How V7 gives AI agents institutional memory

V7 cuts costs 78% while boosting accuracy with GPT-5.6 Luna

Using GPT-5.6, V7 turns scattered company files into context agents can use to complete complex, source-linked work.

Inside OpenAI’s in-house data agent

How OpenAI built an in-house AI data agent that uses GPT-5, Codex, and memory to reason over massive datasets and deliver reliable insights in minutes.

Notion’s GPT‑5 rebuild unlocks autonomous AI workflows

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.

Repo-To-Skill: Distilling GitHub Repositories Into AI4AI Skills

The paper introduces Repo-To-Skill, a method for converting GitHub repositories into reusable AI skills. By distilling operational knowledge from over 1,000 machine‑learning repositories, the authors build the AREX‑Skill Library with more than 5,000 verified skills across 20 areas. Integrating these skills into a research agent—DisCo—yields significant performance boosts on multiple benchmarks, demonstrating the value of reusable, task‑agnostic knowledge.

Repo-To-Skill: Distilling GitHub Repositories Into AI4AI Skills

Repo-To-Skill: Distilling GitHub Repositories Into AI4AI Skills introduces DisCo, a research agent that extracts and verifies operational knowledge from GitHub repositories to create reusable AI skills. The agent produces both task‑agnostic skills—compiled into the AREX‑Skill Library of over 5,000 verified skills from 1,000 repositories—and task‑oriented skills tailored to specific research tasks. When equipped with these skills, the agent achieves significant performance gains across multiple benchmarks, outperforming a skill‑free version by 134.3% on MLE‑bench, 34.4% on PaperBench, 9.2% on FrontierCS, and 14.0% on PassNet.

Dr. AGENTONOMICS: A Didactic Experiment of AGENTONOMICS

arXiv:2608. 03524v1 Announce Type: new Abstract: AGENTONOMICS is a framework that treats AI agents as economic entities that can be designed, managed, and governed through an integrated management architecture.

Subagents vs Agent Skills: Executing Reusable Knowledge for Long-Horizon Agentic Tasks

arXiv:2609.09233v1 Announce Type: cross Abstract: How can language model agents effectively leverage libraries of reusable knowledge to solve long-horizon tasks? Recent work has increasingly focused...

The builder’s guide to GPT‑5.6

Learn how startups use GPT-5. 6 to build faster, more cost-efficient AI agents with smarter model selection and new Responses API capabilities.

GPT-5 and the new era of work

GPT-5 is OpenAI’s most advanced model—transforming enterprise AI, automation, and workforce productivity in the new era of intelligent work.

Netomi’s lessons for scaling agentic systems into the enterprise

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

Give Your Coding Agents a Memory You Own

AI Agents Are Here. What Now?