A SaaS company has a customer support chatbot with a 60K-token system prompt containing product documentation, policy rules, and escalation procedures. The system prompt is identical for all customer sessions. The team notices that each API call takes 3-4 seconds just to process the system prompt before the user's question is even considered. They want to reduce this overhead. What feature should they use?
Prompt Caching
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A team has a 50K-token system prompt that rarely changes. They want to reduce latency. What should they do?
A startup uses prompt caching for their AI coding assistant. The system prompt includes a 20K-token library of coding standards. The CTO is reviewing the monthly API bill and notices that input tokens are the largest cost. They ask the engineering team how prompt caching affects pricing. Currently, the team makes 100,000 requests per month with a 20K cached system prompt. How does prompt caching change the cost structure?