Modeling Human Communication to Build Context-Awareness into LLM Caching

One of the most fun parts of working with LLMs is finding solutions to technical problems in the ways people have solved the same problems in interpersonal communication.

Semantic caching reduces LLM costs and latency, but simple vector similarity search doesn't work well for conversational AI. To make semantic caching effective for context-dependent we’ve modeled features of human communication into our cache.

Have human communcation features helped you solve any LLM application problems? Share them in the comments!