Building AI Agents: From Foundational Concepts to Practical Workflows

AI is shifting from passive chat interfaces to active, autonomous agents that can plan, use tools, and solve complex problems. Understanding how to build these agents is becoming an essential skill for modern developers and tech professionals. In this text-only course, you will transition from understanding the core theory of intelligent agents to designing your own functional agentic workflows. You will master the fundamentals of agent architectures, decision-making loops, and external tool integration. What you'll learn: - Understand core AI agent architectures, including perception, planning, memory, and action loops - Apply prompt engineering techniques and the ReAct framework to guide agent decision-making - Configure agents to interact with external tools and APIs using structured function calling - Implement short-term and long-term memory systems using vector databases for context persistence - Design multi-agent collaboration workflows where specialized agents work together to solve complex tasks - Address safety guardrails, ethical considerations, and cost-management strategies in agent deployment The course begins with foundational definitions and key terminology of agentic systems before guiding you through step-by-step conceptual designs and code-based implementations. You will explore practical, text-based examples of single-agent and multi-agent systems designed for real-world tasks. This course is designed for software developers, product managers, and tech enthusiasts who want a clear, beginner-friendly introduction to AI agents. No prior experience with agent frameworks is required. Start reading today to unlock the potential of autonomous AI workflows.