Production AI applications fail in ways traditional software doesn't. Models go down, tokens run out, responses hallucinate, and rate limits hit at the worst moments. Here's how to build reliable AI-powered systems. The AI Reliability Problem Traditional APIs return consistent responses or clear errors. AI APIs introduce new failure modes: Model outages — The provider's model goes down Rate limits — You've exhausted your quota mid-request Token limits — Your prompt exceeds context window Hallucinations — Model returns plausible but wrong answers Timeout — Request takes too long and hangs Invalid JSON — Model returns malformed structured data Retry Logic with Exponential Backoff `typescript async function withRetry( fn: () => Promise, options: { maxRetries?: number; baseDelay?: number; maxDelay?: number; onRetry?: (attempt: number, error: Error) => void; } = {} ): Promise { const { maxRetries = 3, baseDelay = 1000, maxDelay = 30000, onRetry } = options; for (let attempt = 1; attempt <= maxRetries +…