arXiv:2607. 20759v1 Announce Type: cross Abstract: AI coding agents powered by LLMs are increasingly integrated into real-world software development, where they generate, edit, and execute code with autonomous access to local files and tools.
By Ankur Singh, Jinqiu Yang, Tse-Hsun Chen
arXiv:2606. 05647v1 Announce Type: new Abstract: AI coding agents are increasingly embedded in real-world software development, collaborating with human developers while gaining broader access to codebases and tools.
By Jingheng Ye, Huiqi Zou, Simon Yu, Weiyan Shi
arXiv:2607. 23624v1 Announce Type: cross Abstract: Third-party API routers have become a common layer that unifies access across increasingly diverse LLM providers.
By Donghao Fu, Jingxin Li, Xue Jiang, Yihong Dong
arXiv:2607. 25890v1 Announce Type: new Abstract: AI coding agents are being adopted at historic speed, yet security and risk concerns remain the primary barrier to scaling agentic AI across organizations.
By William Robert Gore
arXiv:2608. 14876v1 Announce Type: cross Abstract: Agentic coding assistants are finding widespread use, not just in new code development but in quickly ingesting and leveraging third-party code.
By Alexandre G. R. Day, Pradeep Yadlapalli, Sriram Venkatapathy, Thomas Paniagua, Nick Raines, Sahil Wadhwa, Himanshu Kumar, Andy Luo, Sudeep Panyam, Rikhiya Ghosh, Pranab Mohanty, Giri Iyengar
arXiv:2607. 29254v1 Announce Type: new Abstract: AI agents extend large language models (LLMs) with external tools, enabling them to perform complex tasks and translate model outputs into consequential real-world actions.
By Minghui Pan, Jiayuxuan Yang, Yuanyuan Yuan, Yu Jiang, Zhenpeng Chen