AI Agent Evaluation: From Prototype to Production

Building an AI agent is only the first step; ensuring it behaves reliably in the real world is the ultimate challenge. Without a structured way to test, score, and monitor your agent's outputs, deploying to production becomes a risky guessing game. This course provides a clear, step-by-step methodology to design and run your own evaluation frameworks. In this text-based course, you will transition from manual, ad-hoc testing to automated, systematic evaluation. You will learn how to define success metrics, build custom scoring systems, and establish a repeatable testing pipeline that ensures your agent performs consistently as it scales. What you'll learn: - Understand the core concepts of AI evaluation and why traditional software testing is insufficient for agentic workflows. - Design and implement custom scorers to measure the accuracy, relevance, and safety of agent outputs. - Apply modern evaluation patterns, including LLM-as-a-judge and semantic similarity metrics. - Configure structured logging systems to store, track, and analyze inputs, agent traces, and final responses. - Build a regression testing workflow to safely update prompts and underlying models without breaking existing capabilities. - Transition your evaluation framework from a local development environment to a continuous production monitoring setup. We begin with foundational definitions and key testing terminology, then guide you through clean, written explanations and practical code snippets to build your evaluation harness from scratch. Every concept is reinforced through conceptual breakdowns and code-based examples that you can read and apply immediately. This course is designed for software developers, AI engineers, and tech-savvy product builders who want to move beyond basic prototypes. No prior experience with machine learning evaluation is required, though a basic familiarity with programming and APIs is recommended. Start establishing your evaluation framework today and deploy your AI agents with absolute confidence.