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  "path": "/t/can-llm-agents-develop-precognition/177347#post_3",
  "publishedAt": "2026-07-03T07:11:27.000Z",
  "site": "https://discuss.huggingface.co",
  "textContent": "This is a very helpful framing. I agree that “consequence-aware action admission” is probably the more operational version of what I’m calling agent precognition.\n\nThe goal is not prediction in the strong sense. The goal is that a candidate action should not become executable until target, scope, missing inputs, constraints, side effects, reversibility, uncertainty, authorization needs, and likely consequences have been made explicit.\n\nThat is how I see the action-preflight SYLLOG: not as a replacement for guardrails, authorization, sandboxing, tracing, or HITL, but as a reusable cognitive contract that can feed those layers.\n\nIt turns a vague candidate action into something the runtime can route:\n\nproceed / clarify / revise / approve / escalate / block\n\nI also agree that not every step needs to be an LLM deliberation. A lot of preflight should be cheap and structural: schema checks, required fields, target/scope, side-effect class, reversibility, consent, authorization, and policy. The richer SYLLOG path is most useful when the action is ambiguous, consequential, externally visible, private, delegated, or hard to reverse.\n\nSo yes, I really like your formulation:\n\n“not agents predicting the future, but agent actions earning admission into execution.”\n\nThat captures the practical version of the idea very well. I was deliberately playing with words in the post",
  "title": "Can LLM Agents Develop Precognition?"
}