Multi-Agent Prompting: Advanced Prompt Engineering for AI Agents and Workflows

This book offers a comprehensive guide to building reliable, intelligent multi-agent architectures that go beyond single-agent setups.
In these pages, you'll discover advanced techniques in agent orchestration, learn how to coordinate specialized agents for distinct roles, and master strategies for chaining prompts across AI agents to solve complex tasks. If you've worked with LangChain, Hugging Face pipelines, or tried building Retrieval-Augmented Generation systems, this book will help you refine your practices and avoid costly design mistakes.

Expect practical workflows and real-world case studies: from automating customer support with collaborative agents to constructing agent teams for data analysis and creative production. Detailed code examples and pseudocode walk you through how prompts are structured, how agents communicate, and how to maintain context and consistency across lengthy conversations or chained tasks.
You'll also gain insight into how to debug and evaluate collaborative prompts-identifying hallucinations, avoiding prompt looping, and establishing reliable evaluation metrics. Each insight is paired with actionable best practices so you can iterate rapidly and build systems that perform in production.
For developers, engineers, and AI practitioners seeking to move beyond introductory prompt engineering, this book positions you at the frontier of multi-agent AI design. Whether you're designing intelligent assistants, supervisory workflows, or autonomous agent ecosystems, Multi-Agent Prompting will equip you with the frameworks, patterns, and principles you need.