Telemetry Now

Host Phil Gervasi talks with Chris Grundemann, cofounder of the Network Automation Forum and AutoCon, about why network automation still isn’t fully adopted after more than a decade of hype. They dig into the real blockers behind the tech: skills gaps, engineer identity and culture, organizational structure, and the broader “sociotechnical” system around NetOps. Chris also shares how the AutoCon community has evolved over five events, the growing role of observability and AI in automation, and what’s next for NAF and AutoCon in Europe.

Kentik’s Mav Turner joins host Phil Gervasi to go beyond chatbot hype and dig into real AI reasoning for network operations. They discuss how Kentik AI Advisor uses network intelligence, hybrid RAG, and tool-calling to troubleshoot issues, optimize cost, and democratize access to network expertise. Along the way, they cover architecture, data governance, model evaluation, and why AI has to be built into an observability platform itself, not bolted on.

Host Philip Gervasi talks with Kentik pre-sales engineer Sean McGinley about what it really means to work in pre-sales. They unpack the various titles associated with those roles (e.g., solutions engineer, solutions architect) and discuss how pre-sales bridges the gap between technology and business. Learn how these roles balance hands-on engineering with customer relationships. Along the way, they share personal stories, lessons learned from the field, and why pre-sales can be one of the most rewarding career paths in tech.

Host Philip Gervasi and Kentik Field CTO Justin Ryburn preview the upcoming AutoCon 4 conference, one of the premier events for the networking industry. They discuss the growth of the Network Automation Forum, the evolution of the AutoCon community, and the event’s focus on real-world network automation, observability, and AIOps. Justin previews Kentik’s hands-on AutoCon 4 session, “Building Smarter Observability with Network Intelligence.”

Kentik CPO Mav Turner joins host Philip Gervasi to cut through the AI hype in NetOps. They discuss where ML and LLMs actually help—anomaly detection, root cause analysis, and agent-driven runbooks—and where deterministic methods still win. Join us for real talk on data pipelines, telemetry quality, model evaluation, human-in-the-loop guardrails, and the build-vs-buy trade-offs that transform network noise into informed decisions.