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  "path": "/t/why-llm-agents-keep-failing-and-it-s-not-the-prompt/175361#post_1",
  "publishedAt": "2026-04-18T12:01:56.000Z",
  "site": "https://discuss.huggingface.co",
  "tags": [
    "Zenodo",
    "Beyond Prompting: Decoupling Cognition from Execution in LLM-based Agents...",
    "https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6600840"
  ],
  "textContent": "Most LLM agent failures I’ve seen share the same pattern:\n\nThey don’t break because of the model.\nThey don’t break because of the prompt.\n\nThey break because we force the system to “figure everything out” from scratch on every interaction.\n\n* * *\n\nIn traditional software, we don’t rebuild logic every time we run a function.\nWe define structure, reuse components, and control execution.\n\nWith LLM agents, we’re doing the opposite.\n\n* * *\n\nThis led me to explore a different approach:\n\n-> What if reasoning wasn’t embedded in prompts,\n→ but structured and executed as reusable components?\n\nThat’s the idea behind ORCA — a cognitive runtime for LLM agents.\n\n* * *\n\nI’ve put the full concept in a paper in zenodo and now also on SSRN:\n\nZenodo\n\n### Beyond Prompting: Decoupling Cognition from Execution in LLM-based Agents...\n\nRecent advances in large language model (LLM) agents have largely relied on prompt-centricdesigns, where complex tasks are executed through monolithic, single-shot or loosely structuredprompting strategies. While effective in some settings, this...\n\nhttps://papers.ssrn.com/sol3/papers.cfm?abstract_id=6600840\n\nCurious if others are hitting the same limits with prompt-based systems.",
  "title": "Why LLM agents keep failing (and it’s not the prompt)"
}