How I Cut My Claude API Costs by 80% with Caching and Model Selection
Two weeks into running my first AI-powered API endpoint, I noticed the Claude bill climbing in a way that didn't match the traffic. Not catastrophic yet, but the trajectory was clear — if I didn't change something, the API cost would outpace any revenue the project could generate. The fix wasn't one thing. It was three changes applied together: using cheaper models for routine tasks, caching responses so the same question doesn't get answered twice, and trimming prompts to stop paying for words that didn't improve the output. Combined, they cut my effective per-call cost by roughly 80%. Here's each one, with the actual numbers. The Problem: One Model for Everything My initial setup was simple and expensive. Every AI call — whether it was generating a 200-word market sentiment report or categorizing a single log entry — went through Claude Sonnet. Sonnet is the strongest model. It's also the most expensive. Using it for a task that Haiku handles equ...