Explore the latest challenge with Neo4j vector indexes, demystify Model Context Protocol (MCP), and hear insights on vibe coding and Retrieval-Augmented Generation (RAG).
What's Inside:
- Confusion around Neo4j vector indexes - models and dimensions
- Why knowing the embedding model matters for vector similarity search
- The limitations of current Neo4j vector index metadata
- What is Model Context Protocol (MCP) and why it matters for generative AI
- Real-world analogies for understanding MCP (microservices, snack choices, Docker containers)
- The power of MCP servers for secure, modular data access
- Article highlight: “From Gimmick to Game Changer – Vibe Coding Myths Debunked”
- How AI coding tools and generative AI are lowering barriers for developers and business users
- Risk mitigation vs. risk avoidance in adopting new technologies
- YouTube livestream: “RAG Was Fine, Until It Wasn’t” – lessons from Neo4j Graph Academy’s evolution
- The importance of focusing on goals over syntax in development
Links & Resources:
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