LLM Prompt Caching
Optimizes LLM performance and reduces API costs through advanced prompt caching, response caching, and Cache Augmented Generation (CAG) patterns.
Optimizes LLM performance and reduces API costs through advanced prompt caching, response caching, and Cache Augmented Generation (CAG) patterns.
This skill provides comprehensive strategies and implementation patterns for managing LLM context efficiently. It covers Anthropic's native prompt caching for stable system prompts, Redis-based response caching for repeated queries, and Cache Augmented Generation (CAG) to handle static document corpuses within the context window. By implementing these patterns, developers can achieve up to a 90% reduction in token costs and significantly lower latency for frequently used AI interactions while avoiding common pitfalls like cache-miss overhead and stale data.