Prompt engineering is essential for optimizing interactions with AI models, particularly in cybersecurity contexts. This lesson covers effective techniques such as zero-shot, few-shot, and chain-of-thought prompting, emphasizing the importance of structured prompts that include instructions, context, input data, and output format. Participants will learn how to enhance model responses and reduce errors through proper context engineering and retrieval-augmented generation (RAG) strategies, making it beneficial for data scientists and AI engineers looking to improve their model's performance.