HAWAT: An AI Assistant for Network Troubleshooting#

Karl Newell & Matt Mullins — Internet2

• Why: A working agentic AI assistant interfacing directly with network hardware at a national research network — one of the few demos in the program where an LLM-driven agent reasons through real protocol failure modes.
• What: HAWAT (Heuristic Analysis With Adaptive Troubleshooting): an agentic chatbot that interprets network conditions and executes commands on infrastructure. Demonstrated on both a lab topology and Internet2's 88-device production-scale national network (aggregation routers, core routers, global exchange points), including live latency tests (NY–LA, ~69ms) and BGP route-origin analysis per neighbor/VRF.
• How: LLM + RAG (over network documentation) + ReAct agentic framework. The demos shown are the convincing kind: diagnosing an OSPF adjacency failure to a hello-interval mismatch (10s vs 20s) with the specific log lines, explaining adjacency flapping from "inactivity timer expired" / "nbr did not list our router ID", and drawing ASCII topology with data-plane vs management-plane distinction. Next steps are MCP and agent-to-agent protocols.
• Where applicable: Internet2 research-network context, and the demos include pre-recorded sessions — evaluate the failure-diagnosis patterns rather than production readiness. The approach (LLM as reasoning front-end over a bounded command set, with RAG grounding in topology and docs) is replicable in any environment; the risk profile of letting it execute commands is yours to scope.