ByteDance's ByteBrain team developed MUSE-Autoskill, an AI framework that autonomously creates, tests, refines, and shares reusable skills for AI agents. These AI-generated skills achieve 87.94% accuracy compared to 68.40% for human-written skills and can transfer across different AI agents with minimal performance loss. The system treats skills as living assets with a full lifecycle including creation, evaluation, memory accumulation, management, and refinement. It automatically tests and fixes skills, maintains cross-task memory, and prunes unused or overlapping skills, enabling self-improving AI agent teams without manual intervention.

May 30, 2026, 7:04 AM