Evaluating AI Agents for User Experience

As businesses rapidly deploy AI agents, the true measure of success shifts from technical metrics to actual user satisfaction. Understanding how to evaluate the interaction between human users and autonomous agents is a critical skill for modern product teams. This course teaches you how to systematically analyze AI agent behavior to ensure they deliver genuine value rather than user frustration. You will transition from viewing AI through a purely technical lens to analyzing the holistic user journey. By learning to separate backend system errors from poor interaction design, you will be able to pinpoint exactly where an AI agent fails to meet user expectations. What you'll learn: - Understand the core terminology and foundational architecture of modern AI agents - Distinguish between underlying technical failures and user experience flaws - Apply evaluation frameworks to measure the qualitative value of AI interactions - Analyze conversation flows and agent decision-making processes for friction points - Design feedback loops that continuously improve agent-user collaboration - Practice identifying alignment issues where the agent's actions diverge from user intent We begin with essential definitions and the core mechanics of AI agents, ensuring you build a strong conceptual foundation. From there, you will progress through practical methodologies to audit agent behaviors, analyze real-world interaction scenarios, and implement actionable improvement strategies. This course is designed for beginners, product managers, UX designers, and technology coordinators who want to evaluate AI implementations without needing to write code. No prior programming or machine learning experience is required. Start learning today to build intuitive and high-value AI-driven experiences.