Multi-agent AI for Juniper switch ops architecture that took provisioning from 1,016 hours to 60 hours Posting this for the network engineers in here who are thinking about where AI actually fits in network ops vs. where it's hype. We just wrapped a production deployment for a telecom operator managing 254 Juniper switches. The problem was classic: too many devices, too many edge cases for scripting, too much engineer time on low-level triage. **What we built and why it works:** The key insight is that network fault diagnosis is fundamentally a reasoning problem, not a pattern-matching problem. Scripts fail because they can't handle the combinatorial explosion of device states, error combinations, and environmental context. An agent can reason across that context the way a Tier 2 engineer does.…