The next big breakthrough will be AIs learning on the job
Dwarkesh Patel
The author’s central question is whether AI can turn scarce, messy work experience into efficient, lasting learning—not just get better at repeatable training tasks.
Open library
The library
The essential reading of generative AI and agents, open in a clean reading view, with Meow and Standard summaries when available. No account needed to read.
560 papers · 558 with a Meow summary · 333 posts
Key publications from Anthropic, OpenAI, Google DeepMind, Meta, DeepSeek, Qwen, Z.ai, Kimi and other labs, plus the most influential essays and blogs.
The Open Source Community is backing OpenEnv for Agentic RL
ben burtenshaw · Hugging Face
OpenEnv is moving to committee coordination and a clearer role as shared RL-environment infrastructure—not a framework for rewards or training loops—so agents can work across tools without one mandated stack.
Agent Lightning v1.0: A 3,500-Line Lightweight Agentic RL Framework for Training Agents with Real Harnesses
Brenda Potts · Microsoft Research
Agent Lightning v1.0 trains agents through the same harness used in deployment, avoiding a costly reimplementation inside the RL framework.