How to Build Reliable AI Systems.

Building reliable AI systems in production requires engineering discipline beyond prompt crafting. Three critical failure modes are addressed: inconsistent outputs (solved with the validator sandwich pattern — input guardrails, structured LLM outputs via JSON schema enforcement, and output guardrails), silent failures (solved with observable pipelines that log confidence scores, latency, cost, and route low-confidence results to human review), and uncontrolled costs (solved with gated pipelines using Redis-based rate limiting, caching, request queues, and circuit breakers). A complete production architecture combining all three layers is demonstrated with TypeScript/Node.js code examples, showing how to go from a fragile prototype to a system handling 10,000+ requests per day reliably.