✨Walking the Tightrope of LLMs for Software Development: A Practitioners' Perspective
📝 Summary:
This study investigated software developers' perspectives on Large Language Models, identifying benefits like improved workflow and entrepreneurship, alongside risks to personal well-being and reputation. It highlights key trade-offs and best practices for adopting LLMs in software development.
🔹 Publication Date: Published on Nov 9
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.06428
• PDF: https://arxiv.org/pdf/2511.06428
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✓ https://t.me/DataScienceT
#LLMs #SoftwareDevelopment #AIinDevelopment #DeveloperExperience #TechResearch
📝 Summary:
This study investigated software developers' perspectives on Large Language Models, identifying benefits like improved workflow and entrepreneurship, alongside risks to personal well-being and reputation. It highlights key trade-offs and best practices for adopting LLMs in software development.
🔹 Publication Date: Published on Nov 9
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.06428
• PDF: https://arxiv.org/pdf/2511.06428
==================================
For more data science resources:
✓ https://t.me/DataScienceT
#LLMs #SoftwareDevelopment #AIinDevelopment #DeveloperExperience #TechResearch
✨AgentDevel: Reframing Self-Evolving LLM Agents as Release Engineering
📝 Summary:
AgentDevel reframes LLM agent improvement as release engineering, treating agents as shippable software. It emphasizes stable, auditable improvements through an externalized pipeline that prioritizes non-regression, leading to more reliable and traceable agent development.
🔹 Publication Date: Published on Jan 8
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.04620
• PDF: https://arxiv.org/pdf/2601.04620
==================================
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✓ https://t.me/DataScienceT
#LLMAgents #ReleaseEngineering #SoftwareDevelopment #AIResearch #MLOps
📝 Summary:
AgentDevel reframes LLM agent improvement as release engineering, treating agents as shippable software. It emphasizes stable, auditable improvements through an externalized pipeline that prioritizes non-regression, leading to more reliable and traceable agent development.
🔹 Publication Date: Published on Jan 8
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.04620
• PDF: https://arxiv.org/pdf/2601.04620
==================================
For more data science resources:
✓ https://t.me/DataScienceT
#LLMAgents #ReleaseEngineering #SoftwareDevelopment #AIResearch #MLOps
✨Multi-Agent Software Development through Cross-Team Collaboration
📝 Summary:
Existing multi-agent LLM software development yields a single solution, missing better alternatives. We introduce Cross-Team Collaboration CTC, a framework where multiple agent teams propose and communicate diverse decisions. This significantly improves software quality and generalizes well.
🔹 Publication Date: Published on Jun 13, 2024
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2406.08979
• PDF: https://arxiv.org/pdf/2406.08979
• Github: https://github.com/OpenBMB/ChatDev
✨ Spaces citing this paper:
• https://huggingface.co/spaces/shanghengdu/LLM-Agent-Optimization-PaperList
==================================
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✓ https://t.me/DataScienceT
#MultiAgentSystems #LLMAgents #SoftwareDevelopment #AICollaboration #AIResearch
📝 Summary:
Existing multi-agent LLM software development yields a single solution, missing better alternatives. We introduce Cross-Team Collaboration CTC, a framework where multiple agent teams propose and communicate diverse decisions. This significantly improves software quality and generalizes well.
🔹 Publication Date: Published on Jun 13, 2024
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2406.08979
• PDF: https://arxiv.org/pdf/2406.08979
• Github: https://github.com/OpenBMB/ChatDev
✨ Spaces citing this paper:
• https://huggingface.co/spaces/shanghengdu/LLM-Agent-Optimization-PaperList
==================================
For more data science resources:
✓ https://t.me/DataScienceT
#MultiAgentSystems #LLMAgents #SoftwareDevelopment #AICollaboration #AIResearch