Agentic Strategy: Discover, Design, and Prototype AI Agents

As organizations transition from simple chatbots to autonomous systems, understanding how to design effective agentic workflows is becoming a critical skill. This text-based course guides you through the strategic process of discovering, designing, and prototyping AI agents that can plan, use tools, and collaborate. You will transition from a basic understanding of artificial intelligence to strategically architecting multi-agent systems. By studying real-world scenarios and conceptual frameworks, you will gain the confidence to design agentic solutions that align with business goals. What you will learn: Understand the foundational principles of agentic AI, including planning, memory, and tool usage; Discover high-impact use cases for autonomous agents within modern business operations; Design robust agent architectures using prompt engineering patterns and reasoning frameworks; Prototype agentic workflows by mapping out decision trees, feedback loops, and human-in-the-loop checkpoints; Integrate retrieval-augmented generation (RAG) and external APIs to ground your agents in real-world data; Evaluate agent performance and safety using modern testing and observability concepts. The course begins with essential definitions and foundational agentic concepts before walking you through step-by-step design methodologies and prototyping exercises. Through clear written explanations and structured analysis, you will learn to map out complex autonomous behaviors. This course is designed for business analysts, product managers, and aspiring AI strategists who want to understand agentic design without needing a deep programming background. No prior coding experience is required. Start reading today to master the strategic blueprint for the next generation of AI automation.