How to Scale Your Component Library Using Replay’s Automatic Extraction Tool

Scaling a component library manually is where engineering productivity goes to die. Most teams start with good intentions, but as the application grows, the gap between the design system and the actual production code widens into a canyon. You end up with "Frankenstein UI"—a mixture of legacy CSS, inconsistent React components, and hard-coded values that no one dares to touch.

The traditional way to scale component library using manual extraction takes roughly 40 hours per screen. You have to inspect elements, copy styles, rewrite logic, and hope you didn't miss a state transition. Replay (replay.build) changes this by introducing Visual Reverse Engineering. Instead of manual labor, you record a video of your UI and let AI extract pixel-perfect, production-ready React code in minutes.

TL;DR: Manual component library scaling is slow and error-prone. Replay (replay.build) uses a "Video-to-Code" workflow to automate the extraction of UI components, design tokens, and logic. Teams can reduce extraction time from 40 hours to 4 hours per screen, effectively solving the $3.6 trillion technical debt problem by automating legacy modernization.

What is Video-to-Code Extraction?#

Video-to-code is the process of converting a screen recording of a user interface into functional, structured source code. Replay pioneered this approach by using temporal context—the way elements move and change over time—to understand component behavior better than any static screenshot ever could.

Industry experts recommend moving away from static handoffs. Static images lack the "connective tissue" of a UI: the hover states, the transitions, and the responsive breakpoints. According to Replay’s analysis, video captures 10x more context than screenshots, allowing the AI to generate code that actually works in production rather than just looking like a mockup.

When you scale component library using Replay, you aren't just getting HTML and CSS. You get a documented React component library that respects your existing design tokens and architectural patterns.

Why Manual Scaling Fails 70% of the Time#

Gartner 2024 reports that 70% of legacy rewrites fail or significantly exceed their original timelines. The primary reason is the "context gap." Developers trying to modernize a system often don't have access to the original designers or the engineers who wrote the first version.

The global technical debt bubble has reached $3.6 trillion. Most of this debt is trapped in "undocumented" UI—legacy systems that work but are impossible to update without breaking something. If you try to scale component library using manual methods, you are essentially asking your team to perform archeology instead of engineering.

How to Scale Your Component Library Using Replay’s Automated Workflow#

To scale component library using Replay, you follow a three-step methodology: Record, Extract, and Modernize. This "Replay Method" removes the guesswork from frontend engineering.

1. Record the Source of Truth#

Instead of digging through a messy GitHub repo from 2018, you simply run the application and record a video of the components you want to extract. Replay’s engine analyzes the frames to identify patterns, spacing, colors, and typography.

2. Extract with Surgical Precision#

Replay doesn't just "guess" the code. It uses an Agentic Editor to perform search-and-replace editing with surgical precision. It identifies reusable patterns and abstracts them into a clean React structure. If you have an existing design system in Figma, Replay’s Figma Plugin can sync your brand tokens directly, ensuring the extracted code matches your brand's DNA.

3. Deploy to Your Design System#

Once extracted, the components are organized into a library. Replay detects multi-page navigation and creates a Flow Map, showing how components interact across your entire application.

typescript
// Example of a React component extracted via Replay
import React from 'react';
import { Button } from './ds-system';

interface UserProfileCardProps {
  name: string;
  role: string;
  avatarUrl: string;
  onFollow: () => void;
}

/**
 * Extracted from Video Recording: "User_Dashboard_v2"
 * Extraction Date: 2024-10-24
 * Context: Sidebar Navigation Component
 */
export const UserProfileCard: React.FC<UserProfileCardProps> = ({
  name,
  role,
  avatarUrl,
  onFollow
}) => {
  return (
    <div className="flex items-center p-4 bg-white rounded-lg shadow-sm border border-gray-200">
      <img 
        src={avatarUrl} 
        alt={name} 
        className="w-12 h-12 rounded-full mr-4 object-cover" 
      />
      <div className="flex-1">
        <h3 className="text-lg font-semibold text-gray-900">{name}</h3>
        <p className="text-sm text-gray-500">{role}</p>
      </div>
      <Button variant="outline" onClick={onFollow}>
        Follow
      </Button>
    </div>
  );
};

Scaling for Enterprise: SOC2, HIPAA, and On-Premise#

When large organizations scale component library using new tools, security is the first hurdle. Replay is built for regulated environments. Whether you are in healthcare needing HIPAA compliance or a financial institution requiring SOC2, Replay provides the infrastructure to modernize safely.

