Neo4j Agent Memory Workshop
Build an AI agent with persistent, explainable memory backed by Neo4j - short-term, long-term, and reasoning - using the neo4j-agent-memory package.
In this 3-hour workshop, you will learn
In this workshop, you will build an AI agent with persistent, explainable memory backed by Neo4j using the neo4j-agent-memory package.
You will work through the three layers of agent memory - short-term conversation, long-term knowledge, and reasoning traces - and see how they connect as a single context graph in Neo4j. Each lesson pairs a short explanation with code you run in your own environment.
By the end of the workshop, you will have built a Pydantic AI learning assistant that records what a learner understands, grounds its recommendations in a course knowledge graph, and writes its reasoning trace into Neo4j.
- Neo4j Fundamentals - graph database concepts
- Cypher Fundamentals - query language basics
- Neo4j & GenAI Fundamentals - generative AI and GraphRAG concepts
- Basic Python - reading and writing simple Python programs
Agent Memory
neo4j-agent-memory
Context Graphs
Reasoning Traces
POLE+O
What you need to take part.
A GraphAcademy account
The workshop is delivered here on GraphAcademy, so you need to be signed in to work through the lessons and keep your progress. Creating an account is free.
A GitHub account, or Git on your own machine
You write code against the workshop-agent-memory repository. The quickest route is a GitHub Codespace, an online editor that clones the code and installs everything for you — that needs a GitHub account.
If you would rather work locally, clone the repository with Git and run it in your own editor instead. No GitHub account is needed for that.
5 modules, 3 hours 20 minutes.
Workshop AI access
This workshop provides temporary access to a hosted language model. Accept the terms and copy your credentials from within any lesson.
Default model: gpt-5.2