Future of Developers! AI Vibe Coding Part 1 - Create Your Own MCP Server with Cursor

LangGraph, packed with the know-how of an AI Agent lead from a major corporation. I will pass on the knowledge I've gained through trial and error in the field.

We invite you to the fascinating world of coding where you analyze and visualize financial statements using only prompts. Without a single line of code, you create and deploy a service in consultation with AI.

This is a hands-on tutorial on how to integrate with IntelliJ and develop quickly using the Model Context Protocol (MCP).

Let's create a service that improves itself even while you sleep! Learn step-by-step how to build a 24-hour vibe coding system using loop engineering with Codex.

[Source Code Provided] No coding knowledge required. Build it instantly in your browser using Google's latest tool (IDX) without any installation! Stop studying coding syntax! This is an ultra-fast, hands-on course where you'll build an RAG chatbot that perfectly understands internal company documents through AI conversation (Vibe Coding) in the Google IDX environment and deploy it live to the web.

LLM: A pro quickly delivers core content, from essentials to practical tips!

AI is only as good as you are. Learn vibe coding properly in three steps: how to use AI → essential foundational knowledge → project development. For those who want to learn vibe coding the right way, we deliver the core concepts that remain unchanged regardless of which AI you use, broken down into bite-sized pieces.

While your colleagues are already working with Claude Code, are you still doing all of this manually? Don’t worry! Take this course, and you too will become a vibe-coding master.

"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.

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.

Learn the entire process of running the latest Gemma 4 model directly on your MacBook without the burden of paid API costs. You will master performance maximization techniques using Apple Silicon's Metal API and optimal parameter settings for different VRAM capacities, while gaining the ability to build production-level local AI infrastructure based on FastAPI.

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.

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.

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 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.

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.

Develop various features using Spring WebFlux. This course will teach you WebFlux's essential concepts and practical implementation.

"How is a 1-trillion parameter model trained?" Discover the scaling strategy of Kimi K2.5, revealed directly on stage by Moonshot AI at GTC 2026, in Korean on Inflearn. 2x token efficiency · 1 million token context · 1,000 agent swarm The next step for open-source LLMs is here. * This lecture is released for free through an official collaboration between Moonshot AI, the creator of Kimi, and Inflearn.

This course teaches you the know-how of the entire process, starting from a single idea, through planning, design, development, and up to app release on each platform. Start developing your own monetization app right now.

Learn the entire process of building AI-callable business tools, from the concept of MCP (Model Context Protocol) to implementing a TypeScript-based custom server using Antigravity. Through a brand copy review example, you’ll develop practical MCP skills that can be applied immediately to automating repetitive tasks, integrating internal company data, and connecting APIs.