Iterative Audit Convergence in LLM-Managed Multi-Agent Systems: A Case Study in Prompt-Engineering Quality Assurance
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
Record details
Published: 12 May 2026
Source: arXiv
Category: Research
Topics: Regulation · Agents & autonomy · Transparency
Retrieved: 14 July 2026
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ethics.ai (12 May 2026), “Iterative Audit Convergence in LLM-Managed Multi-Agent Systems: A Case Study in Prompt-Engineering Quality Assurance,” evidence record 4455, https://ethics.ai/record/4455 (originally published by arXiv).
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