Ping, Probe, Prompt: Teaching AI to Troubleshoot Networks Like a Pro
When a network fails, it doesn’t whisper its problems—it screams in silence. Packet drops, congestion, and flapping links rarely announce themselves clearly. Engineers must piece together clues scattered across logs, dashboards, and telemetry. It’s a detective game where the evidence hides behind obscure port counters and real-time topological chaos. Now imagine handing this job to a Large Language Model. That’s the bold challenge taken up by researchers in “Towards a Playground to Democratize Experimentation and Benchmarking of AI Agents for Network Troubleshooting”. They don’t just propose letting LLMs debug networks—they build an entire sandbox where AI agents can learn, act, and be judged on their troubleshooting skills. It’s not theory. It’s a working proof-of-concept. ...