This episode provides an extensive overview of prompt engineering, explaining it as the crucial process of crafting instructions to guide AI models without altering their core programming. It details the components of effective prompts, such as clear task descriptions and examples, and discusses the concept of in-context learning, including zero-shot and few-shot approaches. The text also addresses the critical topic of defensive prompt engineering, outlining various prompt attack methods like injection and extraction, and presenting potential defenses at the model, prompt, and system levels to enhance application security. Finally, it emphasizes the importance of iterative prompt development and the use of prompt engineering tools while advising caution regarding their complexity and potential hidden costs.