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A to Z of Using AI-Readable Figma for Designers and Front-End Developers

We’ll cover the entire product-building process from A to Z, starting with Figma fundamentals and moving on to building and utilizing an AI-readable design system that can accelerate the design and development process with AI.

3 learners are taking this course

Level Intermediate

Course period Unlimited

Figma
Figma
Design System
Design System
AI
AI
collaboration
collaboration
product design
product design
Figma
Figma
Design System
Design System
AI
AI
collaboration
collaboration
product design
product design

What you will gain after the course

  • You can design the naming, hierarchy, auto layout, tokens, and documentation rules of a Figma design system that AI and developers can interpret accurately.

  • You can analyze GitHub Primer and shadcn/ui in Figma and establish criteria for applying them to our team’s design system.

  • You can diagnose AI-generated screens and code, and correct recurring errors with Agent skills and checklists.

  • You can connect Notion, FigJam Agent, Figma Make, and Figma Design to run a mini sprint from planning through screen implementation.

  • You can connect the design system to a code generation tool and review the output using Dev Mode and MCP.

  • You can establish a collaborative process where designers and frontend developers share tokens, components, and handoff standards.

Why AI-Generated Screens Don’t Feel Like “Ours”

In the age of generative AI, a single prompt is all it takes to produce a rough screen draft.

But when you look under the hood, button heights are inconsistent, colors ignore the tokens, and developers ask, "What component is this?" Run the same command five times, and you get five different results.

The problem isn’t AI’s capability. The problem is a design system that AI can’t read.

Even a system that looks well-organized to people becomes a guessing game for AI every time if the structure of its data itself is unreadable to machines. The same goes for developers.

This course covers how to rebuild that system so that AI can read it. It’s not about creating a new one, but about fixing an existing system.


This course is for both professions.

A design system should not be something designers create and developers consume; it should be something both roles read and write using the same rules.

If you are a working designer or student, you have created or are currently managing a design system and want to structurally solve why AI-generated results are disconnected from the system.

If you are a frontend developer, you may find yourself repeatedly asking questions during the collaboration process of converting Figma files handed over by designers into code because the tokens and naming don't match.

If you are a solo creator, you want to handle planning, design, and development on your own while connecting AI agents to your actual workflow to work faster.


About this course


1. Do It by Hand First, Then Turn to AI

Only someone who has created an AI-generated result themselves can judge whether it is good or bad.
That’s why each exercise in this course follows a set sequence. After creating a button component yourself, you ask AI to create a component set; after working with modes directly using Variables, you have AI handle the dark theme.

In this course, we’ll cover Figma fundamentals and how to use AI at the same time.


2. Experience firsthand why the results are different every time

If you give AI the same instruction 10 times, the result will be different every time.
Identifying why this variation occurs and where it primarily arises is the starting point for transitioning to AI. Only after pinpointing the causes yourself can you understand what “AI Readable” means.


3. Learn how to make decisions rather than how to create.

This course covers methods for continuously advancing design systems and screen designs in the product design field.

Create a diagnostic checklist, register the validation loop as a skill and run it, then execute the same command five times to measure variance. The areas with the greatest variance are the gaps in my system. Fill those gaps and run it again.

The checklist continues to evolve through each sprint. By the end of the course, you’ll have a diagnostic tool you can use directly with the system you built.


4. The Moment a Design System Becomes Code

Create a handoff structure in Dev Mode, then use Dev Mode MCP to let AI read the Figma file directly.

Visually compare how tokens with Code syntax embedded in them produce different code from those without it. This is the point where you confirm that AI actually reads the rules you’ve defined.

We’ll also briefly explore Code Connect, which real-world enterprise teams use for handoffs.


5. In the final part, we’ll simulate how various AI tools are used in real-world work.

Section 6 is a mini sprint. We’ll bring a GitHub open-source project into Figma, plan it with FigJam Agent, create screens using a design system, generate a prototype with Figma Make, and write the handoff to turn it into code.

Rather than learning individual features, you’ll directly experience how an AI organization actually works in the final section.



After completing the course

  • You can evaluate your team’s design system using a diagnostic checklist and prioritize what to fix first.

