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In Module 2 — Lecture 1: From Messy Problem to Agent System, we break down one of the most important skills in AI engineering — transforming real-world chaos into structured agent workflows. Using a practical E-commerce Customer Support example, this lecture walks you through how expert AI designers think when building agent systems. You’ll learn why agent design always begins with messy, ambiguous problems and how to systematically carve out the right automation boundaries instead of trying to automate everything at once. We explore: Why messy problems are the best starting point for agent design How to identify the correct slice of workflow to automate Deciding what humans should handle vs what agents should execute Translating business processes into agent actions The tool-calling workflow pattern used in real production systems Key design philosophy principles that separate amateur agents from production-ready systems This lecture is essential for anyone serious about building real-world AI agents, not just demos or chatbots. If you want to design systems that think, decide, and act, this lesson lays the foundation. 📌 Who this is for AI Engineers • Builders • Product Designers • Automation Architects • Startup Founders • Anyone building AI agents or copilots