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(For Planners) Service Design for LLM Applications

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

(5.0) 1 reviews

19 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.)

  • Positive impact of LLM on service UX/UI design

🧭Precautions

I am currently in the process of completing this course. I plan to gradually adjust the price as I complete the course. Therefore, those who purchase earlier can buy it at a relatively lower price, but have the disadvantage of having to wait longer until the course is fully completed (although I will continuously add supplementary content). Please consider this when making your purchase decision.

📋Change History

  • November 20, 2025

    • I have started comprehensive revision and enhancement work. I also plan to re-record the existing lectures.

    • We have released the individual lesson outlines for Sections 5 through 15.

  • October 6, 2025

    • I have significantly enhanced the existing table of contents. I added 3 lesson topics each to 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 work together with AI to design service experiences.

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

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

🎯 Learning Objectives

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

  1. Understanding the Convergence of Service Design and LLM

    • Learning the impact and synergy structure of LLM technology on user experience design

  2. Enhancing Problem-Solving Skills Based on Design Thinking

    • Empathy→Definition→Ideation→Prototyping→Testing: Applying the entire process with LLM at the center

  3. Prompt engineering and conversational UX design capabilities

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

  4. Strengthening AI Ethics, Legal, and Governance Awareness

    • Learning 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 Project Execution Capabilities for Audience Seating Design

    • Complete hands-on projects like Duolingo, Copy.ai, customer support automation, and local government chatbots

🧱 Course Structure and Key Sections

Chapters 1-4: Understanding Service Design Fundamentals and LLM Integration Points
  • Service Design Overview, Necessity, and the 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 full process practice

  • LLM-Based Idea Expansion and User Persona Generation

  • Personal Practice Challenge (LLM-based Idea Generation)

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

  • Constraint-based prompt writing, memory and session design

  • Practice: Designing and Testing Your Own Prompt Scenarios

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

  • User testing planning, feedback loop design

  • LLM Response Quality Improvement and UX Enhancement Practice

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

  • Personal information protection, copyright, data governance

  • AI Services' Social Responsibility and Risk Response Strategies

Chapters 9-10: Operations, Infrastructure, Integration
  • LLM Service Operations, Monitoring, and Metrics Design

  • MLOps Perspective on Version Control and Model Evaluation

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

Chapter 11: Business Models and Practical Case Studies
  • LLM Service Revenue Structure Design

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

  • Personal Business Canvas Practice

🧠 Capstone Design Projects

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

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

  • Interactive Learning UX Design and Demonstration Prototype Development

Section 13. Copy.ai Style — Content Generation Assistant Design
  • Style transformation, template-based content generation prompt design

  • Quality Assessment and A/B Test Design

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

  • Operation Cost and Quality Metrics-Based Optimization Strategy

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

  • Creating public service prototypes considering transparency, accessibility, and reliability

🏆 Expected Benefits

After taking the course, you will achieve the following practical results.

  • Securing Service Planning and Design Capabilities in the AI Era

  • Improving Personalized User Experience Design Capabilities Using LLM

  • Understanding AI Ethics and Data Governance

  • End-to-End practical experience from prototype development to operation and evaluation

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

🎓 Target Audience

  • LLM-powered Service Planner·UX Designer·PM

  • Startup founders and planners who want to understand AI technology and turn it into services

  • Practitioners and leaders in customer service, marketing, and content automation

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

📢 In Closing

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

Recommended for
these people

Who is this course right for?

  • Service Planner and Designer

  • Marketing and Customer Management Specialist

  • Startup and IT Service Developer

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Curriculum

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114 lectures ∙ (5hr 38min)

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5.0

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    jjhgwx

    Reviews 609

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    Average Rating 4.9

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    19% enrolled

    良い講矩をありがずうございたす

    • arigaram
      Instructor

      ありがずうございたす。継続的に内容を補充しおいきたす。

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