Operations | Monitoring | ITSM | DevOps | Cloud

AI for Network Leaders by Selector - Strategic Imperatives in an AI World by William Collins

Strategic Imperatives for Infrastructure Leaders in an AI-Enabled World William Collins, Director of Technical Evangelism at Itential, explores the strategic imperatives facing infrastructure leaders in today’s AI-enabled world. He unpacks the Gartner Hype Cycle, the true monetary costs of network downtime, and shows how Itential + Selector can close the loop on AIOps with autonomous agents and MCPs.

AI for Network Leaders by Selector - AI Agents and MCP by John Capobianco

AI Agents & Model Context Protocol John Capobianco, Head of Developer Relations at Selector, dives deep into AI Agents and the Model Context Protocol (MCP). In this session, John demonstrates Selector MCP in action — running as a client-server, connecting multimodal inputs, and even talking to Selector using microphone + TTS audio via Gemini CLI. He also showcases Sebastian Maniak’s Claude Desktop integration, where Selector MCP powers a chatGPT-like UI for network engineers. A practical look at how MCP is transforming AI into a true digital co-worker.

AI for Network Leaders by Selector - Building Your First RAG App by John Capobianco

Building Your First GenAI RAG Application John Capobianco, Head of Developer Relations at Selector, walks through a 6-step process for building your first GenAI RAG application. From foundational building blocks to the path toward full AI agents, RAG remains a powerful tool with huge ROI. Even in a world of autonomous agents and MCPs, RAG is still one of the best ways for network engineers and IT leaders to query dozens of sources and unlock real value.

95% of AI Pilots Fail - Here's How to Be the 5%

When MIT released research showing that 95% of enterprise AI pilots fail to deliver measurable business impact, it made headlines for a reason. After years of heavy investment in artificial intelligence, the vast majority of organizations still haven’t moved beyond pilots that promise much but deliver little. This doesn’t mean AI itself is broken. In most cases, the technology performs as intended.

AI That Knows Networking: Selector vs. Generic GPT Integrations

The hype around generative AI has led many IT teams to experiment with plugging generic GPT models into their workflows. On paper, this is the beginning of true AI networking, featuring conversational interfaces, instant summaries, and faster troubleshooting. However, as we discussed in the previous post, “Why Your IT Copilot Needs Context, Not Just Data,” copilots are only as effective as the intelligence behind them.

Why Your IT Copilot Needs Context, Not Just Data

In the rush to adopt AI in IT operations, many organizations focus on feeding copilots as much data as possible. But here’s the problem: data without context is just noise. An IT copilot that can’t distinguish what matters from what doesn’t won’t reduce alert fatigue or accelerate troubleshooting.

Real-World Use Cases for Natural Language Copilots

Natural language copilots are one of the most exciting developments in AI for network operations. They allow engineers and operators to query complex environments in plain language rather than memorizing obscure CLI commands or digging through multiple dashboards. But here’s the truth: a copilot is only as good as the AI behind it. Without a purpose-built network LLM, a copilot can’t deliver the accuracy, context, and speed that real-world IT operations demand.

Network Visualization: 4 Ways to Visualize Computer Networks

Network visualization is the process of visually representing networks of connected entities, like devices, data flows, or relationships, using nodes and links. This technique helps in understanding complex data, identifying patterns, and improving network management by providing a clear visual overview of the network’s structure and behavior.