AI Agent Configuration: Skills and Rules for Programmers

As AI moves from simple chat interfaces to autonomous agents, the ability to define exactly how these systems behave is becoming a critical skill for every developer. This course teaches you how to move beyond basic prompting by architecting the internal logic that governs how AI agents process information and execute tasks. You will learn to transform unpredictable outputs into reliable, production-ready systems by mastering the configuration of skills and behavioral constraints. By completing this course, you will be able to design robust agentic workflows that minimize errors and follow strict operational guidelines. You will understand how to bridge the gap between high-level intent and technical execution through structured rule-setting. What you'll learn: - Understand the core terminology and architecture of modern AI agents - Define specific skill sets that allow agents to interact with external data and tools - Configure execution rules to ensure safe, consistent, and predictable agent behavior - Apply prompt engineering patterns to reduce hallucinations and improve task accuracy - Implement basic retrieval-augmented generation (RAG) concepts within agent logic - Practice refining agent responses through structured written exercises and logic testing The course begins with foundational concepts of agentic behavior before moving into the technical details of skill definition and rule maintenance. You will explore how to maintain these systems over time to ensure they remain effective as requirements evolve. This course is designed for programmers and technical enthusiasts who are new to AI agent development and want a structured approach to building reliable systems. No prior experience with AI orchestration is required. Start building smarter and more reliable AI agents today.