# Caching Responses for Repeated Questions in Production LLM Applications

DevFeed: [Caching Responses for Repeated Questions in Production LLM Applications](<https://devfeed.tech/articles/why-multi-turn-agents-need-more-than-a-task-graph-18248.md>)

Original publisher: [Read original article](<https://blog.dailydoseofds.com/p/why-multi-turn-agents-need-more-than>)

Author: Avi Chawla

Published: 2026-09-10T21:34:26Z

Content type: article

Language: en

Sources: [Daily Dose of Data Science](<https://devfeed.tech/sources/daily-dose-of-data-science.md>)

Topics: [Caching](<https://devfeed.tech/topics/caching.md>), [Redis](<https://devfeed.tech/topics/redis.md>), [Embeddings](<https://devfeed.tech/topics/embeddings.md>), [Large Language Model](<https://devfeed.tech/topics/llm.md>), [Inference](<https://devfeed.tech/topics/inference.md>)

Tags: [cache](<https://devfeed.tech/tags/cache.md>), [caching](<https://devfeed.tech/tags/caching.md>), [embeddings](<https://devfeed.tech/tags/embeddings.md>), [inference](<https://devfeed.tech/tags/inference.md>), [llm](<https://devfeed.tech/tags/llm.md>), [redis](<https://devfeed.tech/tags/redis.md>)

## AI overview

Production LLM applications can reduce repeated model calls by caching generated responses and matching new questions to prior questions using embeddings. The article discusses Redis LangCache, including similarity thresholds, expiration, data isolation, monitoring, and an example where a cache hit was roughly 6x faster than direct inference.

## Source excerpt

What production agents must preserve between turns, and what they must reset.