Kakao Interviewer’s Multi-AI Agent Architecture [A2A Protocol]

Innovation in Work Efficiency and Creativity – Agentic AI AI is now evolving beyond simple automation into a new stage where it can judge and execute on its own. Agentic AI is at the center of this change, serving as a core technology that helps businesses and organizations operate smarter. In this course, we have organized the content clearly and simply so you can understand how Agentic AI connects decision-making with execution and how it can be applied to practical work. Discover the essential knowledge for every professional preparing for the future right now.

This course is not about collecting a large number of prompts. It is about learning an AI directing framework that can be applied immediately to any role or task. Even if you download prompts for specific tasks, in practice you still need to find the prompt you need, adapt it to your situation, and spend time revising the output. Through the M·A·G·I·C prompt framework, you will learn how to design the purpose, context, examples, completion criteria, and review criteria all at once. From reports, proposals, and marketing execution plans to meeting summaries, work emails, and repetitive task automation, you can connect everything with a single framework, reduce unnecessary revision conversations with AI, and build practical AI skills that will change the speed of your work starting tomorrow.

You know about AI agent frameworks, but understanding how they work and applying them in practice can be difficult, right? Drawing on firsthand experience from Silicon Valley, we’ll guide you from the core principles to practical applications.

You may have experienced Claude Code producing different results for the same request each time, violating the rules specified in its instructions, and being overly lenient in approving its own output. While developing platform servers in Pangyo and spending over $1,000 a month on Claude Code, I addressed these issues by building a harness consisting of instructions, Hooks, permissions, and a Sandbox instead of relying on prompts. In this course, you’ll build that harness from scratch, add Subagents, Agent Teams, and headless execution, and leave with a complete setup that you can copy and use as-is in other projects.

Mastering difficult AI with just one single analogy?! A first step into AI principles, understanding through core concepts rather than just terminology.

Stop making mass-produced shorts that just repeat gacha-style content with a single click! This is an integrated introductory and practical course where you will understand the principles of how AI creates videos even if you don't know filming or editing. You will complete one YouTube video using Veo, Runway, Kling, HeyGen, and CapCut, and even create 'surviving AI shorts' that viewers watch until the end through LLM planning.

Acquiring probability theory is essential in the study of AI and machine learning. I recommend this to those who wish to study probability theory in more depth.

[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.

# AI Side Hustle King: Aiming for 1 Million Won per Month with 2 Hours a Day I'll reveal every detail of my know-how—raising two kids while generating 15 million won in pure profit / 60 million won in sales per month, working just 2 hours a day. I'm confident I'm the best at utilizing AI in online sales. Smart Store / Coupang / Branding - An all-in-one package covering sourcing / marketing / detail pages / sales This isn't about randomly churning out products based on luck. It's designed to read the market → create a structure that sells → systematically drive exposure and conversion. I've included only what's essential, in the right order, to minimize wasted effort while using minimal time. ## What This Course Does for You - Helps you select "products that sell" when you're unsure what to sell - Teaches you how to read keywords and intent to reach profitable customers first - Shows you strategies to avoid competition by changing "category names" for the same products - Sets up a roadmap for the structure and timing that generates exposure on Coupang and Naver - Boosts conversion rates with detail pages and connects reviews/blogs/ads - Reduces image/content creation time with AI, making 2-hour daily operations possible ## Core Flow Included in the Curriculum **1) Planning Products That Sell** - Selling customer "problems," not products - Extracting ideas from customers' inconvenient habits - Reading market depth through search patterns - Practice: Identify 3 problems your product solves **2) Practical Keyword Research** - Reading "intent" is more important than search volume - Capturing key points in the search → comparison → purchase flow - Differences between Coupang vs Naver keyword research - Practice: Finding keywords for your product **3) Categorization to Avoid Competition** - The principle that the same product enters a different market with a different name - Creating a competition-free position by inventing new category names - Success case analysis + niche exposure structure - Practice: Planning a new category name for your product **4) Platform Strategy (Coupang·Naver)** - Making top exposure through "structure," not "effort" - Understanding Coupang/Naver exposure logic - New category entry timing, reading traffic data - Practice: Creating a platform entry roadmap **5) Detail Pages That Create Conversions** - Customers buy emotions and confidence, not products - Designing storylines with emotion → awareness → persuasion flow - Practice: Rebuilding emotional points in your detail page - Actual production including redesign with ChatGPT/editor **6) AI Image·Content Creation Practice** - Quickly generating needed images with prompt design methods - Utilizing Freepik + visual content creation - Practice: Detail page creation and feedback **7) From Zero-Cost Marketing to Paid Advertising** - Zero-cost marketing: Building trust with review-type/experience-type content - Blogs: Combining exposure-focused writing with conversion-oriented structure - Paid ads: Dissecting Naver/Coupang ad structure, ROAS-based operations - Avoiding auto-bidding traps, designing thumbnails/keywords centered on CTR - Practice: Designing ad promotions for your product ## Why It's Efficient This course doesn't just tell you "what to do"— it connects 'product-keyword-category-platform-detail page-marketing-advertising' in a single line, in the order that actually makes money. 2-3 million won courses? There are many good courses. But I'm confident there's no course with this level of quality at this price! The most fatal thing about a 2-hour-a-day side hustle is working hard in the wrong direction. This course is designed to save that time by making you move based on market and customer intent from the start, and structured so that once you build the system, it continues to generate sales.

