In this article, you will learn how agent memory works, what types of memory exist, and how different frameworks approach storage, retrieval, and memory management at scale.

Topics we will cover include:

The core memory types used in AI agents and what each one is designed to store.

Practical design strategies for writing, retrieving, and maintaining agent memory reliably.

How leading memory frameworks differ in their storage models, retrieval approaches, and handling of fact changes over time.

Introduction

A language model does not retain information between calls. Each time it runs, it works with the text provided in that request and does not automatically remember what happened before. This works well for simple, one-off questions, but AI agents need more when they have to track previous actions, remember user preferences, or continue a task across multiple steps.

Memory solves this by storing information outside the model’s context window and making it available when needed.…