{
  "id": 4455,
  "url": "https://arxiv.org/abs/2605.12280v2",
  "title": "Iterative Audit Convergence in LLM-Managed Multi-Agent Systems: A Case Study in Prompt-Engineering Quality Assurance",
  "summary": "Prompt specifications for multi-agent large language model (LLM) systems carry data contracts and integration logic across interdependent files but are rarely subjected to structured-inspection rigor. We report a single-system case study of iterative, agent-driven auditing applied to AEGIS (Autonomous Engineering Governance and Intelligence System), a seven-lane production pipeline whose 7152-line specification surface was audited across nine rounds, surfacing 51 consistency defects (per-round c",
  "authors": "Elias Calboreanu",
  "category": "research",
  "topics": "regulation,agents-autonomy,transparency",
  "orgs": null,
  "regions": null,
  "published_at": "2026-05-12T15:39:04.000Z",
  "fetched_at": "2026-07-14T16:30:59.239Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/4455",
  "original_url": "https://arxiv.org/abs/2605.12280v2",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}