{
  "id": 16137,
  "url": "https://arxiv.org/abs/2608.01001v1",
  "title": "From AI Technical Debt to Agentic Technical Debt: A Systematic Mapping of Root Causes and Manifestations in Agentic AI Systems",
  "summary": "The emergence of Agentic AI systems, characterized by autonomous reasoning, multi-agent collaboration, tool orchestration, adaptive decision-making, and persistent memory, represents a fundamental shift from traditional AI pipelines to dynamic software ecosystems. While AI Technical Debt (AITD) has been widely studied in machine learning and software engineering, existing models assume static, component-level architectures and fail to capture the dynamic and emergent behaviors of agentic environ",
  "authors": "Muhammad Tukur, Hayatullahi B. Adeyemo, Tao Chen, Nour Ali, Anis Zarrad, Marco Agus, Rick Kazman, Rami Bahsoon",
  "category": "research",
  "topics": "agents-autonomy",
  "orgs": null,
  "regions": null,
  "published_at": "2026-08-02T05:09:28.000Z",
  "fetched_at": "2026-08-04T05:10:21.797Z",
  "source_slug": "x-arxiv-cs-cr-ai-security",
  "source_name": "arXiv cs.CR (AI security)",
  "source_homepage": "https://arxiv.org/list/cs.CR/recent",
  "ethics_ai_record_url": "https://ethics.ai/record/16137",
  "original_url": "https://arxiv.org/abs/2608.01001v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}