Guardrails for the robot: Architecting deterministic AI remediation in high-stakes platforms

By 2026, the novelty of "GenAI for DevOps" has worn off, replaced by a cold reality: LLMs are probabilistic engines in a deterministic world. For platform teams, an AI hallucination is not just a typo; it is a potential security breach or a production outage. In this session, John Kamenik outlines a shift in how AI-enabled platforms are architected. He argues that the key to scaling automation is not better prompting, but the implementation of a deterministic logic engine, a "semantic compiler" for infrastructure changes. John demonstrates a blueprint that treats AI as an "untrusted contributor," passing every proposed remediation through rigorous logic gates.