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AI Summary: A highly practical guide that treats prompt engineering as a structured discipline, teaching users how to extract reliable, high-quality outputs from LLMs for business workflows.
AI Summary: A highly practical guide that treats prompt engineering as a structured discipline, teaching users how to extract reliable, high-quality outputs from LLMs for business workflows.
While many books focus strictly on backend infrastructure, this guide targets the crucial skill of optimizing the actual inputs that drive foundation models. Phoenix and Taylor explore the science of prompt engineering, treating it as a deterministic programming language rather than a creative writing exercise. The book covers advanced techniques like few-shot prompting, chain-of-thought reasoning, and prompt chaining via APIs. It bridges the gap between technical AI engineering and high-impact business applications like marketing and SEO automation.
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