How to Build Reliable AI Systems.

Building reliable AI systems for production requires engineering solutions beyond better prompts to address three critical failure modes. AI systems are probabilistic and unpredictable, demanding the "validator sandwich pattern" with input/output guardrails around structured LLM responses to ensure consistency. Silent failures from model hallucinations require observable pipelines that monitor confidence scores, latency, and costs to catch degradation early. Uncontrolled costs need gated architectures with rate limiting, caching, request queues, and circuit breakers to prevent runaway expenses at scale.