Improving Composer through real-time RL

Cursor describes "real-time RL," a technique that uses production inference tokens from its Composer agentic coding model as training signal, with user responses aggregated as reward. This closes the train-test mismatch by replacing simulated users with real ones, enabling checkpoint deploys as frequently as every five hours. The approach was first validated on Tab and is now applied to Composer's Auto mode.