The NetDevOps Journey: Manual Firefighting to Agentic Autonomy#

Greg Freeman — Lumen (VP Network & Customer Transformation) — Closing Keynote

• Why: Scale and candor from one of the world's largest networks — ~340,000 fiber route miles, 350+ Tbps backbone, AS1 — on both what large-scale automation achieved and a sober reading of AI's failure statistics.
• What: Lumen's operational transformation: 80% "hands out of the network" via machine-to-machine communication, 350+ workflows developed, running at a pace of ~10 workflows per minute 24×7, built on Itential orchestration with an integration layer spanning ticketing, alarming (Splunk, RFM), CMDB, and dozens of system adapters. The second half pivots to AI: an MCP architecture with an MCP service layer (Ollama in DDC, Databricks/Claude) exposing internal tools to agents, plus a "Supervisor Agent" above them — and an AI use case for pinpointing fiber-cut GPS locations.
• How: The automation strategy is standards-plus-process ("no shortcuts": PDDs, SDDs, training, "upscaling employees" rather than replacing them). The AI section is notable for citing both Wharton's optimistic outlook and MIT's cautionary one (of $30–40B invested in custom AI projects, ~95% see zero return; organizational readiness, not technology, is the limiter), plus clear "what AI is not" caveats: non-deterministic outputs need human oversight, it is not a universal replacement, and it requires continual upkeep.
• Where applicable: Lumen-specific scale and Itential-based stack — the workflow counts and mediation architecture are their topology. Transferable: the tiered support-culture shift, the supervisor-agent-over-MCP-services pattern, and the discipline of treating AI adoption as an organizational-readiness problem. Treat the ROI claims as directional; the cited MIT/Wharton tension is the honest part.