OpenAI Blog

Netomi’s lessons for scaling agentic systems into the enterprise

How Netomi scales enterprise AI agents using GPT-4. 1 and GPT-5.

Microsoft Research
Aug 3

Orchard: An open framework for scalable agentic AI

Orchard is an open-source framework for the research community to train and evaluate AI agents across task types. It reduces complexity while supporting strong performance from smaller models by enabling researchers to reuse the same infrastructure.

By Baolin Peng, Wenlin Yao, Qianhui Wu, Hao Cheng, Jianfeng Gao
arXiv AI
2d ago

LLM-based Agentic Reasoning Frameworks: A Survey from Methods to Scenarios

The article surveys LLM-based agentic reasoning frameworks, presenting a unified formal language that categorizes them into single-agent, tool-based, and multi-agent methods. It reviews application scenarios in scientific discovery, healthcare, software engineering, society, economics, and general-purpose tasks, and compares the distinct features and evaluation strategies of each category. The survey highlights the rapid development of complex agentic systems in real-world contexts.

By Bingxi Zhao, Lin Geng Foo, Ping Hu, Christian Theobalt, Hossein Rahmani, Jun Liu
arXiv AI
Jul 22

Agents in the Wild: Where Research Meets Deployment

arXiv:2607. 19336v1 Announce Type: new Abstract: Agentic systems large language model (LLM) based architectures capable of reasoning, planning, acting, and coordinating with tools and other agents are rapidly transitioning from research prototypes to production scale deployments across domains such as software engineering, scientific discovery, and finance.

By Grace Hui Yang, Pranav N. Venkit, Hooman Sedghamiz, Enrico Santus, Victor Dibia, Ioana Baldini