Building Production Agent Memory with Neo4j: The Constitutional Graph Pattern

Building Production Agent Memory with Neo4j: The Constitutional Graph Pattern Most agent memory tutorials use vector databases. This is a guide for building with Neo4j instead — and why it matters for production autonomous agents. Why Graph > Vector for Agent Memory Vectors are great for "find me something similar to X." But agent memory has different requirements: What agents actually ask: "Has this action already been taken?" → Exact match, not similarity "What led to this decision?" → Graph traversal "Is this agent authorized for this?" → Authority lookup "What is the temporal context here?" → Time-aware traversal These are all native graph operations. They're awkward in vector space. The 6-Layer Constitutional Ontology After building this in production (ODEI, Jan 2026), here's the schema that works: // Core layers CREATE CONSTRAINT ON ( n: Foundation ) ASSERT n.id IS UNIQUE ; CREATE CONSTRAINT ON ( n: Vision ) ASSERT n.id IS UNIQUE ; CREATE CONSTRAINT ON ( n: Strategy ) ASSERT n.id