Have you ever wished you had Iron Man’s perfect assistant, JARVIS, too…?! Create JARVIS for everyone to help you work smarter!

AI is no longer a tool exclusive to developers or experts. The gap between "those who use AI" and "those who don't" is already widening across all roles—from students and job seekers to office workers, planners, and developers. This course is a practical survival guide focused on: ✔️ How to use AI as a tool to explode your productivity, not as a replacement technology ✔️ Prompts you can immediately apply to work, studies, job hunting, planning, and development ✔️ The mindset that turns someone who says "I tried AI, but it wasn't that great" into an AI expert Rather than just explaining features, I will show you: 👉 What kind of people survive in the AI era 👉 Exactly how those people use AI in practice Based on my own experiences and real-world examples.

This course takes you from shaping your experiences or stories into a manuscript to creating an EPUB you can read and review yourself, along with materials for listing your book in international online bookstores. Using examples from published nonfiction books and novels, you’ll learn how to revise AI-generated drafts, translate and localize your work, and check how your EPUB reads. The course consists of 8 lessons totaling about 92 minutes and includes prompts, input templates, and checklists you can use with your own book. You’ll need to prepare an AI agent environment that can work with local files in advance; setting up the environment is not covered. Time for writing, review, and bookstore approval, as well as the cost of paid tools, is not included.

This VOD is designed for current consultants to master, within 2 hours, the entire process of fully utilizing ChatGPT—from “Basic Analysis” → “Idea Generation” → “Report Writing”. From travel itineraries to future business scenarios... This is a practical course that starts with interesting examples and concludes with immediately applicable prompt templates, instilling the conviction not just 'I want to watch it' but 'I must use it'.

If you keep getting errors after asking AI to do it, the problem isn’t the AI—it’s that you lack the foundational knowledge to guide it. In this video, we’ll cover the seven foundational concepts that people who get stuck while vibe coding were missing, and explain what each one is and why it’s necessary. 👾 This is explained for people on day zero of coding who have never opened a terminal before.

It has become easier to write code with AI, but it is still important to understand how the services we build are structured and operate. We need to know the overall flow—how the frontend and server connect, where data is stored, and what to consider as the number of users grows—so we can ask the right questions. I also studied by building up my knowledge one step at a time, starting with the basics. In this course, I first lay out the big picture, then suggest a way to learn by connecting the details to it. “The Age of AI One-Click Coding, a New Direction for Development: The Big Picture of System Design” is the introductory course in the System Design series. Across 74 lessons, we explore a broad range of topics, from the basic structure of services to data, communication, security, deployment, and operations. Familiar examples involving orders and reservations, along with diagrams that build up step by step, help explain why each concept matters. You don’t need to memorize every term or understand how to implement everything from the start. The goal of this course is to help you follow along comfortably, like watching an educational program, and build a big-picture understanding: “So, these are the kinds of problems that come up, and these are some ways to solve them.” Along with the videos, you’ll get an HTML textbook containing detailed explanations, diagrams, and sample code. You can follow the overall flow in the videos and revisit anything you’re curious about in the textbook. Practical implementation and in-depth coverage of specific topics will continue in the follow-up series.

I’ll show you, through an actual work session building a to-do page from scratch, the process of requesting, checking, and revising that I refined after using more than 58.3 billion tokens with Codex. You’ll learn how to ask for the results you want without knowing all the code and how to directly verify the changes.

An introductory course for learners preparing for Japanese university English admissions for the first time. Comprising five theory lessons and seven practical lessons, it covers checking official application guidelines, distinguishing application documents and exams, and reviewing educational sample answers that introduce the CARE framework designed for essay writing alongside AX practice. PDFs for each practical lesson, along with copy-ready prompts and sample materials, are provided.

Stop getting student-record planning. I’ll reveal the entire consulting playbook used by a college admissions consultant with 30 years of experience.

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.

