Imagine arriving at work on a Monday morning discovering that several critical data pipelines failed overnight. Business reports are incomplete, dashboards show outdated information, and teams are already asking when the data will be available. Traditionally, engineers would start investigating logs, checking pipeline dependencies, reviewing recent deployments, and identifying what went wrong. Depending on the complexity of the issue, this could take several hours. Now imagine an AI agent that...