Abstract
Conversational artificial intelligence systems may experience inefficiencies when processing high-frequency initial user queries, as routing repetitive requests to a backend generative model can lead to redundant computations and increased response latency. A response caching system can use pre-model and post-model execution callbacks to manage a cache, for example, an in-memory cache. For certain requests, such as qualifying first-turn requests, the system may generate a context-aware composite key from a user's query text, an agent's system instructions, and its available tools. If a matching key is found, a stored response can be returned, which may bypass a call to the backend model. This approach may reduce response latency for common queries, lessen the computational load on backend systems, and decrease associated operational costs.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Aggarwal, Ankit, "First-Turn Response Caching for Conversational AI Agents Using Context-Aware Keys", Technical Disclosure Commons, (July 27, 2026)
https://www.tdcommons.org/dpubs_series/11140