RL environment creation is becoming continuous QA - Rishi Desai

Why automating RL environment creation means building the loop around task generation.

RL environment creation is becoming continuous QA - Rishi Desai Contents RL environment creation is becoming continuous QA May 27, 2026 • Rishi Desai There has been a lot of discussion about automating RL environment creation. Most of it focuses on task generation: can an agent write the instructions, verifier, and reference solution? That is only the first step. A generated environment is not useful until it has survived contact with frontier agents. A pass is not automatically evidence that the task is good; it may reveal a shortcut, ambiguity, or weak verifier. A failure is not automaticall

related reading

• A Taxonomy of RL Environments for LLM Agentsleehanchung.github.io
• Demystifying evals for AI agents \ Anthropicanthropic.com
• Trust me bro, just one more RL scale up, this one will be the real scale up with the good environments, the actually legit one, trust me bro — AI Alignment Forumalignmentforum.org
• RL Environments and RL for Science: Data Foundries and Multi-Agent Architecturesnewsletter.semianalysis.com
• The Era of Experience Paper.pdfstorage.googleapis.com
• LLM Powered Autonomous Agents | Lil'Loglilianweng.github.io
• Debugging Reinforcement Learning Systemsandyljones.com
• Welcome to The Era of Evalsmercor.com
• Cheap RL tasks will waste compute | Mechanize, Inc.mechanize.work
• The Bitter Lesson - RL Environments Versionseancai.com
• Akash Bajwa on X: "RL Environments with Scale AI" / Xx.com
• Don't Build an RL Environment Startupbenanderson.work