# How LLMs Handle Memory Through Context and Surrounding Applications

DevFeed: [How LLMs Handle Memory Through Context and Surrounding Applications](<https://devfeed.tech/articles/do-llms-have-the-memory-of-a-goldfish-26892.md>)

Original publisher: [Read original article](<https://blog.bytebytego.com/p/do-llms-have-the-memory-of-a-goldfish>)

Author: ByteByteGo

Published: 2026-09-15T15:31:12Z

Content type: article

Language: en

Sources: [ByteByteGo](<https://devfeed.tech/sources/bytebytego.md>)

Topics: [Large Language Model](<https://devfeed.tech/topics/llm.md>), [context window](<https://devfeed.tech/topics/context-window.md>), [App](<https://devfeed.tech/topics/app.md>), [long-context](<https://devfeed.tech/topics/long-context.md>)

Tags: [article](<https://devfeed.tech/tags/article.md>), [context](<https://devfeed.tech/tags/context.md>), [context-window](<https://devfeed.tech/tags/context-window.md>), [cost](<https://devfeed.tech/tags/cost.md>), [latency](<https://devfeed.tech/tags/latency.md>), [llms](<https://devfeed.tech/tags/llms.md>), [memory](<https://devfeed.tech/tags/memory.md>)

## AI overview

LLMs do not usually retain personal or persistent memory between interactions. Surrounding applications create the appearance of memory by storing messages, maintaining summaries, retrieving relevant information, and supplying it to the model. As conversations grow, this processing increases cost and latency, while context-window limits require older information to be removed, summarized, or stored elsewhere.

## Source excerpt

In this article, we will learn how LLMs handle memory so that they are useful to end users in performing complex tasks that require conversation and holding context.