Master observability for AI agents that fail silently. In this 4-hour course, learn to detect invisible cognitive drift, implement policy-bound telemetry, build replayable decision trails, and generate audit-ready evidence packs. Move beyond dashboards to turn observability into governance for autonomous systems. Fully aligned with AEBOP T1.3.
AEI members get 20% off with code MEM_20.
Traditional observability was built for deterministic software, monitoring what happened through metrics, logs, and traces. Agentic systems introduce a new failure mode: invisible drift, where reasoning degrades without operational signals. Dashboard stays green, uptime remains perfect, but trust has already slipped away.
This module introduces the fundamental shift from monitoring actions to understanding decisions. You'll learn why security defines who may act, but observability proves what actually happened, and why both are required for autonomous systems to earn trust. Through real-world case studies from healthcare compliance failures and financial risk advisory systems, you'll identify the four core dimensions of agentic observability and map your own system's blind spots.
Observability isn't a dashboard or log aggregator; it's an architectural discipline. This module teaches you to build the Observability Stack: a four-layer architecture that turns cognition in motion into evidence in motion. From instrumentation at the source to response loops that drive correction, you'll implement the complete 5-phase field framework proven in enterprise deployments.
You'll work with production-ready code templates for event schemas, emitter SDKs, privacy masking, and secure collection pipelines. Through hands-on labs, you'll instrument reasoning loops, implement policy-bound telemetry, and build replay capabilities that make decisions reproducible under identical conditions. The module culminates in implementing a complete trace → drift → trust loop for your own agentic components.
Observability maturity grows through evidence, not ambition. This module introduces the Agentic Observability Maturity Ladder, a proven progression from blind runs to federated sight. You will learn to assess your current tier honestly and create a strategic roadmap for advancing your observability capabilities.
Next, you will master six design patterns for living observability, including the Trace Loop, Drift Loop, and Trust Loop. These patterns enable you to build adaptive, self-improving systems that transform static monitoring into cognitive understanding and governance at scale.
Operational Excellence & Governance translates observability theory into measurable reality. You will learn to implement seven core trust metrics that indicate cognitive health, not just system performance, and integrate these metrics into governance workflows for actionable insights.
Next, you will master field operations through proven practices from enterprise deployments, generating compliance-ready evidence packs and implementing operational playbooks that transform measurements into provable trust and continuous improvement at scale.