EMAS: Stabilizing Multi-Agent System Evolution through Evidence-Guided Revision
The episode discusses EMAS, a method for evolving multi-agent systems by revising prompts and topology based on execution evidence. Hosts highlight its recurrence gate and paired validation to prevent regressions, noting strong results like Qwen code generation accuracy rising from 55% to 89% with 62% fewer tokens.