// 01 / Speaker
Stephen Chin is VP of Developer Relations at Neo4j, where he works on knowledge graphs, GraphRAG and agent memory for enterprise AI. With Michael Hunger and Jesús Barrasa, he is coauthoring O’Reilly’s upcoming GraphRAG: The Definitive Guide, which covers how vector search and graph traversal combine to give LLMs connected, multi-hop context that can be audited. He is program chair and a board member of the LF AI & Data Foundation, and an ambassador for the Agentic AI Foundation (AAIF).
Before Neo4j, Stephen was VP of Developer Relations at JFrog. There he sat on the governing boards of the Continuous Delivery Foundation and the Cloud Native Computing Foundation, and focused on CI/CD and software supply chain security. Earlier, he led Java developer marketing and advocacy at Oracle and built open-source projects including JavaFX-Spring.
His recent talks cover agentic GraphRAG, context engineering and graph-based memory for AI assistants. He has run developer evangelism tours by motorcycle across Europe, Japan and Brazil, and he teaches AI, embedded and robot programming to kids with his daughters.
// 02 / About this session
Vector search finds text that looks similar. A graph captures how facts connect. Drawing on his upcoming O’Reilly book, Stephen shows where GraphRAG beats a vector index on its own, how hybrid graph and vector retrieval works in practice, and what it means for agent memory.
Want to build it yourself? Neo4j’s hands-on workshop with Nyah Macklin follows at 11:55 AM on Stage 3.
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