AI Agent Development with LLMs and Prompt Engineering

Autonomous AI agents are reshaping how we interact with technology, moving beyond simple chatbots to systems that can plan, reason, and execute tasks. Understanding how to build these agents is one of the most valuable skills in modern software development. This text-based course guides you through the core concepts of Large Language Models (LLMs) and prompt engineering, taking you from foundational definitions to designing your first functional AI agent. You will learn how to structure prompts, manage agent memory, and integrate external data sources to build intelligent, goal-oriented systems. What you'll learn: Understand the core architecture and capabilities of modern Large Language Models; Master advanced prompt engineering techniques to guide agent behavior and output formatting; Implement planning and reasoning frameworks such as Chain-of-Thought and ReAct; Configure agent memory systems to maintain context across complex, multi-step tasks; Apply Retrieval-Augmented Generation (RAG) patterns to connect agents with external data; Design structured outputs to reliably integrate AI agents with external APIs. We begin with essential AI terminology and the mechanics of LLMs before moving into hands-on prompt design and agent architecture. Through clear written explanations and practical code walkthroughs, you will develop a deep conceptual and practical understanding of autonomous agent design. This course is designed for software developers, product managers, and tech enthusiasts who want to enter the world of AI development. No prior experience with artificial intelligence or machine learning is required, though a basic understanding of programming concepts is helpful. Start reading today to build your first autonomous AI agent from scratch.