Overview of agentic memory - Amazon ElastiCache
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Overview of agentic memory

An agentic AI application is a system that takes actions and makes decisions based on input. These agents use external tools, APIs, and multi-step reasoning to complete complex tasks. Without persistent memory, agents forget everything between conversations, making it impossible to deliver personalized experiences or complete multi-step tasks effectively.

Agentic memory handles the persistence, encoding, storage, retrieval, and summarization of knowledge gained through user interactions. This memory system is a critical part of the context management component of an agentic AI application, enabling agents to learn from past conversations and apply that knowledge to future interactions.

Consider the following examples where agentic memory provides value:

  • Customer support agents – An agent remembers a customer's previous issues, preferences, and account details across support sessions, avoiding repetitive information gathering and delivering faster resolutions.

  • Research agents – An agent that researches GitHub repositories remembers previously discovered project metrics, avoiding redundant web searches and reducing token usage and response time.

  • Personal assistant agents – An agent retains a user's scheduling preferences, communication style, and recurring tasks to provide increasingly personalized assistance over time.