Reading Notes
Links, short summaries, and notes on what is worth noticing across AI, operations, strategy, and company-building.
Archive
A look at how OpenAI built its new enterprise agent to bring AI workers mainstream. OpenAI's ChatGPT Work combines past tools like Codex and browser control into one product for knowledge workers.
A major open-weight release worth testing for coding agents, deployment costs, and model selection. Qwen positions its 2.
How Chinese models cut agent workflow costs through architecture changes instead of just distillation. Multi-agent frameworks and coding tools are replacing standard chat and will drive enterprise AI billing.
Explains how top AI models are becoming cheap commodities and what open-weight models mean for geopolitics. OpenAI slashed GPT-5.
Details a new approach for generative models that scales inference compute to improve generalization, adding to standard data and parameter scaling. Researchers identified "Exploration" as a third pretraining axis that consistently improves text, image, and video models.
How OpenAI builds fast, cheap agent infrastructure internally. OpenAI shared five rules for keeping agent harnesses cheap and fast.
Explains why supervising an agent's step-by-step process is better for reliability than only checking its final output. Real-world tasks take time and involve many intermediate steps.