Graph-centric agentic intelligence
This article discusses how graph-centric agentic AI can be applied to network operations, enabling autonomous reasoning over complex system topologies for root cause analysis and failure isolation. The piece traces the evolution of graph representations in networking—from basic topology modeling to knowledge graphs, dependency graphs, and graph neural networks—and demonstrates how agentic AI agents can reason over these structures to identify network failures more efficiently than traditional approaches.















