Introduction to AI Agents and ReAct Prompting

AI agents are transforming how we interact with technology by moving beyond simple static prompts to dynamic, goal-driven reasoning. Understanding how to guide these agents through structured planning and execution is the key to unlocking their true potential. This text-based course guides you through the core concepts of agentic design, focusing on the powerful ReAct (Reason and Act) framework. You will transition from writing basic prompts to structuring sophisticated, multi-step workflows where AI agents can reason about a task, select the right tools, and execute actions dynamically. What you'll learn: - Understand the foundational concepts of AI agents, autonomous planning, and execution loops. - Master ReAct prompting techniques to help models reason systematically before taking action. - Configure dynamic tool calling to connect your AI agents with external APIs and databases. - Apply modern prompt engineering patterns to manage agent memory and state across multi-turn conversations. - Build robust evaluation strategies to test and refine your agent's decision-making processes. The course begins with essential terminology and the theory behind agentic workflows before moving into practical, step-by-step written walkthroughs and code examples. You will read detailed explanations of prompt structures and analyze real-world scenarios of agents solving complex problems. This course is designed for beginners, developers, and prompt engineers looking to build interactive AI systems. No advanced programming background or prior experience with AI agents is required. Start reading today to build your first autonomous reasoning agent.