We invite you to become a ‘Top-Tier Enterprise AI Systems Architect’ Do not remain a micro-level technician (Prompt Writer) who merely assembles libraries created by others or polishes prompt sentences. From mathematical first principles to runtime control-loop kernels and autonomous recovery infrastructure — through 40 years of practical engineering insight that has driven industrial operations in South Korea, I will firmly guide you to become a top-level ‘Enterprise AI Systems Architect’ who protects your company’s business and digital sovereignty. Now, begin the great journey of transforming uncontrollable AI into a perfect industrial core. “Why does an AI that ran perfectly in a demo start spouting strange nonsense or bring the pipeline to a halt as soon as it is deployed to production?” “Why do AI projects that so many companies launch with great enthusiasm ultimately fail to escape the ‘PoC (Proof of Concept) swamp’ and get abandoned?” These are the most desperate questions that countless developers and systems architects I have met in the field have asked me. Hello. I am Hongjip Kim, who spent more than 40 years in the powertrain R&D division of the South Korean automotive industry (including 17 years as an executive in Hyundai Motor Group R&D), led the export of engine and drivetrain technologies worth 130 billion won, and commanded operations as the CEO/CTO of a listed mid-sized manufacturing company. From the perspective of an engineer who has spent decades in mechanical engineering and precision-control environments, a ‘risk of fatal uncertainty’ lurks behind today’s frenzy to adopt generative AI. In mission-critical industrial environments where even a mere 0.1% error or mistake can directly result in the destruction of physical equipment worth hundreds of millions of won and an enterprise-wide shutdown, integrating a probabilistic chatbot that simply relies on probability to generate plausible text directly into a service is like carrying a ticking time bomb into a fire. This course was designed to impart the “practical engineering methodology for training uncontrollable probabilistic AI into the most robust industrial control core, one that allows not even 0.000% of syntax errors.” 1. The 3 Major Fatal Bottlenecks You Face in the Field (Problem) Many engineers attempt to challenge production environments using an approach limited to one-off prompt tuning (Vibe Prompting), only to become frustrated when they encounter the following 3 structural defects: Finite Context and ‘Lost in the Middle’: As conversations or multistep executions grow longer, critical system instructions are pushed aside and the context window is exhausted, causing the system to lose its memory and amplifying hallucinations. Nondeterministic Outputs and Cascading Pipeline Collapse: Tiny probabilistic fluctuations, such as one missing closing bracket in JSON or an incorrect type, can paralyze legacy ERP/CRM API calls and destroy data integrity. Untrusted Code Execution and Infrastructure Security Bankruptcy: When scripts autonomously generated by an agent run in a non-isolated host OS environment, they create risks such as kernel escapes and sensitive-data leakage. As such, AI malfunctions in industrial environments are not merely quantitative accuracy problems; they become a massive financial disaster in the form of asymmetric business loss (Asymmetric Business Loss). 2. ‘How’ to Solve These Problems Perfectly (Solution) This course differs fundamentally from commercial courses that teach only how to use fragmented off-the-shelf tools. By combining 40 years of hands-on field expertise with computer systems engineering, it delivers 3 hardcore architectures for vertically integrated, system-level control of probabilistic AI: ① Move Beyond Prompting to ‘LLM-OS & Context Orchestration’ Following Andrej Karpathy’s paradigm, redefine the LLM not as a conversational respondent but as the central computational core (CPU) of a computer. Systematically organize the context window as ultra-low-latency volatile RAM, the internal vector DB as Disk, and external APIs as an I/O bus. Through MemGPT hierarchical virtual-memory paging, preserve critical state without saturation even during infinite conversations, while scaling a dynamic agent network through MCP-based Liquid Swarm MAS, minimizing token costs. ② ‘Deterministic Harness Engineering’ That Constrains Probabilistic Hallucinations to 0.000% Leave the language model’s creative flexibility open only during the Reasoning phase, while firmly confining the physical output layer that interacts with external systems using mathematical Boolean algebra and compilers. Apply EBNF / XGrammar-based CUDA logit masking to forcibly block the generation probability of invalid tokens at P = 0.000%. Form a physical security isolation ring so that code generated by agents runs only once inside a Firecracker MicroVM micro-virtualization sandbox with 5ms snapshot restoration capability. ③ ‘High-Reliability MLOps·LLMOps Autonomous Recovery Infrastructure’ Without Wasting GPU Resources Build vLLM PagedAttention and S-LoRA hot-swapping to suppress idle VRAM waste to below 4%. When a multi-agent API fails, restore data consistency 100% through SagaLLM reverse compensation transactions. Through an OpenTelemetry/Langfuse distributed observability network, defend system availability by executing an unmanned automatic canary rollback whenever a decline in the RAGAS faithfulness score (Data Drift) is detected. 3. Practical Value That Drives Spiral Growth (Pedagogy & ROI) This course is systematically designed according to the 5 levels of Bloom's Taxonomy. Starting from simple theoretical recall (Remember), learners directly code and validate a 5-stage debugging pipeline (analyzing deceptive baseline trap source code ➔ deconstructing adversarial engineering ➔ establishing a Robust integrity pipeline ➔ calculating the TEI ROI formula ➔ SOTIF/ISO 42001 governance). Going beyond the intuitive satisfaction of simply “working well,” I will apply the Forrester TEI (Total Economic Impact) financial model to visualize, from an executive perspective, how much the AI system you build reduces your company’s rework cost (Rework Cost), avoids failure risks worth hundreds of millions of won, and proves an ROI of more than 200%.