{
  "id": 6382915,
  "title": "Procedural Graphs: Self-Evolving Execution Structures for LLM Agents",
  "url": "https://urgent.news/2026/09/08/procedural-graphs-self-evolving-execution-structures-for-llm-agents",
  "topic": "ai",
  "section": "AI",
  "published": "2026-09-08T17:59:41.000Z",
  "source": {
    "name": "arXiv cs.AI",
    "slug": "arxiv-cs-ai",
    "url": "https://arxiv.org/abs/2609.09153v1"
  },
  "original_language": "en",
  "account": null,
  "summary": "Large language models are increasingly deployed as agents that plan over long horizons and act through external tools. Most agents select actions through unconstrained generation over an accumulating history, leaving implicit the procedural knowledge of what to do, in what order, and under which conditions. As trajectories lengthen, agents can lose track of their objectives, invoke tools out of…",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}