Your AI system produces inconsistent outputs — sometimes excellent, sometimes completely wrong, with no predictable failure pattern. Design an approach to make it more reliable and deterministic. Cover: structured output enforcement (schemas, grammar-constrained generation), output validation layers, confidence scoring and fallback paths, ensemble approaches and majority voting, adversarial testing to find brittleness before users do, and how to build a regression suite that catches reliability issues in CI. What does a production-ready reliability architecture look like?