HN837: Agentic AI to Reduce MTTR

Heavy Networking · Aug 7, 2026 · 1:05:04

0:001:05:04

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Ethan Banks sits down with Eduard Dulharu live at AutoCon 5 to explore how agentic AI can be used to reduce Mean Time to Recovery (MTTR) for complex network environments. Eduard breaks down how these AI agents leverage deterministic workflows and custom fine-tuned models to analyze telemetry and propose solutions. Through the use of agentic... Read more »

← HN836: Optimize AI Traffic on the WAN with Ciena’s… HN838: Meet Mr. Packets – Building Your Own Agentic AI… →

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