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…