2026 Claude Code in Practice: Automating AI Development from Design to Implementation, Testing, and PRs

When AI says “implementation complete,” do you take it at face value? This Step 2 course has Claude Code and Codex handle everything from understanding the repository to implementation, testing, review, and PRs, while teaching you to evaluate results based not on completion descriptions, but on the scope of approval, execution evidence, and change risks.

Are you feeling stuck trying to implement an agent that goes beyond a simple chatbot? Based on my own trial and error and know-how from official documentation, I will show you how to build intermediate-level agents that can be immediately applied to real-world tasks.

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.

Beyond a chatbot that simply generates answers, you will directly implement an autonomous AI Agent that makes its own judgments, calls tools, and performs multi-step tasks. You will learn through step-by-step practice, covering everything from OpenAI Agents SDK's Tool Calling, Handoff, Guardrail, Session, and Tracing to connecting external tools and databases using MCP, as well as LangChain and Deep Agents' Planning, Subagents, Filesystem, and Memory. The ultimate goal is to equip you with the ability to design and implement tool-integrated AI Agents that can be applied to real-world tasks.

"A hands-on web development project course that covers everything from planning and design to implementation and deployment using Generative AI." We will complete the entire process together step-by-step—starting from idea conception, quickly creating designs with AI, implementing a functional website with React, and finally deploying it to the internet. Latest AI tools like Stitch and Figma Make will assist with your design work, and even complex coding will be taught in a way that is easy to follow step-by-step.

This is a practical web development project course where you complete everything from planning and design to implementation and deployment using generative AI. You will create designs using Stitch and Figma Make, generate code with AI Studio, and deploy them as actual services. Even if you don't know much about coding, you will learn how to develop alongside AI and complete your own AI web app. Now, you too can become a developer who collaborates with AI.

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.

"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.

Go beyond a simple system prompt to build an AI character chatbot that remembers users and whose relationship with them evolves, using persona design and Structured Outputs. In this 30-minute hands-on session, you’ll learn how to safely call the OpenAI API based on the provided starter project, process emotions, trust levels, and memories in a verifiable format using JSON Schema and Zod, and use an AI coding agent within defined constraints.

Create a program using the GPT API, and even generate images and videos!

Simple tutorials alone make it difficult to apply in practice. I will clearly pass on my professional know-how, covering complex state management and multi-agent design methods.

We explore how to create an AI judge by combining knowledge graphs, reasoning systems, and various agent frameworks such as CrewAI, LangChain, and AutoGen, which enable the implementation of LLM-based multi-agent technology.

Theory, numerical approximations, intuition, and visualization in integral calculus. Enhance your math-coding skills.

Solve the point where 80% get stuck at makeathons. Complete Raspberry Pi · Computer Vision · LLM · 3D Design in 4 weeks! Achieve top rankings at makeathons with a demonstrable smart mirror PoC!

I got answers from AI, but am I still doing the work myself? From the basics of using Claude Code to building apps, automating Instagram carousel posts, and researching competitors’ social media. Follow along while watching the screen and learn how to apply it to your own work. This includes 11 beginner-focused desktop app lessons, along with hands-on practice for real-world tasks.

This course covers implementing combat, UI, data, and server functionality for a Unity idle game using CLI- and MCP-based AI tools. You’ll learn the entire process of applying Firebase, ads, in-app purchases, and Addressables to launch a mobile game on Google Play.

AI agents can feel vague, right? We’ll share practical problem-solving know-how from real-world experience, covering everything from prompts and loops to graph engineering systems.

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.

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.

From AWS EC2 backend operations to automatic error fixing, we are revealing the entire development process of Sidabari (https://github.com/cx8537/sidabari), a Claude Code-based automation tool. In this course, we provide all the actual prompts and conversation history used as learning materials, allowing you to experience the entire prompt input process involved in its creation.