[Enterprise Challenge] AI Coding with Claude Code

Who will review the code when you submit a PR to GitHub? 🤔

When team members are busy, reviews get pushed back by a day or two, and deployment is delayed.

What if, the moment you submit a PR, three AI agents immediately jump in to find security vulnerabilities, write tests, and point out refactoring opportunities?

The answer lies in Claude Code's Agent Teams.

The era of code autocompletion is over. Starting from 2025, Agentic AI—which reads, plans, executes, and even validates code—has begun to take its place within the developer's terminal. Claude Code is the tool at the forefront of that shift.

In this course, we will build a complete workflow for operating real-world projects using the Claude Code CLI. You will learn how to teach the AI your team's specific coding standards using Custom Skills, automate quality gates with Lifecycle Hooks, and design systems where multi-agents develop in parallel using Agent Teams. We cover the advanced features of the latest Claude Code version at a professional, practical level.

In this course, experience a new dimension of development where you tell the AI, "Form a team and build this feature!"

Features of this course

📌 How do you design a pipeline where three AI agents review a PR simultaneously? We provide a real-world architecture that integrates Claude Code into production workflows.

📌 We provide practical operational insights not found in official documentation, such as Custom Skills design, Hooks-based quality gates, and Agent Teams task distribution strategies.

📌 20% Theory, 80% Practice. You will execute all workflows directly in the terminal and see for yourself whether the agents actually operate as intended.

📌 This course is for professional developers. The programming language does not matter, but you should be basically familiar with the terminal and Git.

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After taking the course,

• By combining Custom Skills and Hooks, you will be able to establish your team's own coding standards. Repetitive tasks that make you wonder, "Why do I have to do this manually every time?" will disappear.

• With Agent Teams, you can design a parallel development workflow where multiple agents write, review, and test code simultaneously. It allows you to work like a full team even when you're on your own.

• You can build a PR automated review pipeline with GitHub Actions + Claude Code CLI. You no longer have to stay late at work because of reviews.

• From context window management and token cost optimization to model selection strategies. You will experience the difference between using AI tools "well" versus "just" using them .

• You will be able to develop new habits of coding efficiently in the terminal using natural language and developing with AI agents.

Here is what you will learn.

MODULE 1

A new experience of coding in natural language from the terminal

"Analyze this code," "Find and fix the bug," "Write a test" — with a single natural language command, AI reads, analyzes, modifies, and even runs tests on the code. We cover everything from setting up project context with CLAUDE.md to efficient context engineering.

MODULE 2

Custom Skills

Define AI behavior with a single Markdown file. Practice declaring skill metadata and hooks using YAML Frontmatter, and packaging workflows such as security reviews and team guidelines into skills.

MODULE 3

Agent Teams — Parallel development where multiple AI agents work simultaneously

The Lead plans, the Builder implements, and the Tester verifies. Each agent operates within an independent context window and is coordinated through a shared task list and messages. While watching agents work in real-time within a tmux-based split pane, you will practice team orchestration, including task distribution, dependency management, and Delegate Mode.

MODULE 4

Integrating Claude Code into CI/CD Pipelines

The moment a PR is submitted, Claude Code automatically reviews the code. You will directly build a pipeline that executes non-interactively in Headless mode (-p flag), runs security scans, test coverage checks, and style reviews in parallel via GitHub Actions, and automatically posts the results as PR comments.

The person who created this course

Rose — AI Coding Educator

By combining traditional software engineering expertise with the latest AI tool utilization, I help developers acquire AI coding capabilities that can be immediately applied in practice.

• Master of Science in Software Engineering, Sogang University

• Global Enterprise Android/Java Developer

• Researcher at a public enterprise in the SW field

• Leader of the "Vibe Coding" study, which ranked #1 in participation rate at GPTers, Korea's largest AI community

• Created AI educational content for 540,000+ global students

• Creation and operation of Claude Code Custom Plugins (TDD, security review, Claude Code Utility)

Notes before taking the course