[VOD] Hwang Hyun-tae (AX) Builder Meet - How to Execute AX to Drive Team Performance

This course is for non-developers who want to learn Claude Code but find the official documentation full of developer jargon, while YouTube focuses only on vibe coding (app/web development) and doesn’t explain how to use it for automating real-world work. Concepts are explained through comics and easy-to-understand analogies, with hands-on practice in a desktop app environment without using the terminal. It also walks you through three practical work-automation examples from start to finish: work automation, creating detailed product pages, and automating the production of card news, blog posts, and short-form videos.

[Sustainable AX and How to Collaborate with AI Colleagues] Have you encountered these limitations when trying to apply AI tools to your work? 🙋‍♂️ : "Entering the commands from scratch every time is actually more of a hassle." 👨‍💻 : "I’m tired of one-off tasks that simply involve repeating copy-and-paste." 🤷‍♂️ : "Since I don’t have a background in development, I can’t even imagine automating more advanced tasks." What we need now is not simply 'how to use tools'—learning the features. It is a mindset of cultivating your own AI colleague—one that understands the context of your work and grows smarter on its own over time. We transparently share a practical, field-oriented AX (AI transformation) guideline developed by a non-developer planner through countless trials and errors in the workplace.

When you use a chat-optimized LLM for classification, routing, and guardrails, it returns a string that you then have to parse again. This comes with hallucinations, type drift, delays of several seconds, and output-token costs. This course follows the architecture of Jev, TypeSafe’s first System One model: provide a state, and it returns typed decisions within a schema along with calibrated probabilities. The model does not generate strings. It covers, through concepts and code, why parallel sampling and RLCD (Reinforcement Learning for Calibrated Decisions) make those decisions fast, how to combine Choice · Score · Noul in a single request, and a hybrid approach that leaves structurally defined judgments to Jev and open-ended descriptions to an LLM.

"The cost of making one app is the price of a cup of coffee." Learn vibe coding with Kimi K3, an open-weight model with 2.8 trillion parameters. You’ll launch your first app in a browser with a single sentence, create a UI by providing a hand-drawn sketch, and have it build and deploy an entire full-stack web app to the internet. If you’re already using Claude Code, you’ll also learn how to keep that environment as-is and simply switch the model to K3. It’s pay-as-you-go, not a monthly subscription. In an actual test, one session that created and deployed an app cost 1.69 dollars. 14 lessons, approximately 102 minutes total; the course is free.

There are so many stories saying, "Automation is just one click away." However, it's easy to give up when you actually try to apply it to your own work. We have captured the raw record of a team that spent six weeks narrowing the gap between "it works" and "I am using this for my work!"

This course teaches the essential CS knowledge required for web development using AI. If you don't understand the principles of servers, databases, and deployment, "Vibe Coding" will inevitably hit a wall at some point. Through interactive textbooks, you will quickly learn essential concepts, enabling anyone to complete a web project using Vibe Coding.

Latest version as of October 2026. This is a 299-lesson course created by YouTube’s “AI Adjunct Professor Lee Jong-beom” (54,000 subscribers). It guides you step by step, starting with how to open a browser tab and progressing to creating an AI employee team with Claude Code. It includes approximately 290 practice worksheets and 1,000 credits.

Master Claude Code from the basics to a professional level. Learn core features (CLAUDE.md · subagents · MCP · Hooks, etc.), develop and deploy a real-world service, and wrap up with foundational appendices and advanced-use lessons for non-majors.

The starting point for a successful AX (AI Transformation) is not technology, but the leadership's understanding of AI. This course is designed to help executives grasp the overall flow of AI easily and clearly, while covering ways to maximize business productivity through the familiar Google Workspace and Gemini. Moving beyond mere theory, we provide 5-minute hands-on tasks for each session and a 1:1 customized online meeting (30 minutes) with AX Cody to systematically guide your company's tailored AI adoption strategy.

How to Build an Efficient Startup Workflow System with Just Notion 🧑🏻‍💻 (Practical Workflow Templates Provided by Practitioners)

Learn how to structure diverse data—including students’ grades, school records, and areas of interest—using the AI-SPARS tool, and leverage an LLM to design everything from major exploration and college/admissions strategies to personalized roadmaps. Rather than simple Q&A, you can immediately apply in practice a systematic AX-style career and college counseling process that progresses from Profile-Interview-Major-College-Admissions Track-Gap-Roadmap-Smart Report-Portfolio.

What if you could hand over those repetitive tasks you've been stuck with all day to an AI assistant? Introducing a guide to building your own AI work assistant—not a GPT chat that requires a fresh explanation every time, but one that remembers you, works in your style, and even reports back via Slack. From installation and Slack integration to skill setup, Notion/Calendar/Email automation, and even security and cost management! Complete an AI work system you can use immediately at the office, with a step-by-step approach that anyone can follow even without coding knowledge. Point 1. Set up a "Personalized AI Assistant" that remembers you, unlike standard GPT chats - Build the basic AI assistant environment by following steps from OpenClo installation to Slack integration. - Create an assistant that works according to your professional style by setting its personality and rules. Point 2. Master practical automation patterns to reduce repetitive tasks - Connect with actual work tools like Notion, Calendar, and Email by installing skills. - Practice immediate automation for tasks such as morning briefings, writing work logs, sending emails, and managing schedules. Point 3. Complete an AI work system that can be used safely in the workplace - Review essential checkpoints for professionals, including permission management, security settings, and cost control. - Learn how to expand from a single AI assistant to a multi-agent work system.

The one-year real-world record of a company that declared an “AI all-in” strategy. This case study introduces how DeNA, one of Japan’s leading IT companies, transformed an organization of 3,000 people into an AI-native company. For organizations preparing for an AI transformation, we’ve gathered only the most useful insights.