CS107 Lecture 25 builds the essential cache model from a concise deck: memory access costs are nonuniform, smaller and faster layers retain data likely to be reused, and temporal and spatial locality determine whether a program benefits.
After dissecting Claude Code's 18+ caching mechanisms, I found that you can't touch provider-level prompt cache, but embedding cache, tool result cache, and entity cache are not only within your reach — they deliver even better results. Includes a complete AgentCache interface design and per-tool TTL strategy.
KV is Cloudflare's globally distributed key-value store. Reads are served from the nearest edge node with extremely low latency. It's ideal for caching, feature flags, and ephemeral data — but writes are eventually consistent.
Redis is an in-memory key-value store that's blazingly fast. DaoDao uses it to handle three responsibilities at once — API caching, session storage, and BullMQ job queues — all from a single Redis instance.