DeepLearning.AI

Harrison Chase

In this course, you will learn how to build an agent with long-term memory by creating a personal email agent that can respond, ignore, and notify the user using writing, scheduling, and memory tools. You’ll develop your agent’s memory by adding facts to its memory store, providing examples to learn the user’s preferences, and optimizing system prompts to evolve instructions based on previous responses. This course will equip you with the skills to integrate semantic, episodic, and procedural memory into AI agents, enhancing their functionality and user interaction.

Long-Term Agentic Memory with LangGraph

An overview of the course and its objectives, including a brief introduction to agent memory.

Introduction

Detailed explanation of how memory works in agents, covering semantic, episodic, and procedural memory.

Introduction to Agent Memory

Building a basic email assistant with code examples to understand the foundational concepts.

Baseline Email Assistant

Enhancing the email assistant by integrating semantic memory to store and retrieve user facts.

Email Assistant with Semantic Memory

Further development of the email assistant by adding episodic memory for learning user preferences.

Email Assistant with Semantic + Episodic Memory

Completing the email assistant by incorporating procedural memory to optimize system prompts.

Email Assistant with Semantic + Episodic + Procedural Memory

Summarizing the course content and reinforcing the key learning outcomes.

Conclusion

A short quiz to test the knowledge gained throughout the course.

Quiz

Additional resources and tips to assist learners in applying the course content.

Appendix - Tips and Helps

Learn to build an agent with long-term memory in this course, created in partnership with LangChain and taught by its Co-Founder and CEO, Harrison Chase. By the end of this course, you will have the foundational mental framework to build an agent with long-term memory using LangGraph.

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Long-Term Agentic Memory with LangGraph

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