By design, Large Language Models (LLMs) are non-deterministic. Even with an identical prompt, they can return different answers, trigger the wrong API, leak sensitive personal data, or initiate a costly chain of requests that evaporates a monthly cloud budget in seconds. For engineers managing production systems, this isn't an abstract risk — it's the nightmare scenario that keeps them up at night.

The solution does not lie in hoping for better models. Instead, it lies in a deterministic guardrail layer that governs the agent, regardless of the model's output.…