AI 시대의 주니어 개발자

About this book

AI can write code quickly—but how much of it do you really understand? Rather than showing you how to produce more code, this book focuses on leaving behind code you can explain and verify. It helps job seekers and developers with one to three years of experience use AI as a teacher, pair programmer or delegated worker, while building the fundamentals through unfamiliar repositories and small, reproducible failures. Across 75 pages, it explores changes in the development environment, core skills for junior developers, agent permissions, policies and evaluation, and examples from coding, internal workflows and operational incident response. Five hands-on exercises using the Python standard library cover duplicate-page bugs, discount calculation boundaries, safe tool execution, token budgets and legacy characterization tests. The final sections include a 30-day growth plan, before-and-after self-assessments and a mini-project evaluation sheet. It is for readers who want a portfolio that captures problem definitions, tests, Git diffs and decision records—not just screenshots of the finished result. Companion materials include 17 copyable prompts, Python exercise code and tests (23 items in total), and verification checklists for frontend, mobile and database work. The download opens a practical-kit ZIP shared through Naver MYBOX. Use the example files included in that ZIP when running the code. The book's technology-news analysis covers April 15 to July 15, 2026. Tools, prices and policies may have changed since then. The material does not guarantee employment, income or productivity outcomes. Please check the included usage guide for permitted uses.

Who it is for

Job seekers and new developers who wonder whether AI-generated code is safe to use as-is Developers with one to three years of experience who want to practice reading unfamiliar repositories, debugging and testing Self-taught and bootcamp learners who feel a gap between faster AI use and real skill development Mentors and team leads who teach junior developers both AI workflows and the fundamentals

Contents

1. Introduction · Analysis methods and limitations
2. Part 1 · Seven shifts revealed by the past three months
3. Part 2 · The developer's role, learning with AI and skills for the future
4. Part 3 · Building and working with AI agents
5. Part 4 · Three real-world cases: what to delegate and where to stop
6. Part 5 · Strategies for individuals and teams · A 30-day growth plan
7. Part 6 · Five hands-on coding tutorials
8. Part 7 · Reader workbook: turn what you read into skills
9. Appendix · Agent-building checklists, copyable templates and analysis sources