Agent Foundations and Prompt Engineering

Agent Foundations and Prompt Engineering is designed for learners eager to master the emerging field of AI agents and advanced prompt engineering. You'll learn how to design, build, and deploy intelligent AI agents using large language models (LLMs), craft high-quality prompts for various tasks, and automate complex workflows through programmatic execution and chaining. To begin with, you'll explore the fundamentals of AI agents, including their structure, behaviors, and real-world applications. You'll understand how LLMs enable agent intelligence and compare different agent architectures from reactive systems to sophisticated tool-using agents. The next module focuses on prompt engineering, where you'll learn to craft effective prompts using proven patterns like few-shot learning, chain-of-thought reasoning, and role prompting. You'll master the art of structuring prompts for optimal model performance and develop systematic evaluation strategies. In the third module, you'll advance to programmatic prompt execution and chaining. You'll build multi-step workflows, integrate Python code with LLM APIs, handle errors gracefully, and create production-ready prompt systems with proper debugging and monitoring. The final module teaches you to automate research and summarization tasks. You'll build end-to-end pipelines for collecting, processing, and summarizing information, implement both extractive and abstractive summarization methods, and evaluate outputs using comprehensive quality metrics. By the end of this course, you will confidently: • Design and implement AI agents for real-world automation and decision-making tasks • Craft effective prompts using advanced patterns and systematic evaluation methods • Build chained prompt workflows with robust error handling and programmatic control • Develop automated research and summarization systems with quality assessment frameworks Disclaimer: This is an independent educational resource created by Board Infinity for in