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PAP. Etat : New. New Book. Shipped from UK. Established seller since 2000.

Taschenbuch. Etat : Neu. Neuware.

Etat : New. Print on Demand.

Etat : New. Print on Demand.

Paperback. Etat : new. Paperback. AI tools produce the output that matches your instructions - no better, no worse. This is the step-by-step guide to writing instructions that maximize output quality across text, code, and image generation, using the techniques professionals use in production environments.The gap between an average AI output and an exceptional one is not determined by the model. It is determined by the prompt. Precise, well-structured prompts produce precise, high-quality outputs. Vague, unstructured prompts produce generic, off-target results that require extensive revision or get deleted entirely. Prompt engineering is the discipline of closing that gap - and this book teaches it completely, from foundational principles through advanced techniques, for every major AI output type.The Prompt Engineer's Toolkit is built around a single transferable methodology that works across ChatGPT, Claude, Gemini, Grok, Midjourney, DALL-E, Stable Diffusion, Copilot, and every tool that follows them. Rather than teaching platform-specific tricks that break with the next model update, the book teaches the underlying principles of effective AI instruction that remain consistent regardless of which tool you are using or what you are asking it to produce.The book opens with the foundational mechanics of how language models interpret instructions - why specificity outperforms length, why context determines output quality, and what the three most common prompt failure modes are and how to diagnose and fix them. From this foundation, every major use case receives dedicated, worked treatment.Text prompt engineering covers professional writing, summarization, research synthesis, creative content, business communication, data analysis, and long-form document generation, with before-and-after prompt comparisons and industry best practice frameworks for each category. Code prompt engineering covers generation, debugging, refactoring, documentation, unit test creation, and code review across multiple programming languages, with iterative refinement techniques that take a rough specification through to production-quality output. Art and image prompt engineering covers positive and negative prompt design, style and composition control, model-specific syntax for Midjourney, DALL-E, and Stable Diffusion, and the iterative workflow that takes a creative concept from vague to visually precise.Advanced techniques include Chain-of-Thought prompting for complex reasoning, few-shot and zero-shot design, role-based prompting, prompt chaining for multi-step workflows, Tree-of-Thoughts for structured problem-solving, and self-refinement loops. The final section covers building a personal prompt toolkit - creating and maintaining a reusable prompt library, establishing quality benchmarks for recurring tasks, and developing the testing discipline that produces consistent results rather than inconsistent ones.No prior technical background is assumed. Every technique is accessible from the first chapter and applicable from the first session. This book is written for writers, marketers, developers, designers, business professionals, and students who use AI tools and want consistently better results from them.Haruto Minase - Author This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…