AI Coding in 300 Questions: Learn AI-Assisted Software Development and Coding Agents One Question at a Time and Prepare for Technical Interviews Along the Way

Master AI Coding—One Question at a Time

300 questions to understand AI coding, coding agents, AI-assisted software development, MCP, repository context, testing, debugging, security, code review, and production AI engineering—and prepare for technical interviews along the way.

AI is changing software development.

Developers are no longer using AI only to autocomplete code. Modern AI coding agents can explore repositories, understand context, modify files, run commands, debug failures, generate tests, review code, work with Git, and help move engineering tasks from an issue to a pull request.

But using these tools effectively requires much more than writing better prompts.

How should a coding agent understand a large repository?

What context should you give an AI coding assistant?

When should an agent plan before editing?

How do you prevent hallucinated APIs and dependencies?

How should AI-generated code be tested and reviewed?

What is MCP, and where does it fit?

And how do you know whether AI coding is actually improving developer productivity?

AI Coding in 300 Questions gives you the structure.

Through 300 carefully ordered questions and answers , this book takes you from the fundamentals of AI coding to production-grade coding-agent architecture.

Inside, you’ll learn:

AI coding, coding agents , and AI coding assistants

How modern AI coding tools interact with software repositories

Prompting and context engineering

Repository exploration, code search, and dependency awareness

Coding-agent tools, terminal access, tool calling, and MCP

Planning, implementation, refactoring, and debugging with AI

Unit tests, integration tests, regression tests, and verification

AI-assisted code review, Git, commits, pull requests, and CI

Sandboxing, least privilege, secrets, prompt injection, and supply-chain security

Productivity, model routing, token cost, evaluation, and reliability

How to build your own coding agent architecture

AI coding system design and technical interview preparation

Every question includes a concise Short Answer , a practical explanation, and an Interview Answer to help you communicate the concept clearly under pressure.

This is not a book about blindly accepting AI-generated code.

It is about learning how to engineer with AI .

You’ll understand when to delegate work to an agent, what context it needs, which tools it should use, how to verify its output, and when a human developer must take control.

Along the way, you’ll learn to reason about the trade-offs that matter:

AI assistant or coding agent?
Small patch or large refactor?
One model or model routing?
Autonomous execution or human approval?
More context or better context?
Fast generation or trustworthy verification?

Whether you are a software developer, aspiring AI Engineer, experienced engineer exploring AI-assisted coding , or preparing for technical interviews, this book gives you a practical path into AI-native software development.

By Question 300, you will not simply know how to ask AI to write code.

You will understand how to design, control, evaluate, and safely operate the systems that write code with you.

Start with Question 1.

By Question 300, you’ll be thinking like an AI-native engineer.