Practical Harness Engineering for Senior Engineers at Korea’s Top Tech Companies: Claude Code in a Real-World Spring Boot Environment

Explore → Plan → Implement → Commit. Master a proven AI development workflow with Claude Code. Learn everything from MCP and sub-agents to prompt engineering through 23 missions, and complete 3 real-world projects.

This is a tutorial-style Claude Code development course that beginners and those new to development can easily follow. Based on experience teaching planners, designers, and non-developers in offline classes, the course covers everything in one continuous flow—from beginner examples not covered in books to intermediate development examples. Using Claude Code, you will experience the step-by-step development process, starting with Hello World and progressing to a lucky draw, a device-optimized café menu management web page integrating Claude Design with Excel data, and a SaaS web application that can be connected to a database and deployed to cloud services. Tutorials are provided at each stage—theory, practice, and projects. Through hands-on exercises across 6 levels, you will learn AI-collaborative development methodologies and experience the entire development cycle, including cloud deployment and operations.

The time when your imagination becomes reality—welcome to the world of 'Vibe Coding.' We prepared this course for those of you who may not know coding but know exactly what you want to create. With the emergence of AI tools like ChatGPT and Claude, people say that anyone can develop software. But what happens when you actually try? - "It writes simple code well, but once the number of files increases, the AI forgets what came before." - "It looks plausible, but when I run it, errors occur—and when I ask it to fix them, it gives me even more unrelated code." You’ve probably had experiences like these at least once. I experienced the same frustrations when I first started collaborating with AI. AI was an excellent 'assistant,' but it had limitations because it couldn’t see the entire forest. However, after discovering OpenAI Codex CLI and learning a new approach called 'Vibe Coding,' my development process completely changed. This course will solve the problems you’re experiencing while transforming you from someone who isn’t a coder into a director who commands AI agents. Equip yourself with the powerful tool Codex CLI, and join me on the exhilarating journey of Vibe Coding, where imagination becomes reality.

Building an MVP with AI is no longer difficult. However, most projects stop at the next stage. 👉 You’ve built the features 👉 But development doesn't continue Why does this happen? The problem isn't the code; 👉 It's because there is no structure that allows AI to work continuously. --- In this course, based on an existing project, 👉 We will cover the process of building a structure 👉 That allows AI to continue development on its own. --- Instead of simply using AI tools, we will: * Create a docs structure * Define the SSOT (Single Source of Truth) * Execute development on a per-ticket basis * Connect QA and iteration cycles 👉 To complete a single "AI Development System." --- Through this process, you will: 👉 Create a structure where development continues 👉 Even without a human manually coding. In other words, you can: 👉 Build and understand a development system 👉 That operates AI like a team. --- This course is designed for: 👉 Those who want to build a structure applicable to their projects immediately 👉 Those who started development with AI but found it difficult to sustain 👉 Those who want to move to the next level after "Vibe Coding" --- Beyond just learning, we provide an experience where you: 👉 Take action 👉 Build a structure that actually works 👉 And walk away with a framework you can apply to your own projects.

If you design the tests first, AI handles the implementation. A practical development approach that captures both speed and quality!

Messy code, a flood of requirements... If you're looking for a breakthrough with AI, Learn how to become a "high-performing developer" by leveraging AI in legacy environments, taught by the former VP of Engineering at Toss Payments. Legacy code isn't going anywhere, even in the age of AI. It’s no exaggeration to say that every company has legacy code, unless they were founded today. So, how should we utilize AI in this reality? In this course, the former VP of Engineering at Toss Payments, who led a large-scale payment service organization, demonstrates firsthand how to work effectively using AI in legacy environments. This isn't just a course about how to use AI or basic coding skills. The goal is to help you develop your "critical thinking" as a developer and truly understand what it means to work effectively.

While LLMs are currently transforming the development environment, what truly matters is not just "writing code on your behalf" but integrating them as features into a service. This course provides a step-by-step guide to implementing a lightweight yet polished Tarot reading service using Next.js and the OpenAI API. In the first stage, we will build an MVP that works without a backend, connecting the user input flow (questions/threads/card selection) to result generation. In subsequent stages, we will expand the functionality by building a backend, implementing general login and OAuth, adding community features, and creating a reading dashboard. Finally, we will conclude by deploying to AWS and integrating Google AdSense to complete a service ready for actual operation. Additionally, we will cover understanding pricing structures and cost optimization strategies to ensure that LLM API usage costs do not become a burden.

Learn deep learning through PyTorch. Ultimately, the course covers image classification.

Do the results of vibe coding keep turning out differently from what you intended? Learn a workflow that uses specification-driven development (SDD) and Spec Kit to define goals, scope, business rules, and completion criteria, then shares the same specifications with Claude Code and Codex to reduce repetitive revisions.

It's okay if you don't know a single line of code. We are now in the era of 'Vibe Coding,' where you develop by 'conversing' with AI.

Design by me, code by AI: Learn object-oriented design with Unity 6 and C#, Copilot / Claude prompting, and AI code verification to complete a 60-second survival 3D game. Become a game developer who knows how to work with AI.

This course trains you to think in terms of frontend system design through real-world service cases such as Threads feeds, Amazon shopping carts, the Netflix streaming UI, Google Docs collaborative editing, Micro Frontends, Agentic UI, and Observability.

Learn how to efficiently manage multiple AI coding agents, including Claude Code, Codex, and pi, from a single screen. Starting with tmux concepts, you’ll practice using Herdr’s sessions, panes, plugins, and CLI to build an agent workflow that keeps your work running even when your SSH connection is interrupted. Complete the essential development environment for the Agent era in just one day.

This is a process for completing IoT products without complex coding, using the Vibe Coding methodology powered by AI agents. You can experience the entire product development cycle in a condensed format—from embedded hardware control and AI vision recognition to PCB design, 3D printing, and web/app service development—allowing you to launch functional, commercial-grade IoT devices.

The more you modify, the more anxious vibe coding can become. Now create save points you can return to anytime. You don’t need to know Git commands. Just tell the AI what to do, and it will handle saving, backups, and restoration.

"Beyond Data Analysis: From Predictive Model Design to Optimization (29 Lectures in Total)" Have you finished your data analysis but feel stuck when it actually comes to building a model? We help you fully master not just how to call libraries, but the working principles of each algorithm and optimal model validation strategies.

Are you overwhelmed by AI-generated backend code and unsure where to look? Learn how to identify missing conditions in requests, APIs, data, concurrency, authentication, and caching—and what requirements to give the AI and what criteria to use when reviewing its output.

AI-generated SQL ran without errors—but does that mean the result is correct? Learn to identify missing criteria in a row’s meaning, values, queries, aggregations, changes, and concurrent requests, as well as which data rules to communicate to AI and what evidence to use when reviewing the results.

From coding basics to launching your own app all at once?! The App Build All-in-One, connecting fundamentals and practical application.

This course conducts hands-on practice related to Diffusion models among generative artificial intelligence models. By reading and implementing the prompt-to-prompt paper, which is a representative Diffusion model application paper, we expect to cultivate the ability to understand the latest artificial intelligence papers.