Inflearn - Lifetime Career Platform

Building your own emotional diary service with Spring AI + React It's time for our 4th project with Neo + Essential!

If you only know LangChain, it's just a chatbot; but if you know LangGraph and Multi-Agent patterns, it becomes a service. An active AI instructor will share the know-how to build operational AI Agent workflows from start to finish—going beyond simple prompt calls to handling tools, maintaining memory, and incorporating human-in-the-loop verification—using 17 practice notebooks and 4 multi-agent patterns (Subagents, Handoffs, Router, and Skills).

If you follow OpenClaw Parts 1 and 2, you eventually end up making a single agent do everything. As you do this, there comes a moment when prompts get tangled, memory gets mixed up, folders get messy, and you feel stuck, not knowing how to organize things anymore. This lecture is the "Introduction to Multi-Agents (Part 2.5)," designed to help you move one step further from that point. While maintaining a single bot, we will separate roles into two agents—planner and editor—and connect each agent to different workspaces and Telegram forum topics. You will personally build a structure where "different agents respond depending on which room you speak in." By following the hands-on practice, you will have the following in your environment: - A configuration file defining two agents: `content_planner` and `content_editor`, - A content folder structure where planning and drafting are separated, - A Telegram group chat where different agents are attached to specific forum topics, - And one actual draft of an Inflearn course introduction created through the collaboration of the two agents. In short, this is a practical class that helps you design the first step of upgrading your Telegram bot from a "single AI assistant" into a "small AI team with divided roles."

Build a Saju (Four Pillars of Destiny) analysis AI agent that integrates Manseryeok, Astrology, Zi Wei Dou Shu, Onomancy (Name Study), and MBTI using n8n workflows and Python algorithms. We will complete a production-level service system from start to finish where 13 specialized agents collaborate to generate professional-grade Saju reports.

This course is not about non-developer office workers learning coding itself, but rather an education focused on developing the ability to solve business problems directly using AI agents. Previously, one had to rely on IT departments or outsourced development when problems arose, but we are now in an era where you can design alongside AI and create immediate prototypes to implement task automation. The core competencies required for this are problem definition, establishing solution strategies through AI collaboration, and the ability to build the necessary tools yourself. In particular, by utilizing Codex CLI, existing ChatGPT users can practice agentic coding immediately without additional costs, allowing non-developers to quickly gain practical experience. The curriculum is structured step-by-step, covering everything from understanding changes in the AI agent era to development basics, terminal usage, Codex CLI-based agentic coding, problem structuring, Django web app development, and the creation of actual task automation apps. Learners can secure task automation capabilities by directly building applications applicable to real-world work, such as To-Do lists, checklists, schedule management, meeting minutes, and summarization tools. The entire course is designed as a modular micro-learning system composed of short units, allowing for rapid learning of necessary content and immediate reuse during work.

Even those who know nothing about coding will be able to create their own automated stock trading program by giving commands to AI in Korean!

I highly recommend Spring AI to developers using Spring Boot and React, as well as those considering the introduction of AI systems in corporate environments. This course goes beyond a simple introduction to libraries; it helps you understand the core concepts and internal structure of Spring AI, and strengthens your practical implementation skills through various hands-on examples. The course is based on Spring AI version 1.1.x and provides continuous technical support and expansion strategies to ensure you can adapt to future version upgrades. Furthermore, we expand the practical value of Spring AI technology by utilizing MCP (Model Context Protocol) to achieve cross-domain context integration, AI linkage in distributed environments, and AI architecture design suitable for enterprise environments. With the goal of building AI systems that can actually be deployed in corporate settings, this will serve as a practical guide that balances theory and hands-on experience.

It’s okay if you don’t know how to code. This course focuses on the experience of using AI to build an ad-revenue-generating Android app from scratch and successfully launching it in just one day. Many people stop at these stages: “I built the app, but how do I monetize it?” “I tried adding ads but got stuck on AdMob, policies, and reviews.” “I gave up right before launch because of the privacy policy.” In this course, we will navigate through every "drop-off point": 👉 Idea → App Creation → Ad Integration → Store Launch Essentials → Actual Deployment. We let the AI do the work, and we make the decisions. The goal is to complete an app with a "functioning revenue structure" within a single day.

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

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.

It's an era where you can create apps even without knowing how to code. If you have an idea, you can implement the features you want by conversing with Claude Code. This book introduces a new development approach where you communicate with AI to achieve desired results, rather than writing code directly. Through 15 hands-on projects, you'll experience various workflows with AI, from creating personal web pages to handwriting recognition, quiz apps, image-based recommendations, AI summarization, Notion automation, and cloud deployment. Rather than simply following examples, this provides an experience of completing the entire real-world development process—from planning, design, testing, to deployment—in collaboration with AI.

Now, your AI is no longer in the cloud. It runs directly inside your laptop. Using LM Studio and Ollama, we will show you how to build a Private AI environment that runs entirely locally— from data processing and document analysis to code generation. Without security concerns, without costs, and even faster— Move beyond simply "using" AI and start "truly mastering" it.

We are launching a "Complete Reading Challenge" for the book "AI Agent Engineering," a practical guide to building proactive agent systems using LLMs. This book covers the core components of agents step-by-step, from tool selection to orchestration (designing planning and execution flows) and memory management. It also explores how to scale into multi-agent architectures where multiple agents collaborate by dividing roles. Furthermore, it expands your perspective from "how to build" to "how to operate" by covering essential production-level topics such as reliability, security, and governance. Do you want to design agent systems that go beyond simple automation to operate safely and transparently according to human intent? Join the book and the challenge to discover a concrete roadmap for turning your ideas into production-level systems!

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.

Non-Majors Welcome: Real-World Vibe Coding Projects Created Through Conversations with AI

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.

We will teach you all the know-how for YouTube Shorts automation. Stop using expensive external services! Let's create AI videos cost-effectively using open source and libraries!

"Turn your Java code into the hands and feet of AI! Practical Agent Development with Kakao PlayMCP and Spring AI" Traditional LLMs are limited to answering based only on their trained data, which can lead to issues with recency and accuracy. In this course, you will learn **MCP (Model Context Protocol)**—the next-generation standard protocol for connecting AI with external tools. Using Spring AI, you will build a server that communicates with various platforms like Kakao PlayMCP through a single implementation. Master the entire process from theory to real-world deployment and platform registration through the 'Proverbs & Psalms Counseling Center (JAMSI)' project, and grow into a true AI agent developer who can empower AI to handle tools independently.

🔥 Vibe Coding with Streamlit 🔥 Real-time coding experience where you can instantly create your own web service with just one line of code! Visual-focused, hands-on lectures tailored to MZ sensibilities - no complex backend knowledge required. Learn the basics of Streamlit and awaken your development instincts by directly implementing practical apps. Complete your own "personal service" with code in a vibe way right now 😎💻

No more AI toy projects that end with a single API call! Based on my experience designing and deploying a full-stack AI chatbot, I will guide you through the entire process of building an AI chatbot that "works as a real service"—covering streaming, tool calling, memory, multi-modal capabilities, and Human-in-the-Loop.