The Observability & Automation Posts

In an era where observability and AI Agents power operations, data literacy is no longer optional — it’s a shared responsibility. From Specialists to System Thinkers Observability has transformed operations from isolated troubleshooting to system-wide understanding. But without a team that can interpret data, insights remain unused. Building data literacy means teaching everyone — not just SREs or data scientists — how to read trends, identify anomalies, and question what the

Trust isn’t automatic — it’s engineered.Observability systems must be designed to explain, justify, and earn confidence, one decision at a time. From Transparency to Trust AI Agents can execute at speed and scale, but speed without transparency is risk. Engineers must be able to understand why  an AI Agent took a particular action, not just that it did. Observability bridges that gap — surfacing reasoning paths, input signals, and decision outcomes. When users can trace logic

Even the most advanced AI Agents need human context.Observability provides data; humans provide meaning. Together, they form the foundation of intelligent, ethical, and adaptive operations. From Automation to Augmentation AI Agents excel at identifying anomalies, predicting outcomes, and even executing corrective actions. Yet, they operate within boundaries defined by data — not by experience, culture, or intuition. Humans bring context: understanding why a certain service ma