Generative AI and the Transformation of Software Development Practices
Not on the map. Why?
Abstract (arXiv)
Generative AI is reshaping how software is designed, written, and maintained. Advances in large language models (LLMs) are enabling new development styles - from chat-oriented programming and 'vibe coding' to agentic programming - that can accelerate productivity and broaden access. This paper examines how AI-assisted techniques are changing software engineering practice, and the related issues of trust, accountability, and shifting skills. We survey iterative chat-based development, multi-agent systems, dynamic prompt orchestration, and integration via the Model Context Protocol (MCP). Using case studies and industry data, we outline both the opportunities (faster cycles, democratized coding) and the challenges (model reliability and cost) of applying generative AI to coding. We describe new roles, skills, and best practices for using AI in a responsible and effective way.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 1 of its 22 references that are in the map. First posted on arXiv 12 Oct 2025.
Builds on
1 of 22 references.
References · 1
Built on by
Citing papers per year: 2026: 3.
3 papers.
- 2026Interrogating Design Homogenization in Web Vibe Codingcited by 1
- 2026"Don't Be Afraid, Just Learn": Insights from Industry Practitioners to Prepare Software Engineers in the Age of Generative AIcited by 0
- 2026Physically-Relevant Information Learning in High-Dimensional Time-Derivatives Spacescited by 0
- 2026Physically-Relevant Information Learning in High-Dimensional Time-Derivatives Spaces6 Jul 2026
- 2026"Don't Be Afraid, Just Learn": Insights from Industry Practitioners to Prepare Software Engineers in the Age of Generative AI7 Apr 2026
- 2026Interrogating Design Homogenization in Web Vibe Coding13 Mar 2026
Similar, not cited
Close in wording, no citation either way
- 2023Exploring the intersection of Generative AI and Software Development
- 2026Human-AI Collaboration and the Transformation of Software Engineering Work
- 2026AI-driven Software Development: A Pragmatic Path to Agentic Development Processes
- 2025Lost in Code Generation: Reimagining the Role of Software Models in AI-driven Software Engineering
- 2026The Rise of AI-Native Software Engineering: Implications for Practice, Education, and the Future Workforce
- 2026From Code-Centric to Intent-Centric Software Engineering: A Reflexive Thematic Analysis of Generative AI, Agentic Systems, and Engineering Accountability
- 2026Developing LLM-based Multi-Agent Systems in Software Engineering: A Mixed-Method Experience Report
- 2024Building Living Software Systems with Generative & Agentic AI