From RL to IRL — Gaurav Mishra, Amazon AGI Lab
Aug 14, 2026 · 17:46
Gaurav Mishra of the Amazon AGI Lab explains why RL for computer-use agents works in games but breaks in real life, and how his team turns failures into training data. He shows early browser-training runs where an agent guesses its password and locks the account, and clicks a sponsored button styled like the submit button, landing elsewhere. The talk catalogs partial observability, irreversibility, expiring credentials, and ambiguous success, then proposes flight-school sandboxes, process reward models, calibrated confidence, and adversarial tasks. A later trajectory shows the agent recognizing the sponsored button, refusing to guess the password, and handing off to the user, echoing the talk's point that the difference between a demo and a product is what happens after the first failed click.
