Why AI Agents Fail: Practical Adoption Strategies Based on Data, Security, Cost, and Operational Challenges

The “AI Team Members Do It All” online course is a hands-on program where you learn to use AI not simply as an automation tool, but as an “AI team member” that works alongside you in carrying out practical tasks. The course is structured around common real-world workflows, including market research, proposal writing, strategy report creation, brand content visualization, project promotion and operations, and post-project management. Participants assign various AI tools—such as ChatGPT, Perplexity, Copilot, Canva, Gamma, Miricanvas, and Vrew—to roles including planning partner, strategic research partner, design partner, and operations support partner, and use them to complete actual work deliverables. Across 30 sessions, you will learn step by step, from the fundamental mindset for working with AI to practical prompt writing, market research, proposal and report writing, brand content creation, and project operations. By following the course, you can develop the AI collaboration skills needed to work independently like an entire team.

Textbooks teach the modules separately, but the real world is different. An active SAP center director builds a hypothetical dumpling factory from start to finish and shows, through actual implementation project screens, how FI, CO, SD, MM, and PP really connect and work together.

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.

In the era of generative AI, it is difficult to solve practical problems simply by writing prompts. In real-world services, you need to be able to design AI systems that can make decisions autonomously, call tools, retrieve data, and collaborate across multiple agents. This course is a hands-on program for everyone from developers designing AI agents for the first time to engineers seeking to build systems that can be operated in production. You will learn step by step, from designing agent architectures with LangGraph to State Management, Tool Calling, API and MCP integration, natural-language database control, RAG implementation, semantic search, Few-shot Learning, Reflection, and Fine-tuning. You will also learn how to build multi-agent collaboration structures, use the Supervisor pattern and Actor-Critic strategies, implement asynchronous communication, create automated evaluation systems, and establish Quality Gates through real-world projects. Finally, you will learn the MLOps and AI Agent operations strategies required in real production environments, including monitoring based on Metrics, Logs, and Tracing; Shadow Deployment; Canary Deployment; Drift Detection; RCA automation; and A/B testing. By the end of the course, you will be able to directly design, develop, and operate high-performance AI systems that can be applied to real-world services using the latest AI agent technologies.

Instead of using more agents, experience firsthand how to entrust them with greater confidence. With Codex CLI, build your own harness so you can delegate work without worry!

Learn how to create a team of AI Agents with Grokbot that goes beyond simply chatting with AI to perform development, research, design, and operations tasks on your behalf. Build everything hands-on—from Agent design to Prompts/Rules, browser, terminal, and tool usage, Multi-Agent collaboration, Memory, Skills, Routines, cost optimization, and failure recovery—and ultimately complete a 24/7 AI Company system that performs repetitive tasks without requiring constant human instructions.

From a single email to proposals and presentation materials—complete an entire work cycle with Claude Code.

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.

From the solid foundational theories of contract law to practical drafting guides and advanced review techniques using generative AI, this course covers it all in one place. Beyond simply learning how to use AI, it helps you become a 'smart contract expert' capable of independently identifying and managing legal risks.

Are you losing time to these recurring weekly tasks—organizing meeting minutes, writing reports, and compiling materials? This course does not simply list how to use Gemini. Instead, you will work through the practical task of “introducing a new AI tool to our team” from start to finish: researching with Deep Research → understanding with NotebookLM → sharing with Canvas → managing with Sheets → automating with Workspace Studio → and turning decision-making criteria into reusable assets with Gems. This is not a lecture; it is a workshop. You need to pause the videos and follow along hands-on. By the end, you will have learned more than how to use these tools—you will have developed a new way of working in which AI creates the drafts and you make the decisions.

Simple tutorials alone make it difficult to apply in practice. I will clearly pass on my professional know-how, covering complex state management and multi-agent design methods.

Can you create a service with your ideas even if you don't know how to code? With AI, it is possible! In this course, you will experience the entire process of turning an idea into a real web service using "Vibe Coding" tools used in the industry, such as Gemini, Lovable, Antigravity, Cursor, and Claude Code. You won't just learn how to use the tools; you will master a new way of service development in the AI era—from planning and deploying to integrating payments. Point 1. Master 5 Core Vibe Coding Tools - Hands-on practice with core features and applications of Gemini, Lovable, Antigravity, Cursor, and Claude Code - Understanding the Vibe Coding development method of collaborating with AI Point 2. Building a Real Service Without Coding - Hands-on process of planning and implementing a book recommendation web service - Understanding the entire service creation flow: Idea → Development → Deployment Point 3. Practical Skills for Service Launch and Operation - Understanding domain purchase, server setup, and the deployment process - Learning core operational technologies such as payment module integration and SEO settings

Solve the point where 80% get stuck at makeathons. Complete Raspberry Pi · Computer Vision · LLM · 3D Design in 4 weeks! Achieve top rankings at makeathons with a demonstrable smart mirror PoC!

: "From Mathematical Foundations to the Latest Models, Completing the Deep Learning Pipeline with PyTorch (44 Lectures in Total)" The era of simply learning how to call model.fit() is over. From the very basics of artificial neural networks—differentiation and gradient descent—to essential PyTorch techniques used in the industry, and CNN/RNN for handling image and time-series data! We will help you systematically master the entire process of deep learning. Go beyond analyzed data and step into the amazing world of deep learning, where artificial intelligence mimicking the human brain learns and makes decisions on its own.

The rules of every game are changing — a new dimension of business opened by quantum computing. Moving beyond simple technological advancement, quantum computing has already emerged as a key variable determining the future business landscape, poised to shift paradigms across all industries. This analysis provides insightful perspectives on the massive wave of technological change, covering everything from the basic principles of quantum computers to innovation cases in finance, pharmaceuticals, security, and the strategic moves of global Big Tech. It offers the most definitive roadmap for professionals who wish to gain quantum literacy without complex physics knowledge and transform into future-ready talent.

Reading the Standard of Digital Money — A New Financial Order Opened by Stablecoins In the uncertain digital asset market, stablecoins—the only assets that function "like real money"—have already emerged as a core part of the global financial infrastructure. This provides essential, condensed knowledge for professionals who want to be at the forefront of understanding the paradigm shift in the digital economy.

We provide a comprehensive guide to understanding information security and privacy issues that may arise when using generative AI, and to establishing a secure AI usage framework based on the AI Basic Act and the latest security strategies.

It is difficult to complete a classification service using only AI API calls. Based on practical experience, I guide you through everything from implementation to deployment.

Customer analysis completed with Excel and Orange, from cross-selling to A/B testing and churn risk management all at once

We help marketing practitioners solve the "having data but being unable to reach a conclusion" problem through a practical routine—spanning problem definition, analysis, interpretation, and one-page reporting—combined with the use of ChatGPT.