Agentic AI Engineering with Claude Code and MCP

Stop Prompting. Start Engineering AI Systems That Actually Work.

If you're still relying on prompts to build with AI, you're already behind.


Prompt-based coding breaks the moment your projects grow, outputs become inconsistent, workflows collapse, and control disappears. That's why top developers are shifting to agentic AI engineering: building systems that think, act, and execute reliably.


This book shows you how to do exactly that.


2 What You'll Learn Inside


This is not another "AI tools" book.


This is a practical, system-level guide for developers who want to move beyond experimentation and start building production-ready AI systems using Claude Code and Model Context Protocol (MCP).


Inside, you'll learn how to:


• Design agentic workflows that are predictable, scalable, and controllable

• Build and orchestrate multi-agent systems that solve real development problems

• Use context engineering to eliminate randomness and improve output reliability

• Implement persistent memory systems for long-term AI reasoning

• Automate development with commands, hooks, and workflow pipelines

• Integrate AI into real tools using MCP for structured context sharing

• Debug, monitor, and control AI systems like a professional engineer

• Build a complete production-ready AI SaaS system from scratch


Built for Developers Who Want Real Results


This book is for:


• Developers tired of inconsistent AI outputs

• Engineers ready to build scalable AI workflows

• Builders who want to turn AI into a reliable system not a guessing tool


If you understand coding but feel stuck with AI tools, this book bridges that gap.


Why This Book Is Different


Most books stop at prompting.


This one shows you how to:

• Design systems
• Control behavior
• Scale workflows
• Build real applications