As cloud ecosystems scale, traditional DevOps automation struggles to keep pace with the dynamic, unpredictable nature of operations. This session reimagines AIOps through the lens of reflexive agent intelligence—AI systems that sense, analyze, and act continuously to maintain operational stability. Built on open-source observability tools like Prometheus, Grafana, and InfluxDB, combined with the reasoning power of OpenAI models, this framework models the cloud as an environment of sensors (telemetry, alerts, events) and actuators (deployment triggers, scaling controls, remediation actions). A simple reflex agent monitors metrics and executes predefined actions in real time, while a model-based reflex agent learns patterns, predicts anomalies, and adapts its responses over time. Together, they form an autonomous feedback loop that eliminates manual intervention, reduces mean time to recovery (MTTR), and keeps distributed environments self-healing and resilient. The talk explores design patterns, open-source integration, and the evolutionary path from automation to autonomous operations.