Operations | Monitoring | ITSM | DevOps | Cloud

AI agents are everywhere in the headlines—and yet no one seems to agree on what they actually are. Ask five companies what it means, and you’ll get five different answers: So yeah—no wonder people are confused. At the highest level, everyone agrees on this: AI agents are systems designed to act on behalf of a user. But that’s where the agreement ends. The big differences come down to how independent they are, how intelligent they really seem, and what kind of work they can do.

AI systems, from machine learning models to Large Language Models (LLMs) and autonomous AI agents, introduce unique observability challenges. Their non-deterministic nature, complex dependencies, and specialized performance characteristics require thoughtful instrumentation approaches. OpenTelemetry has emerged as the leading standard for implementing observability across these systems.

Agentic AI - the term has stirred much interest since being mentioned for the first time. And why not? The business world is still basking in the comfort, ease, and speed GenAI has brought since its democratization. Agentic AI promises to propel this leap in growth further. It promises more time freed up for strategic work, for finding new avenues of development, and a complete freedom from mundane work.

Not long ago, AI was largely experimental, but today it’s a strategic imperative. Enterprise AI adoption has surged to record levels, with over three-quarters of organizations now using AI in at least one function . In Deloitte’s latest global study, almost all organizations reported measurable ROI from AI, and 74% said their most advanced AI initiatives meet or exceed ROI expectations .

Seems like you can’t throw a rock without hitting an announcement about a Model Context Protocol server release from your favorite application or developer tool. While I could just write a couple hundred words about the Honeycomb MCP server, I’d rather walk you through the experience of building it, some of the challenges and successes we’ve seen while building and using it, and talk through what’s next. It should be pretty exciting, so strap in!

Traditional monitoring approaches have served IT operations for decades, providing basic visibility into system health through predefined metrics and thresholds. However, these conventional methods face significant limitations when confronted with modern, complex environments: Static Thresholds and Rules Traditional monitoring relies heavily on manually defined thresholds and rules.

If 2023 was the year AI entered the enterprise conversation and 2024 was the year of AI overhype, 2025 is the year it takes action. “Agentic AI” has quickly become the banner term for next-gen systems that aren’t limited to generating responses—they operate, decide, and resolve. The shift from passive chatbots to autonomous agents is underway, and for IT operations teams, the implications are massive.