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:

Neo4j vector index documentation
Neo4j MCP server information
From Gimmick to Game Changer – Vibe Coding Myths Debunked (article by Michael Hunger)
RAG Was Fine, Until It Wasn’t (YouTube livestream)

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