Design × Code Lab: A Frontend Handbook for Designers

Design × Code Lab is a code literacy site made for designers. It explains frontend concepts with the language designers already understand: layers, frames, auto layout, variants, tokens, components, and interaction states.

The idea came from a recurring question: why does AI sometimes fail to reproduce a Figma design accurately? A frontend engineer can quickly understand that Figma layers, frames, and auto layout become HTML tags, CSS styles, and the box model in code. For many designers, that mapping is still abstract.

Designers know the interface, the design file, and the requirement best. With a little frontend foundation, they can communicate with AI much more clearly.

Learning Code Through Visual Examples

Code can feel dry, so the site uses analogies, visual demos, animation, quizzes, and hands-on interactions wherever possible.

• HTML nesting is explained through Figma layer structure.
• CSS layout is compared with Auto Layout.
• Frontend state is connected to component variants.
• Tokens are explained as design variables used by code and AI.

Many concepts are hard to understand from definitions alone. They become much clearer when designers can drag, click, and see how the result changes.

A Roadmap from Interface to Launch

The site follows a roadmap from breaking down a UI to publishing it online. It starts with concepts designers run into most often, then gradually moves toward deeper topics.

• HTML, CSS, and JavaScript: structure, styling, and interaction.
• DOM and the box model: how browsers organize a page and why size, spacing, borders, padding, and margin affect fidelity.
• Layout and responsive design: why one design changes across screens, containers, and code environments.
• Tokens and design variables: how color, typography, radius, and spacing become rules AI and code can reuse.
• Components and state: how buttons, forms, and dialogs contain logic as well as visual style.
• Frontend, backend, APIs, and databases: where page data comes from and why fields, permissions, and interfaces affect design.
• npm, localhost, GitHub, Vercel, DNS, and HTTPS: how a webpage moves from local preview to online access.
• Figma MCP, Figma Skills, and Agents: how AI reads design files, uses component rules, and participates in design-to-code workflows.

More chapters are still on the way, including performance, AI models, and dynamic data. If you are using AI to build interfaces or want to build frontend intuition, this site is for you.