We introduce basic prompt patterns for coding and advanced API prompt patterns for leveraging artificial intelligence.

[The 2nd edition is scheduled for completion in 2026] You can develop your programming skills while exploring the fundamental principles of Large Language Models (LLMs) such as ChatGPT and Claude in depth. You can learn a variety of information and development techniques that are often difficult to come by.

Without a single formula or line of code, this penetrates the essence of basic statistics necessary for AI development and application.

It enables junior developers to understand the entire development process, from planning to coding, deployment, and verification, by using AI as a development tool.

It covers a wide range of topics, from prompt engineering theory and practical techniques to the latest application cases and security/ethical issues, providing practical assistance to LLM-based service developers, data scientists, and AI planners alike.

It helps train the "constructive thinking" needed to frame problems.

We present ways to improve RAG performance based on Cognitive Load Theory. To overcome the limitations of existing RAG enhancement techniques, we synthesize various methods by applying the conceptual framework of cognitive load.

"I only changed a name, but the code has transformed." I have summarized the core of readable code, 'naming that reads well,' from principles to examples. Easy-to-read names are the beginning of collaboration.

This lecture is designed to be easily understood even if you have no prior knowledge of Secure Coding. After covering fundamental secure coding concepts, it focuses on web service security. This course was originally conducted as a special lecture hosted by OO University. It provides over 160 source codes with extensive comments, pinpointing core topics and techniques that can be applied immediately in the field.

You can quickly understand the basic concepts and fundamental syntax of the C language.

We present various clean coding techniques.

[Scheduled for completion of the 2nd edition in 2026] This book provides detailed explanations of various language models developed throughout the process, starting from the beginnings of natural language processing technology to the latest LLM models.

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.

We will look at how to collect and analyze user requirements for planning an LLM service.

Explore the limitations of LLMs, the latest technologies to overcome them, and projected future technologies.

[Scheduled for completion of the 2nd edition in 2026] We will explore the types of applications and web services that can be built using LLMs.

[Scheduled for completion of the 2nd edition in 2026] Explains why LLM is necessary, the technical background, and basic concepts for LLM planners and LLM application planning managers.

[Scheduled for completion of the 2nd edition in 2026] We will explore the types of applications and web services that can be built using LLMs.

We will look at how to collect and analyze user requirements for planning an LLM service.

Now, with the power of AI, anyone can easily plan apps and design UIs! It's okay even if you don't know coding or have no UI experience. AI tools like Claude and ChatGPT will turn your ideas into reality. With just a few questions, you can analyze target customers, design app structures, and even automatically generate UI screens. In this lecture, we will teach you step-by-step from the basics so that even those who are new to Figma can follow along. Even without drawing by hand, you can import existing website UIs at once with the HTML to Design plugin, and with AI tools like Google Stitch or readdy.ai, you can create high-quality screens in a few seconds. This lecture is perfect for anyone dreaming of starting a business, wanting to switch careers to a planner, or wishing to communicate with developers. Instead of complex theories, we will only teach practical know-how that you can immediately use. Now, with just an idea, anyone can plan app services!

In the AX era where AI technology and UX design converge, what strategies should product teams use to design customer experiences? A 17-year veteran senior researcher from a major corporation and knowledge sharer with a PhD in HCI will share insights based on the latest trends, use cases, and research findings.

Re-emphasizing novice instructors as digital content business creators provides an opportunity to reach more learners, and improve the quality and efficiency of education through AI-based educational content creation and management. This course teaches instructors how to use new technologies to enrich the learning experience of learners, including hands-on practice in using AI tools and developing digital content businesses.

This is our 'actual real-world workflow,' and we are releasing the 'onboarding video' used for planners and developers joining our company. It teaches you how to design service screens without a designer and create UX flows and prototypes even if you don't know Figma. Our company maximizes productivity by prototyping quickly during service planning to enable fast decision-making, finalize necessary features, and utilize them directly in front-end development. If the response is positive, I will upload more lectures on other "real-world workflows."

This course provides UX principles and practical know-how necessary for planning and designing AI products. We will explore user-value-centered AI utilization methods, UX planning and design methods using AI, core UX principles and theories learned through everyday design cases, and UX research and data analysis methods for providing a better experience.

[Problems This Course Solves] - The limitations of planners who have ideas but cannot build them directly - Inefficient decision-making based on imagination: "Please make it like this" - Bottlenecks caused by requesting and waiting for the development team for every data analysis or API verification - The reality of using AI tools but remaining at the level of simple ChatGPT Q&A [What You Will Learn] 1. Redesigning the Planning Process in the AI Era - Traditional: Planning → Design → Development (Sequential waiting) - Shift: Writing PRD → Generating Prototype → Decision-making based on the actual product → Delivery after confirmation - Moving from planning explained through documents to planning demonstrated through actual products 2. Designing AI Agents for PMs - Harness Engineering: Designing a working structure rather than just asking AI questions - CLAUDE.md, Rules, Hooks, MCP, Plugins — The roles and design principles of each layer - Agent Router: A structure where a single request is automatically assigned to the optimal agent - PGE Pipeline: Planner → Generator → Evaluator, quality control design for large-scale tasks 3. Building Your Own AI Team - Planning/Research, Product, Design, Development, Marketing — 20+ agents across 5 columns - Actual workflows where a solo planner manages a team of experts - Connecting external tools via MCP (Notion, Figma, Slack, data sources) - Automating repetitive tasks with one-command "Skills" 4. Practical Automation of Supplementary Tasks - GA4 + Clarity + GSC + BigQuery → Integrated dashboard + automatic weekly insight generation - Direct calling of in-house APIs → Scenario verification → Quality evaluation reports - BigQuery cohort analysis → Aha Moment hypothesis verification - A/B testing, Notion synchronization, UI/UX audit automation --- Who should take this course: - PM/PO/Service Planners tired of waiting times and review cycles in the planning process - Those who want to properly design AI as a professional work tool - Those who want to make data-driven decisions themselves but lack analysis team resources - Non-developers who want to move past their fear of the "terminal" [Prerequisites] - None. We guide you through everything from installation to setup. - No coding experience required. We focus on design and application from a PM's perspective. [Changes After Taking the Course] - Increase decision-making speed by creating working prototypes directly from a single PRD.md - Design and operate your own team of AI agents - Directly automate data analysis, API verification, and report generation