LLM Can't Enforce Hard Boundaries: Keep Final Decisions Outside the Probabilistic Engine
forevergeeks · reddit · 2026-09-29
The author proposes a "Law of Probabilistic Entropy": a probabilistic engine cannot be relied on to enforce absolute boundaries by itself.
- You can instruct an LLM never to do something, but an instruction is not a hard boundary.
- If something is truly forbidden, don't leave the final decision to the probabilistic system you're trying to control.
- AI can recommend an action, but the boundary should be enforced elsewhere.
The core claim: safety constraints belong in a deterministic layer outside the model, not in the model's own compliance.
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