The AI Developer's Field Guide

The AI Developer's Field Guide

Classes, Monsters, and Anti-Patterns in AI Coding

Generative AI has changed software development. It has also introduced a new class of failure.

Code can now look correct, pass tests, and still be wrong in ways that only show up later-in production, in edge cases, or in the hands of the next developer. This book is about those failures.

What This Book Covers

• The most common AI coding anti-patterns in modern software teams

• How tools like ChatGPT, GitHub Copilot, and Claude change code quality, review, and architecture

• Why AI-generated code often produces plausible but incorrect results

• How technical debt forms faster in AI-assisted development workflows

• Practical techniques for code review, testing, and prompt discipline

A Practical Framework for AI-Assisted Development

This book introduces a working vocabulary for understanding how teams actually behave with AI:

• Developer archetypes (Fighter, Wizard, Rogue, Cleric)

• Failure modes (Scope Creep Kraken, Congealing Slop, Phantom Intern, and others)

• Tool-driven patterns that emerge from real-world usage

These are not metaphors for their own sake. They are labels for repeatable problems teams encounter when using AI to write code.

Who This Is For

• Software engineers using AI coding tools

• Engineering managers and technical leads

• Teams adopting AI-assisted software development

• Anyone responsible for code quality, maintainability, and delivery

The Problem

AI makes it easy to generate code faster than you can understand it.

That creates predictable issues:

• Systems that grow quickly but are difficult to maintain

• Code that passes review but fails under real conditions

• Teams that ship more while understanding less

Without shared language, these problems are hard to identify and harder to fix. This book provides that language.

What You Get

• A clear way to diagnose problems in AI-generated code

• Patterns you can reference in code reviews and retrospectives

• Concrete practices that improve how teams use AI tools

• A framework for staying effective as development continues to change

This book helps you avoid the most common mistakes-and build better habits before they become defaults.