AI Prompt Engineering: Foundations of Communication with LLMs – Building Generative AI and Agentic AI Prompt Systems Across Development, Testing, and Deployment,

“Writing a really great prompt for a chatbot persona is an amazingly high-leverage skill and an early example of programming in a little bit of natural language.” — Sam Altman, OpenAI

As Large Language Models have become central to software, research, and business operations, the ability to communicate with them precisely has quickly become an essential skill across many sectors. Prompt engineering is now a question of absolute competence. Author Nelson Ming provides a comprehensive resource that teaches this discipline from the ground up. Written for forward-looking and active practitioners, this book provides the conceptual foundations and practical systems needed to build reliable and scalable prompt-driven solutions.

Across 45 modules organized into eight chapters, the book begins with first principles: how prompts work, how models interpret them, and how to design stable interactions. From there, it develops into advanced architectures, orchestration patterns, and deployment strategies used in real systems. Readers learn how to construct modular prompt systems, integrate prompting with external tools and APIs, build retrieval-augmented flows, and establish evaluation and governance layers for safety and compliance.

A section of the book is dedicated to Agentic Prompting. Here, prompts drive perception, reasoning, action, and self-reflection loops inside automated AI agents. The book explains how these patterns work, when they fail, and how to design them responsibly in production environments.

Throughout the book, selected modules are supported by additional online resources, including tools and detailed examples. Together, the book and its supporting resources provide both a strong theoretical framework and a practical system for applying prompt engineering in real-world contexts.

Table of Contents:Chapter I – Core Concepts and Building BlocksChapter II – Building Structured Prompt SystemsChapter III – Prompting Tools and EcosystemsChapter IV – Prompting AI AgentsChapter V – Safety, Governance, and RiskChapter VI – Deploying and Scaling Prompt SystemsChapter VII – Real-World Use CasesChapter VIII – Emerging Trends and TrajectoriesAdditional Content Available Online Whether you are learning the foundations of prompt engineering or seeking to refine your professional practice, this book provides a clear and deeply informed foundation for communicating with LLMs at scale. It equips readers perfectly to navigate the continuously evolving landscape of AI-driven systems in the years ahead.

Scroll up and click Buy Now to start reading.