{
  "id": 7062,
  "url": "https://arxiv.org/abs/2603.17787v1",
  "title": "Governed Memory: A Production Architecture for Multi-Agent Workflows",
  "summary": "Enterprise AI deploys dozens of autonomous agent nodes across workflows, each acting on the same entities with no shared memory and no common governance. We identify five structural challenges arising from this memory governance gap: memory silos across agent workflows; governance fragmentation across teams and tools; unstructured memories unusable by downstream systems; redundant context delivery in autonomous multi-step executions; and silent quality degradation without feedback loops. We pres",
  "authors": "Hamed Taheri",
  "category": "research",
  "topics": "regulation,agents-autonomy",
  "orgs": null,
  "regions": null,
  "published_at": "2026-03-18T14:49:31.000Z",
  "fetched_at": "2026-07-14T16:32:54.537Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/7062",
  "original_url": "https://arxiv.org/abs/2603.17787v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}