You’ve probably tried one of the Figma-to-code tools that promise to turn your designs into working React or HTML with a single click. They seem like the perfect shortcut, offering a way to skip repetitive layout work and move directly from design to product.But speed often comes at the cost of structure. The exported code looks correct in a preview, yet beneath the surface, it’s static, repetitive and hard to maintain. Styles are hard-coded, components are flattened into generic tags and nothing connects back to your design system. The result is code that looks right but can’t adapt, scale or be reused by your team.Let’s explore why that happens and how to fix it. You’ll see what Figma-to-code tools actually generate, why their output isn’t fit for production and how a composable architecture helps you turn design exports into modular, production-ready components.What Figma-to-Code Tools GenerateThe main problem with Figma-to-code tools is that they copy the visual layout of a design rather than its underlying structure. They treat every element as a unique shape instead of recognizing patterns or reusable components.To see how most Figma-to-code tools behave in practice, start with a simple dashboard design from the Figma Community, such as this minimal finance dashboard. Export it to code using any popular Figma-to-code plugin that claims to generate responsive code.Within seconds, you’ll get a working preview that looks impressive. The layout is aligned, text is rendered neatly and the buttons appear to respond to interaction.Generated preview of the minimal dashboard design.But upon inspecting the generated code, the limitations become obvious. The layout isn’t responsive and elements that should be interactive, such as buttons or pagination, are rendered as generic elements.For example, it generated: New deposit Instead of something closer to: New depositEven Figma components that appear interactive, such as selects or pagination controls, contain no logic. They’re styled placeholders with no behavior or state management.This highlights a deeper issue of these tools replicating more of the appearance than the architecture. They can reproduce the surface of a UI, but they don’t capture its composition, behavior or intent.Why Figma-Generated Code Fails in ProductionBeyond structure and responsiveness, generated code also fails in ways that make collaboration and long-term use difficult. They include:It’s Not Connected to Your Design SystemDesign systems exist to enforce consistency. They give you tokens for spacing, typography and color and they define reusable components like buttons, cards and modals. Figma-to-code tools ignore all of this. In the exported dashboard, none of the styles were linked to design tokens or system variables. The “New deposit” button, for example, wasn’t mapped to any existing component; instead, it was rebuilt from scratch. Over time, this approach can create a shadow system of mismatched components that drift away from your actual design system.No Version TrackingWhen you export code from a Figma-to-code plugin, it comes out as a single file dump. There is no history of how the design evolved or who changed what. That makes it nearly impossible to trace a UI issue back to its source. In production environments, teams rely on git history and design versioning to collaborate safely. Without that link, every export becomes a frozen snapshot that cannot be rolled back or compared. Developers often end up deleting the output and starting fresh with manual coding to avoid the mess.It’s Hard For Another Developer to Pick UpEven if you understand the generated code yourself, another developer joining the project might not. The export provides no clear component boundaries, no property (prop) definitions and no explanation of how it is meant to be used. There is no inline documentation to show expected states or variations. Without this context, a new developer has to reverse engineer both the design intent and the quirks of the code before making even a small change. In a team setting, this lack of clarity quickly becomes a productivity killer.These limitations are why most teams end up discarding the code generated by Figma-to-code tools altogether. But what if the workflow started with composability instead of static markup?How to Convert Figma Designs To Production-Ready CodeTo turn design exports into maintainable code, start by importing the same Figma dashboard used earlier into Hope AI. The tool will first analyze the layout and hierarchy, mapping the design into a component tree that highlights reusable patterns such as buttons, cards and form inputs.Hope AI analysis step showing it interprets the user request before generating code.This pre-generation step is where structure takes shape. You review the proposed architecture, confirm the relationships between components and adjust naming or grouping where necessary. This process reverses the usual design-to-code workflow, ensuring that structure leads and code follows.Hope AI analysis step showing it interprets the user request before generating code.Once the structure is approved, Hope AI generates the components and builds an interactive demo. Each element uses proper HTML semantics. Buttons are defined as elements, selects are and tables follow correct markup conventions. The generated UI also includes basic interactivity. Pagination, form inputs and sorting behaviors are all functional.If similar components already exist anywhere in your project or company, Hope AI detects them and reuses those instead of duplicating new ones. This keeps your design system clean and consistent. Behind the scenes, the code is organized as Bit components, each with props, tests, a README and a live composition example. You can also extend these to publish specific components in your design system.Dashboard view of Hope AI generated components with attached documentationThe generated components are ready for versioning and can be shared across projects or teams. Each one is independent and discoverable in your component registry, which makes collaboration and scaling much easier.Beyond semantics and structure, Hope AI’s composable architecture is even more powerful in production workflows.Why Bit Cloud AI-Powered Workflow Scales In ProductionThe real value of a composable workflow shows up in how teams build, maintain and scale applications. Some areas include:Reuse across projects: Components are packaged as versioned units that can be imported into any project. Your team can avoid rebuilding the same button or card multiple times, ensuring consistent behavior and faster delivery.Design-to-development feedback loop: Since components live in a shared registry, designers can view existing components before creating new patterns. This shortens handoff cycles, reduces duplication and keeps design and code aligned.Version history and traceability: Every component comes with version history. You can see when and why something changed and roll back safely. This replaces the static and one-off nature of Figma exports with a collaborative workflow.Production-ready from the start: The generated components use semantic HTML, include tests and meet accessibility standards. You can ship them directly instead of rewriting or debugging generated code.The Hope AI workflow demonstrates that design-to-code can work in production, but only if the workflow respects how teams build and maintain software.Wrapping UpMost Figma-to-code tools export static markup that mirrors the design but fails in production. The output is rigid, unstructured and disconnected from your system, which is why teams often discard it and rebuild from scratch. A composable workflow such as Bit’s Hope AI takes a different path. Designs are broken down into reusable components with props, semantic HTML, tests and version history. Instead of throwaway code, you get building blocks that fit naturally into a real codebase and can scale with your product.Engineering judgment will always be needed, but starting with production-ready components gives teams a serious head start. It reduces duplication, improves collaboration and creates a shared source of truth between design and development.Want to see this workflow in action? Run a design through Hope AI and get system-ready components you can version, share and reuse across projects.The post How a Component-First Approach Fixes Figma-to-Code appeared first on The New Stack.