I Added Four Lines of Code and Cut My Claude Agent’s Cost by 57%
Anthropic's docs on prompt caching are clear about the mechanics. You cache a stable prefix and pay a small premium the first time you write it. After that every read comes back at roughly a tenth of the normal input price. Search around and you'll find a dozen 2026 blog posts repeating the same 60-90% savings figure and the same breakeven math. What's harder to find is a real before-and-after test on one specific, common shape of agent. Its system prompt carries a large, mostly-static schema description on every single turn, sitting next to a small question that changes each time. That's the exact shape of a BI chat agent. It's the shape I already had built and running.
I already had a Claude-based BI assistant built for a separate comparison, tested against a production-scale synthetic retail warehouse: customers, orders, order line items, promotions, returns, a separate wholesale side and...
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