Build Agents That Run for Hours (Without Losing the Plot) — Ash Prabaker & Andrew Wilson, Anthropic

Why self-evaluation is a trap and adversarial evaluator agents work better; why context compaction doesn't cure coherence drift but structured handoffs do; how to decompose work into testable sprint contracts; how to grade subjective output with rubrics an LLM can actually apply; and how to read traces as your primary debugging loop. Plus the question nobody asks: which parts of your harness should you delete when the next model drops? Speaker info: - Ash Prabaker | https://www.linkedin.com/in/ash-prabaker/ - Andrew Wilson | https://www.linkedin.com/in/anddwilson/