, Yanxian Huang, Ensheng Shi, Min Yang, Jiachi Chen, Hui Li, Yuchi Ma, Qianxiang Wang, and Zibin Zheng. 2025. Agents in Software Engineering: Survey, Landscape, and Vision. Automated Software Engineering 32, 2, Article 70 (2025), 35 pages. DOI: 10.1007/s10515-025-00544-2
Miku Watanabe, Hao Li, Yutaro Kashiwa, Brittany Reid, Hajimu Iida, and Ahmed E. Hassan. 2026. On the Use of Agentic Coding: An Empirical Study of Pull Requests onGitHub. ACMTrans. Softw. Eng. Methodol. (2026). DOI: 10.1145/3798166
Publicado
08/09/2026
Como Citar
HICKMANN, Lucas Feksa; HOCH, Barbara; PARIZI, Rafael; MACHADO, Leticia dos Santos.
Agentes de Codificação de IA como Prática Colaborativa: Implicações para Equipes de Desenvolvimento de Software. In: WORKSHOP EM ENGENHARIA DE SOFTWARE PARA SISTEMAS AGÊNTICOS (SE4AS), 1. , 2026, São Paulo/SP.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2026
.
p. 25-30.
DOI: https://doi.org/10.5753/se4as.2026.32995.
