In this episode of Breaktime Tech Talks, dive into the real-world challenges and discoveries from my recent work with Langchain4j, Quarkus, and Neo4j. If you’re a developer navigating the evolving landscape of AI, vector search, and graph databases, this episode is packed with practical insights and lessons learned. Highlights: Struggles with configuring hybrid search (vector + graph retrieval) in Langchain4j and Quarkus Pain of setting up Neo4j vector stores, especially for read-only databases Data importer docs difference (standalone vs Aura) Why current frameworks make it hard to customize retrieval workflows Discovery of Neo4j’s MCP Cypher server for vector search as a tool Blog post on implementing GraphRAG retrievers as an MCP server for reusable, agentic applications Updates on the GraphRAG Fundamentals online course and the upcoming NODES 2025 conference My new new Java book project Tune in for practical advice, honest roadblocks, and new ideas for building smarter, more flexible developer tools!