{
  "id": 3175,
  "url": "https://arxiv.org/abs/2606.04455v1",
  "title": "The Meta-Agent Challenge: Are Current Agents Capable of Autonomous Agent Development?",
  "summary": "Current AI benchmarks evaluate agents on task execution within human-designed workflows. These evaluations fundamentally fail to measure a critical next-level capability: whether models can autonomously develop agent systems. We introduce the Meta-Agent Challenge (MAC), an evaluation framework designed to test the capacity of frontier models for autonomous agent development. Specifically, a code agent (the meta-agent) is given a sandboxed environment, an evaluation API, and a time limitation to ",
  "authors": "Xinyu Lu, Tianshu Wang, Pengbo Wang, zujie wen, Zhiqiang Zhang, Jun Zhou et al.",
  "category": "research",
  "topics": "agents-autonomy,environment",
  "orgs": "meta",
  "regions": null,
  "published_at": "2026-06-03T04:58:17.000Z",
  "fetched_at": "2026-07-14T16:30:05.528Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/3175",
  "original_url": "https://arxiv.org/abs/2606.04455v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}