Continual Harness: First AI System Completes Pokemon Without a Lost Battle via Self-Improving Embodied Agent

arXiv·high signal

Princeton and Google DeepMind introduce Continual Harness, a reset-free self-improving runtime for embodied agents that alternates between acting and refining its own prompt, sub-agents, skills, and memory without human involvement. In Gemini Plays Pokemon experiments, the system became the first AI to complete Pokemon Blue, Yellow Legacy on hard mode, and Crystal without a single lost battle. Formalizes the observe-refine loop that coding harnesses like Claude Code provide for software agents, extending it to embodied settings.