How to manage AI investments in the agentic era
Learn how enterprises can manage AI investments in the agentic era by measuring useful work per dollar, improving efficiency, and scaling high-value workflows.
How Netomi scales enterprise AI agents using GPT-4. 1 and GPT-5.
Learn how enterprises can manage AI investments in the agentic era by measuring useful work per dollar, improving efficiency, and scaling high-value workflows.
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.
arXiv:2606. 12835v1 Announce Type: cross Abstract: The rapid emergence of autonomous AI agents is transforming artificial intelligence from isolated model inference into distributed systems of reasoning, communication, and action.
Notion rebuilt its AI architecture with GPT-5 to create agents that reason, act, and adapt across workflows, unlocking faster and more flexible productivity in Notion 3. 0.
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.
GPT-5 is OpenAI’s most advanced model—transforming enterprise AI, automation, and workforce productivity in the new era of intelligent work.
Explore lower GPT‑5. 6 pricing for Luna and Terra—and how OpenAI’s more efficient models help enterprises deploy AI workflows at scale.
Cloudflare brings OpenAI’s GPT-5. 4 and Codex to Agent Cloud, enabling enterprises to build, deploy, and scale AI agents for real-world tasks with speed and security.
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.
arXiv:2607. 07052v1 Announce Type: cross Abstract: AI agents deployed for IT operations are typically permanent cost centers because every execution requires full LLM inference, even for previously solved problems.
arXiv:2505. 21550v2 Announce Type: replace-cross Abstract: Collaborative agentic AI is projected to transform entire industries by enabling AI-powered agents to autonomously perceive, plan, and act within digital environments.