Lunagraph

What is Lunagraph?

Lunagraph is a design canvas for creating user interfaces using real HTML, CSS, and React code. The core purpose is to help teams design and implement UI in a way that keeps the design and the shipped code aligned, reducing “hand off” gaps.

Instead of treating the design as a separate deliverable that someone else must translate into components, Lunagraph positions the deliverable as the code itself, with AI assistance provided by Claude Code.

Key Features

• Design directly into real code (HTML, CSS, React): Your canvas work is reflected in actual markup and components, so the output corresponds to what will run.
• Zero handoff workflow for UI teams: The platform is designed to support consistency across designers, product, developers, and agents without requiring a translation step from design to implementation.
• Claude Code-powered context aware assistance: The AI partner is described as able to work with the full picture, including the canvas and existing codebase.
• Canvas + chat + local repo round trip: The chat can access your canvas and your local codebase, and the workflow includes implementing changes directly into a repository and previewing results.
• Live preview and screenshot comparison: The described workflow previews in a live iframe and uses screenshots from both the design and the output to compare.
• In-repo component updates from design changes: Examples shown include generating components such as PricingCard and updating files like a feature comparison table component.

How to Use Lunagraph

1. Start from a design canvas: Begin designing UI elements on the canvas.
2. Use the integrated chat for implementation help: Ask for changes in a way that references the canvas and your repository context.
3. Let the AI implement into your repo: The workflow described includes writing directly into your local codebase.
4. Preview and verify: Use the live iframe preview and screenshot both the canvas/design and the resulting UI output for comparison.
5. Iterate on components: Apply further updates by requesting refactors or feature adjustments (for example, splitting a sidebar into smaller components).

Use Cases

• Designer-to-implementation UI creation: A designer creates UI layouts on the canvas and ensures the resulting code uses real HTML/CSS/React rather than a separate design file.
• Team workflow without handoff friction: A mixed team (design, product, development, and agents) works in the same workflow so fewer translation steps are needed between roles.
• Refactoring complex components with AI assistance: When a component becomes too complex (e.g., a sidebar), the chat can help restructure it into smaller components and add behavior such as a collapse toggle.
• Updating existing pages from design intent: Use a screenshot or palette reference to update UI sections so the produced output matches an expected layout and styling.
• Build pricing/feature UI from canvas designs: Generate components for pricing cards and feature tables, then wire them into page layouts and update existing table markup.

FAQ

• What code does Lunagraph generate or work with? Lunagraph is described as generating and working with real HTML, CSS, and React code.

• Does Lunagraph rely on a separate design file handoff? The website emphasizes a “zero handoff” workflow, where the deliverable is the code itself rather than a design file that must be translated.

• What does “powered by Claude Code” mean in this workflow? The content states that Claude Code acts as a creative design partner that considers the canvas and the local codebase, supporting implementation tasks through chat.

• How do users verify that the design matches the output? The described workflow includes previewing in a live iframe and screenshotting the canvas and the rendered result for comparison.

• Can the AI read from and write to a local repository? The page includes an example showing “AI File Access” with filesystem paths for reading/writing outside the project, suggesting local repo integration, but details beyond that are not provided.

Alternatives

• General-purpose design tools (Figma-style) + separate developer implementation: This keeps design and code in different tools and workflows, requiring translation from design files into components.
• Code-first UI builders (React component editors) without a design canvas: These focus on building directly in UI code, but may not provide a canvas designed to capture and communicate design intent in the same way.
• AI coding assistants integrated into an IDE: These can help generate or refactor code, but typically don’t combine a design canvas, live iframe preview comparison, and the “canvas + chat + repo” loop as described here.
• UI prototyping tools that export components or styles: These aim to bridge design and implementation, but the approach may still involve exporting or converting rather than producing code as the primary deliverable.