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Prompt Engineering is a book category focused on the art and science of crafting effective inputs for AI systems—especially large language and multimodal models—to produce accurate, useful, and safe outputs. Titles in this genre explain how these models interpret instructions and cover practical techniques such as clear task framing, role and constraint setting, few- and zero-shot examples, decomposition and iterative refinement, retrieval-augmented prompting, and evaluation. Many books also address advanced workflows (tool use, agents), prompt security and defenses against jailbreaks, as well as ethics, bias, and safety. Blending theory with templates, patterns, and case studies across domains like coding, writing, analysis, education, and marketing, the category serves developers, researchers, educators, and creators seeking to design reliable human–AI interactions without deep ML expertise.

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