{
  "id": 20,
  "url": "https://arxiv.org/abs/2607.11138v1",
  "title": "A Formal Hierarchical Architecture for Agentic Orchestration with Stack-Based Execution and Lazy Discovery",
  "summary": "The rapid expansion of capabilities in Large Language Model (LLM) agents has exposed a critical architectural bottleneck: when agents are given access to a flat, monolithic registry of tools, the model must evaluate hundreds or thousands of options simultaneously. This leads to decision-space explosion, context window saturation, and degraded routing accuracy. To address these limitations, this paper presents a hierarchical, skill-based architecture for agentic orchestration. Capabilities are or",
  "authors": "Prashant Devadiga, Abhishek, Adithya Mishra, Alok Singh, Amisha Sinha, Asit Desai et al.",
  "category": "research",
  "topics": "agents-autonomy",
  "orgs": null,
  "regions": null,
  "published_at": "2026-07-13T06:15:51.000Z",
  "fetched_at": "2026-07-14T14:14:15.663Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/20",
  "original_url": "https://arxiv.org/abs/2607.11138v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}