# Transforming Software Development with Generative AI: Empirical Insights on Collaboration and Workflow

arXiv: https://arxiv.org/abs/2405.01543 · HTML: https://mlsanity.com/paper/2405.01543/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 12 Feb 2024.

## Built on by (most cited first, 6 of 6)

- [Vibe Coding as a Reconfiguration of Intent Mediation in Software Development: Definition, Implications, and Research Agenda](https://mlsanity.com/paper/2507.21928/) (2025)
- [Time Warp: The Gap Between Developers' Ideal vs Actual Workweeks in an AI-Driven Era](https://mlsanity.com/paper/2502.15287/) (2025)
- [The State of Generative AI in Software Development: Insights from Literature and a Developer Survey](https://mlsanity.com/paper/2603.16975/) (2026)
- [Towards Requirements Engineering for RAG Systems](https://mlsanity.com/paper/2505.07553/) (2025)
- [Controlling Context: Generative AI at Work in Integrated Circuit Design and Other High-Precision Domains](https://mlsanity.com/paper/2506.14567/) (2025)
- [AI and Agile Software Development: A Research Roadmap from the XP2025 Workshop](https://mlsanity.com/paper/2508.20563/) (2025)

## Abstract (arXiv)

Generative AI (GenAI) has fundamentally changed how knowledge workers, such as software developers, solve tasks and collaborate to build software products. Introducing innovative tools like ChatGPT and Copilot has created new opportunities to assist and augment software developers across various problems. We conducted an empirical study involving interviews with 13 data scientists, managers, developers, designers, and frontend developers to investigate the usage of GenAI. Our study reveals that ChatGPT signifies a paradigm shift in the workflow of software developers. The technology empowers developers by enabling them to work more efficiently, speed up the learning process, and increase motivation by reducing tedious and repetitive tasks. Moreover, our results indicate a change in teamwork collaboration due to software engineers using GenAI for help instead of asking co-workers which impacts the learning loop in agile teams.