A startup launched their AI-powered customer support bot and watched their API bill climb to $100,000 per month within weeks. Every customer message triggered a call to their most powerful (and expensive) model with the entire conversation history stuffed into the prompt. After applying a systematic optimization strategy, semantic caching for common questions, routing simple queries to a smaller model, compressing conversation history, and batching non-urgent requests, they cut costs to $20,000 per month with no measurable drop in quality. The techniques aren't secrets, but most teams don't apply them until the bill becomes painful. Learning them upfront can save your project before cost pressure forces you to cut corners on quality.