You've used Claude Code, Cursor, or Copilot and wondered: how does this thing actually work? How does it read my files, decide what to do next, edit code, run tests, and fix its own mistakes - all from a single prompt?
This book answers that question by having you build one yourself.
Starting from an empty directory, you create a working AI coding agent in C# and .NET that streams LLM responses in real time, calls tools to read and write your code, searches your codebase, runs shell commands, and remembers what it learned across sessions. A three-tier safety system asks permission before anything destructive happens. Multi-provider support means you can point it at Claude, GPT-4, Grok, or Gemini without changing a line of agent code.
The secret sauce? The agent loop - the think-act-observe cycle that turns a chatbot into something that can actually get work done. You'll build that loop in Chapter 4, and every chapter after that makes it smarter: tool calling, safety gates, project awareness, persistent memory, sub-agent orchestration.
Twelve chapters. One AI concept and one piece of working code per chapter. Roughly 4,000 lines of clean, idiomatic C# when you're done. No machine learning background required - if you're comfortable with async/await, interfaces, and LINQ, you have everything you need.
The architecture comes from real production patterns documented by the developer community through studying Claude Code's public APIs, official documentation, conference talks, and open-source reimplementations. We took those patterns - the same ones powering a tool used by hundreds of thousands of developers - and rebuilt them at a scale you can read and understand in an afternoon.
What you build isn't a throwaway exercise. Want to add a new tool? Implement the interface. Want tighter safety rules? Adjust the approval gate. Want to swap LLM providers? Change one line. Your agent is yours to keep, extend, and ship.
