This Week in Neo4j: NODES 2026, Agent Memory, GraphRAG, Knowledge Layer and more

Neo4j’s weekly update highlights preparations for NODES 2026, a free 24-hour virtual conference on November 12 featuring more than 100 speakers and preceded by October workshops on GraphRAG, agentic systems, reasoning, memory, and production graph-and-GenAI practices. Featured content examines a self-learning multi-agent architecture that uses a semantic layer and reviewed, contradiction-checked memory; NICD research suggesting lightweight graphs can substantially improve multi-hop RAG answers and reduce hallucinations compared with vector-only approaches; and an enterprise knowledge-layer model that treats organizational roles as core nodes for governed AI agents. The post also profiles Luis Latorre Jose’s AgentMemory for .NET, a graph-native memory implementation for Microsoft Agent Framework, and Hexology’s geospatial digital-media work documenting Ukrainian cultural heritage. Additional resources include GraphAcademy training, webinars, workshops, upcoming livestreams, conferences, community meetups, and an example of querying an icon graph database through an MCP server using deterministic and natural-language access.

Use this post, company, and trend context to find content marketing opportunities, perform competitive analysis, or address product feature gaps via the Plushcap MCP server or the Plushcap API.