Why Blind Retries Are Burning Your AI Budget Every AI app does the same thing when an API fails: retry. And retry. And retry. It feels right — the error says "503 Service Unavailable", so obviously the service will come back if we just try again, right? Wrong. And it's costing you real money. The Real Cost of Blind Retries Let's do the math on a typical production AI app making 100K API calls/day: Average failure rate : ~3-5% across major providers (based on public status pages) Blind retry success rate : <20% for non-transient errors (rate limits, auth failures, model-specific outages) Wasted tokens : Every failed retry consumed input tokens you paid for but got zero value from Latency penalty : Each retry adds 2-30 seconds of user-facing delay On a bad day — like OpenAI's April 20 outage or Claude's March 2 incident — your retry logic will happily burn through your entire API budget hitting a wall that isn't coming back. Not All Errors Are Created Equal This is the core problem.…