  • You can design a token structure from Foundation to Component based on principles and build it with agents.

  • You can measure variations in AI outputs, trace their causes back to system deficiencies, and strengthen the rules.

  • You can lead the handoff from design to code using Dev Mode and MCP.

  • You can complete the entire workflow—from planning to prototyping to coding—in one continuous process.

  • Even after the course ends, you’ll develop a routine for continuing to learn independently.


This is how it works.

Missions
There is a mission every 4–5 lessons. By leaving your results or thoughts in the comments, you can exchange feedback with other students doing the same exercises. The missions focus on topics without a single correct answer, such as naming conventions, and topics about sharing failures, such as where AI went wrong.

Practice materials
are provided through a Notion workspace and GitHub repository. Every exercise includes a starter file, so you can pick up where you left off even if you fall behind.

Provided Materials
AI Readable diagnostic checklist, practice design system files, and a self-study routine tracker

Community
You can ask questions and share your work in the Naver Café and open chat.


Please check before taking the course

Prerequisite knowledge

  • Experience creating frames, auto layouts, and components directly in Figma.
    You can learn the basics in Section 1, but depending on your familiarity with Figma, it may not be sufficient to learn the fundamentals through this course.

  • You don’t need to write the code yourself. AI handles the code conversion, and we read and evaluate it.

Learning environment

  • A paid Figma account with a Full seat on the Professional or Edu plan or higher is required.

  • Features exclusive to the Enterprise plan (Organization or higher) will be covered through instructor demonstrations only.

  • GitHub account (free), Notion account (free plan)

  • AI coding tools such as Claude (Sections 5–6 hands-on practice)

  • Desktop environment (Windows / macOS)

A Figma account is required. For other prerequisites, please first review the publicly available preparation guide.


Who created it?

Dangoon Soft is an official Figma channel partner that has supported the adoption of Figma, Figma onboarding, and design system consulting for corporate design and development teams.

The manager leading the course, Juhan Lee, works as a UX/UI design advocate at Dangunsoft.
Having repeatedly encountered situations in the field where designers and developers interpreted the same design system differently, he incorporated the solution into the structure and exercises of this course.

Recommended for
these people

Who is this course right for?

  • A designer with 3+ years of experience who operates a design system and wants to improve the quality and consistency of AI-generated outputs

  • A frontend developer who repeatedly fixes inconsistencies in tokens, components, and naming when translating Figma files into code

  • Intermediate learners who want to go beyond the basics of Figma, analyze open-source design systems, and improve them to a professional standard

  • Designers and developers who want to connect Figma Make, FigJam Agent, and Dev Mode MCP to real projects to boost productivity

  • A solo creator who handles planning, design, and development independently while building an AI-powered design system and code conversion workflow

Need to know before starting?

  • Someone with a basic understanding of Figma (Section 1 is a warm-up to help you follow along with the exercises and is not structured in as much detail as an introductory fundamentals course.)

  • Someone with basic knowledge of AI tools

  • During the class, we will use paid ChatGPT and Figma accounts.

Hello
This is tgedu

Hello, this is Dangun Soft.

Dangoonsoft has been a software solutions partner working alongside Korean IT companies since 2002.

From consulting on which tools customers need, to solution implementation and technical support, and even B2B training that enables the entire organization to use them in practice, we work with customers on everything related to software.

We work with software across nearly every field, including Figma, ProtoPie, JetBrains, GitHub, Microsoft, Adobe, Autodesk, and Docker. Rather than specializing in just a select few products, we have designed the right combinations for companies’ entire work environments. Recognized by each developer as a top-tier partner, we are now taking the leap toward becoming a global company through our APAC distribution business.

After providing solutions to and communicating with most major Korean enterprises, we now aim to share with more people the recurring challenges and solutions we encountered in the field.

Tangunsoft Official YouTube: https://www.youtube.com/@tangunsoft
Tangunsoft Official Instagram: https://www.instagram.com/tangunsoft/
Tangunsoft Official LinkedIn: https://www.linkedin.com/company/tangunsoft/posts/?feedView=all

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