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(For Product Managers) Service Design for LLM Applications

You can learn the concepts and methods of 'service design' needed when planning applications or web services built on LLM, a type of generative artificial intelligence (generative AI).

(5.0) 1 reviews

20 learners

  • arigaram
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LLM
Generative AI

What you will gain after the course

  • Service design process (customer journey map, touchpoint analysis, etc.)

  • The Positive Impact of LLMs on Service UX/UI Design

🧭Important Notes

The course is currently being completed. Please note that you may need to wait a considerable time until the course is fully finished (though updates will be added regularly). Please consider this when making your purchase decision.

📋Change History

  • November 20, 2025

    • I've started a complete revision and reinforcement effort. I also plan to re-record the existing lectures.

    • I've released the individual lesson table of contents for Sections 5 through 15.

  • October 6, 2025

    • I have significantly expanded the existing table of contents. I added 3 lesson topics to each of the existing sections 1-4, and added new sections 5-15. Each additional section includes lesson topics. I plan to supplement the content based on these topics, but I haven't set a schedule for the supplementation yet.




🎓 LLM-Based Service Design Master Class

― "The Power of Designing Truly User-Centered Services in the AI Era" ―

💡 Course Overview

As AI technology rapidly advances, Service Design is no longer the exclusive domain of design majors. We are now in an era where planners, designers, developers, and marketers must all design service experiences together with AI.

This course comprehensively covers Large Language Models (LLM) and service design,
teaching you step-by-step how to realize "user-centered innovation" rather than "technology-centered automation." You will learn how to plan services utilizing LLM and AI Experience (AX) technologies.

In particular, the course covers the entire process from design thinking methodology, prompt engineering, conversational UX design, AI ethics, to hands-on service prototyping practice, structured to enable students to independently design and implement LLM-based services.

🎯 Learning Objectives

Through this course, you will systematically acquire the following competencies.

  1. Understanding the Convergence of Service Design and LLM

    • # The Impact of LLM Technology on User Experience Design and Learning the Synergy Structure

  2. Strengthening Problem-Solving Skills Based on Design Thinking

    • Empathy→Define→Ideation→Prototyping→Test Apply the entire process centered around LLM

  3. Prompt Engineering and Conversational UX Design Skills

    • Design scenarios for chatbot, content generation, and customer service at actual service level

  4. Strengthening Awareness of AI Ethics, Law, and Governance

    • Learn essential transparency, fairness, and privacy protection strategies in public and commercial services

  5. Developing Business Modeling and Operations Design Capabilities

    • # Sustainable Revenue Structure and Operational Metrics Design for AI Services

  6. Securing Capability to Execute Pipeline Design Projects

    • Duolingo, Copy.ai, customer support automation, local government chatbots, and other hands-on projects you'll complete yourself

🧱 Course Structure and Key Sections

Chapters 1-4: Understanding Service Design Fundamentals and LLM Integration Points
  • # Service Design Overview, Necessity, and Impact of LLM

  • User-Centered Design Principles and Collaboration Structure

  • User Requirements Analysis and Core UX Elements

  • Hands-on Practice Guide (Individual-based Practice), Latest AI Service Trend Analysis

Chapter 5: Design Thinking Process and LLM Integration
  • Empathy→Define→Ideation→Prototype→Test: Hands-on Practice of the Entire Process

  • # Idea Expansion and User Persona Generation Using LLM

  • # Personal Practice Challenge (LLM-Based Idea Generation)

Chapter 6: Conversation Design & Prompt Engineering
  • Interactive UX Structure, Prompt Patterns, and Multi-turn Conversation Design

  • Constraint-Based Prompt Writing, Memory & Session Design

  • Practice: Designing and Testing Your Own Prompt Scenario

Chapter 7: Prototyping & User Testing
  • Guidance on rapid prototype creation using tools like Figma, Chatbase, and no-code platforms

  • # User Testing Planning, Feedback Loop Design

  • # Improving LLM Response Quality and UX Practice

Chapter 8: AI Ethics, Law, and Governance
  • Learning the Principles of Fairness, Transparency, and Accountability

  • Personal Information Protection, Copyright, Data Governance

  • Social Responsibility and Risk Response Strategies for AI Services

Chapters 9-10: Operations, Infrastructure, and Integration
  • # Operating, Monitoring, and Metrics Design for LLM Services

  • # Version Control and Model Evaluation from an MLOps Perspective

  • No-code/Low-code Tool Integration, API Integration Practice

Chapter 11: Business Models and Practical Case Studies
  • # Revenue Structure Design for LLM Services

  • Analysis of Success and Failure Cases (Education, Content, and Customer Support Fields)

  • Personal Business Canvas Practice

🧠 Capstone Design Projects

The highlight of this course is analyzing real successful LLM service cases
and based on this, a hands-on project where you directly design similar services.

Section 12. Duolingo Style — Designing an AI Language Learning Tutor
  • Learning Scenario and Feedback Design

  • Interactive Learning UX Design and Demonstration Prototype Development

Section 13. Copy.ai Style — Designing a Content Generation Assistant
  • # Style Transformation and Template-Based Content Generation Prompt Design ## Overview This guide covers designing prompts for style transformation and template-based content generation, enabling AI to adapt content tone, format, and structure while maintaining core meaning. ## Style Transformation Prompts ### Basic Style Transformation Structure ``` You are an expert content stylist specializing in adapting text to different tones and audiences. Source Style: [Current style] Target Style: [Desired style] Audience: [Target audience] Transformation Guidelines: 1. Maintain core message and key information 2. Adapt vocabulary to target audience

  • # Quality Evaluation and A/B Test Design

Section 14. Customer Support Automation + Human-in-the-loop
  • Automatic Response and Human-in-the-Loop Design

  • # Optimization Strategy Based on Operating Costs and Quality Metrics

Section 15. Chatbot Service for Local Governments
  • Design of LLM Chatbot for Public Civil Service Response and Policy Guidance

  • Prototyping Public Services with Transparency, Accessibility, and Reliability in Mind

🏆 Expected Benefits

After completing the course, you will achieve the following practical outcomes.

  • Securing Service Planning and Design Capabilities in the AI Era

  • Improving the Ability to Design Customized User Experiences Using LLM

  • Understanding AI Ethics and Data Governance

  • From prototype creation to operation and evaluation: End-to-End practical experience

  • Duolingo, Copy.ai, local government chatbots, and other practical portfolio projects completed

🎓 Target Audience

  • # LLM-Powered Service Planner·UX Designer·PM

  • AI startup founders and product managers seeking to understand and commercialize AI technology

  • Customer service, marketing, and content automation practitioners and leaders

  • For those interested in public service innovation, AI governance design, and AI-based customer experience improvement

📢 Closing Remarks

This course is not simply about "how to use" LLMs, but a practical program where you learn how to design new service experiences through LLMs. Not an era where "AI replaces humans," but an era where we "design better experiences together with AI" — stand at the center of that transformation.

Recommended for
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Who is this course right for?

  • Service Planner and Designer

  • Marketing and Customer Management Manager

  • Startup and IT Service Developer

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Curriculum

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120 lectures ∙ (7hr 25min)

Course Materials:

Lecture resources
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5.0

1 reviews

  • jjhgwx님의 프로필 이미지
    jjhgwx

    Reviews 609

    Average Rating 4.9

    5

    19% enrolled

    Thank you for the great lecture!

    • arigaram
      Instructor

      Thank you. I will steadily supplement the content.

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