Strategic Prompt Caching with Multi-TTL Breakpoint Architecture

Anthropic·high signal

Claude's prompt caching API caches up to 90% of input tokens at 10% of normal cost, but naive breakpoint placement leaves most savings on the table. Structuring prompts in descending order of change frequency (tools → system instructions → background context → conversation) and using mixed 1-hour and 5-minute TTLs can shift API spend by 85–90% at scale. Monitoring cache_read vs cache_creation token ratios exposes unstable content that silently invalidates cache blocks.