mlsanityData to 7 Oct 2026

Generative AI and the Transformation of Software Development Practices

arXiv 2510.10819 ↗First posted 12 Oct 2025cs.SE cs.AIcited by 3

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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.

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1 of 22 references.

References · 1

  1. 2025Intelligent Healthcare Ecosystems: Optimizing the Iron Triangle of Healthcare (Access, Cost, Quality)cited by 1

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 3.

3 papers.

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  2. 2026Human-AI Collaboration and the Transformation of Software Engineering Work
  3. 2026AI-driven Software Development: A Pragmatic Path to Agentic Development Processes
  4. 2025Lost in Code Generation: Reimagining the Role of Software Models in AI-driven Software Engineering
  5. 2026The Rise of AI-Native Software Engineering: Implications for Practice, Education, and the Future Workforce
  6. 2026From Code-Centric to Intent-Centric Software Engineering: A Reflexive Thematic Analysis of Generative AI, Agentic Systems, and Engineering Accountability
  7. 2026Developing LLM-based Multi-Agent Systems in Software Engineering: A Mixed-Method Experience Report
  8. 2024Building Living Software Systems with Generative & Agentic AI