At HumanX, Ryan is joined by Philip Rathle, CTO at Neo4j to discuss what knowledge context means for AI agents, how limitations like stale training data make the model-only approach to agents a bad fit for enterprise environments, and how Graph RAG raises the bar for accuracy and reduces context rot by combining vectors with a knowledge graph so agents are more targeted and connected.

Episode notes:

Neo4j is a native graph database management system designed to handle complex, highly-connected data by focusing on relationships rather than tables. You can try it out for free on Aura and learn more at their Graph Academy. 

Connect with Philip on LinkedIn. 

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