Cost Optimization
The practical work of making your AI API usage cost less — through better model selection, smarter prompts, caching repeated content, batching requests, and routing simple tasks to cheaper models. Many teams discover that 80% of their API requests are simple enough for a smaller, cheaper model — and only 20% genuinely need the most capable (and expensive) one. Getting this right is often the difference between an AI feature that's financially viable and one that's not.
In practice
You're running 10,000 API calls a day and your bill is $800/month. You switch shorter, simpler requests from Claude Sonnet to Claude Haiku (10x cheaper) and turn on prompt caching for the system prompt that's the same on every call. Your bill drops to $200. That's cost optimization — getting the same quality output for less money.
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