Why RL Environments are all you need for building agents

RL Environments are used by frontier labs to train their latest models and agents. In this talk, I will explain why RL environments are fundamental to all stages of building agents: from evaluations and prompt optimization to post-training agents. I will show concrete industry examples of how practitioners use RL environments to evaluate their agents, and to understand how their agents fail. Lastly, I will also talk about how one can set up data flywheels which helps you figure out how to improve your agents on your specific data and use-cases.