Course · Part of Generative AI & GraphRAG

Context Graphs: Agent Memory with Neo4j

Build an AI agent that records its reasoning, then query the trace to understand what it did and why

2 hours20 lessons across 4 modules
About this course

In this 2-hour course, you will learn

In this course, you will learn how to give AI agents persistent, explainable memory backed by Neo4j using the neo4j-agent-memory library.

You will learn why most AI agent deployments fail to deliver enterprise value — and how context graphs solve the three critical gaps: no memory, no audit trail, and no shared learning. You will explore the three-layer memory model (short-term, long-term, and reasoning), the POLE+O entity classification system, and the full graph schema that connects them.

By the end of the course, you will have built a Pydantic AI agent that records its complete reasoning trace into Neo4j, and written Cypher queries to traverse that trace and explain exactly what the agent did and why.

  • Context Graphs

  • Agent Memory

  • neo4j-agent-memory

  • Reasoning Traces

  • POLE+O