Most design tools trap you in their workflow. You drag pre-built components around, but you can't really change how they work. When the AI generates something, you're stuck with whatever structure it decided on.
Prototyper takes a different approach. Its composable architecture means every piece of a design is an independent building block. The AI doesn't generate monolithic screens—it assembles atomic components that you can rearrange, swap, and customize. This matters because it gives you actual control over the output.
Here's how this architecture works in practice and why it changes what's possible with AI-powered design.
What composable architecture actually means
"Composable" isn't a buzzword here. It describes a specific design philosophy: build complex things from simple, independent parts.
Think about how you might build a house. One approach is prefabricated construction—you get pre-designed rooms that snap together in limited ways. Another approach is having individual bricks, beams, and panels that you can combine however you want.
Prototyper works like the second approach. Instead of generating complete pages as single units, it works with atomic primitives: buttons, inputs, cards, containers, typography blocks. Each primitive is self-contained. It doesn't depend on what's around it. You can move it, duplicate it, or delete it without breaking anything else.
This granularity is the foundation everything else builds on.
The three layers of composable architecture
Prototyper's architecture has three distinct layers, each with a different level of abstraction.
Primitives
At the base layer, you have primitives. These are the smallest building blocks: a button, a text label, an input field, a divider line. Primitives have properties you can adjust—colors, sizes, spacing—but they do one thing and do it well.
When the AI generates a design, it's actually composing primitives according to patterns it learned from thousands of real interfaces. You see a login form, but under the hood it's a vertical stack containing a heading primitive, two input primitives, and a button primitive.
Components
The middle layer groups primitives into reusable components. A navigation bar is a component. A pricing card is a component. A testimonial block is a component.
Components encode design decisions. A pricing card isn't just "some primitives arranged in a rectangle"—it's a specific arrangement with intentional hierarchy, spacing ratios, and interactive states.
When you ask Prototyper for a pricing section, it generates components that follow established patterns. But because those components are still made of primitives, you can crack them open and adjust the internals.
Layouts
The top layer handles how components arrange on a page. Layouts define the grid, the sections, the responsive behavior. A landing page layout might specify: hero section spanning full width, followed by a three-column features grid, followed by a centered testimonials carousel.
Layouts provide structure without being rigid. You can swap components in and out of layout slots. You can change a two-column section to three columns. The layout adapts.
Why this matters for AI-generated design
Here's where the architecture pays off. Because everything is composable, the AI can generate designs that are actually editable.
Compare this to image-generation AI. When DALL-E creates a picture, you get pixels. Want to move the chair? Generate a new image. Want to change the lighting? Generate a new image. The output is flat and final.
Prototyper generates structure, not images. When it creates a dashboard, you get a layout containing components containing primitives. Want to move a chart? Drag it. Want to change a button color? Click it and adjust. Want to swap a bar chart for a line chart? Replace the component.
This is the difference between AI as a one-shot generator and AI as a starting point for iteration.
Atomic design in practice
The composable architecture approach aligns with a methodology called atomic design, which has been standard in frontend development for years. Prototyper applies this same composable thinking to AI-generated interfaces.
In atomic design terminology:
- Atoms are the primitives (button, input, label)
- Molecules are simple component groups (search bar = input + button)
- Organisms are complex components (header = logo + nav + search bar + user menu)
- Templates are page-level layouts
- Pages are templates filled with real content
When you understand this hierarchy, you can communicate more precisely with Prototyper's AI. Instead of asking for "a page," you can ask for specific organisms or molecules. The more precisely you specify the level of abstraction, the more useful the output.
How composable architecture enables code export
Composable architecture isn't just a design concept in Prototyper—it extends to the code export.
When you export a design to React + Tailwind, you don't get a single massive file with everything hardcoded. You get a component structure that mirrors the design hierarchy. Each component is its own unit. Props flow down. Styles are scoped.
This means the exported code is actually usable in a real project. You can import individual components into your codebase. You can modify them without touching unrelated code. You can add business logic and state management in the places where they belong.
The alternative—a single generated file with thousands of lines of coupled code—would be technically accurate but practically useless. Composability keeps the output maintainable.
Emergent features from composition
Something interesting happens when you combine granular primitives with AI that can compose them: features emerge without being explicitly built.
Say you want a settings page with expandable sections. Prototyper doesn't need a specific "expandable settings section" feature. It can compose an accordion component with form primitives inside each panel. The capability emerges from combining existing building blocks.
This is powerful because it means Prototyper can handle requests it wasn't specifically designed for. As long as the request can be expressed as a composition of primitives and patterns, the AI can attempt it.
Users discover what's possible by trying things. Composable architecture makes experimentation cheap. Ask for something unusual. If it works, you've found a new use case. If it doesn't, you've lost thirty seconds.
Working with composable architecture
Understanding how composable architecture works changes how you use Prototyper.
Start broad, then refine
Generate at the layout level first. Get the overall page structure right before worrying about individual components. Once the skeleton is solid, drill into specific sections and adjust component-level details.
Name the level you want
Be explicit about whether you're asking for a primitive, component, or layout. "Design a button" is different from "design a pricing card" is different from "design a pricing page." The AI generates at the level you specify.
Compose manually when needed
Sometimes the fastest path is manual composition. Generate a few components separately, then arrange them yourself. The AI is good at component-level design. Your eye might be better at page-level arrangement.
Keep components independent
When customizing, preserve the independence of components. Avoid edits that create dependencies between unrelated parts. If component A's styling starts depending on component B's position, you've introduced coupling that will bite you later.
The trade-off
Composable architecture has one meaningful downside: it requires the AI to work within constraints.
A pure image-generation model can create anything. It doesn't care about semantic structure. Prototyper's AI has to generate valid compositions—arrangements that actually make sense as component hierarchies.
This constraint means some highly custom, unconventional layouts are harder to generate. If you want something that breaks standard component patterns, you'll need to do more manual work.
For most use cases, the trade-off is worth it. The ability to edit and export generated designs outweighs the occasional limitation on pure creative freedom.
Why composable architecture matters for your workflow
Prototyper's composable architecture is what makes it a practical tool rather than a novelty. The AI generates structured output. That structure is editable because it's made of independent parts. The code export is usable because it preserves component boundaries.
When you work with Prototyper, you're not just generating designs. You're generating starting points that fit into a real development workflow. The composable architecture is what makes that possible.
Understand the three layers (primitives, components, layouts). Communicate at the right level of abstraction. Let the AI handle composition, then refine with manual adjustments. That's how you get the most from composable architecture.
Once you grasp how composable architecture works, you'll approach AI design tools differently. You'll think in terms of building blocks instead of finished pages. You'll iterate faster because you can swap pieces without starting over. And you'll get exported code that actually works in production.