Description

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!