Ash Prabaker

This talk explores the evolution of AI agents, focusing on enabling them to run for extended periods, from minutes to hours or even days. It details the challenges of long-running agents, such as context limitations and model judgment, and presents Anthropic's approach to overcoming these through model improvements and harness development. The discussion highlights how co-evolving models and scaffolding have led to more capable and autonomous AI systems.