Evaluating, Governing, and Scaling AI Agents

As businesses increasingly deploy autonomous AI agents to automate complex workflows, ensuring their safety, reliability, and alignment with business goals becomes a critical challenge. This text-based course equips you with the foundational frameworks needed to measure agent performance, establish robust governance guidelines, and scale AI operations safely. What you'll learn: Understand foundational AI agent architectures, terminology, and core decision-making loops; Evaluate agent performance using modern testing frameworks, prompt validation, and benchmark datasets; Implement governance guardrails to mitigate risks around data privacy, bias, and unexpected agent behavior; Scale agent deployments using modern orchestration patterns and retrieval-augmented generation concepts; Monitor agent actions in real-time to ensure alignment with organizational policies and security standards. Starting with basic terminology and core safety concepts, the course guides you step-by-step through evaluation methodologies, governance frameworks, and practical scaling strategies. Designed for beginners, this course requires no previous programming experience, making it perfect for managers, analysts, and aspiring AI operators. Start reading today to confidently manage and scale your organization's AI initiatives.