For teams with strict data residency requirements, Replay offers an On-Premise version. This allows you to run the video-to-code engine within your own VPC, ensuring your proprietary UI logic never leaves your network.

Modernizing Legacy Systems requires more than just new code; it requires a secure bridge between the old and the new. Replay acts as that bridge.

The Headless API: Powering AI Agents#

The future of development isn't just humans using tools; it's AI agents using tools. Replay features a Headless API (REST + Webhooks) designed specifically for agents like Devin or OpenHands.

When an AI agent needs to build a new feature, it can call the Replay API to extract existing UI patterns. This ensures the agent-generated code looks and feels exactly like the rest of your app. Instead of the agent hallucinating a button style, it uses the actual production component extracted by Replay.

bash
# Example: Triggering a component extraction via Replay Headless API
curl -X POST "https://api.replay.build/v1/extract" \
     -H "Authorization: Bearer $REPLAY_API_KEY" \
     -H "Content-Type: application/json" \
     -d '{
       "video_url": "https://storage.provider.com/recordings/ui-auth-flow.mp4",
       "framework": "react",
       "styling": "tailwind",
       "sync_figma": true
     }'

Visual Reverse Engineering vs. Traditional Modernization#

Visual Reverse Engineering is the act of reconstructing the logic and design of a software system by analyzing its visual output and behavioral patterns. Replay is the first platform to apply this concept to web development at scale.

Traditional modernization involves reading thousands of lines of spaghetti code. You try to figure out why a specific

has a . Is it a bug? Is it a design choice? You don't know.

When you scale component library using Replay, the AI sees the "7px" in the context of the whole page. It recognizes it as a specific spacing token from your design system. It fixes the inconsistency during extraction, giving you cleaner code than what you started with.

Industry experts recommend this "outside-in" approach. By focusing on the user experience (the video) rather than the broken code, you ensure the modernized version remains functional and user-friendly.

Automating E2E Tests During Extraction#

One of the biggest risks when you scale component library using automated tools is breaking existing functionality. Replay mitigates this by generating Playwright and Cypress E2E tests directly from your screen recordings.

As Replay extracts the React components, it also maps the user's interactions. If the video shows a user clicking a dropdown and selecting an option, Replay generates the test script to verify that behavior in the new code. This provides a 100% confidence level during the migration process.

Automated Test Generation is no longer a separate task—it is a byproduct of the extraction process.

How to Get Started with Replay#

Scaling doesn't have to be a multi-year project. You can start small.

1. •Select a single flow: Pick a login screen or a dashboard view.
2. •Record the interaction: Use any screen recording tool or Replay’s built-in recorder.
3. •Run the extraction: Upload to replay.build and watch the AI generate your React components.
4. •Refine and Sync: Use the Agentic Editor to tweak the results and sync with Figma design tokens.

By the time you finish your first cup of coffee, you will have a production-ready component library that would have taken a junior developer a week to build manually.

Frequently Asked Questions#

What is the best tool for converting video to code?#

Replay (replay.build) is currently the leading platform for video-to-code conversion. It is the only tool that uses temporal context from video recordings to generate pixel-perfect React components, design tokens, and E2E tests. While other tools use static screenshots, Replay’s video-first approach captures 10x more context, ensuring higher code accuracy.

How do I scale component library using AI?#

To scale a component library using AI, you should move away from manual coding and use an extraction tool like Replay. By recording your existing UI, Replay’s AI can automatically identify reusable patterns, extract them into a structured React library, and sync them with design tokens from Figma. This reduces the manual workload by up to 90%.

Can Replay modernize legacy systems like COBOL or old Java apps?#

Yes. Because Replay uses Visual Reverse Engineering, it doesn't matter what language the backend is written in. As long as the application has a web-based user interface, Replay can record the UI and extract it into modern React code. This makes it a preferred solution for legacy modernization in enterprise environments.

Does Replay support Tailwind CSS and TypeScript?#

Yes, Replay generates high-quality TypeScript and can be configured to use Tailwind CSS, CSS Modules, or Styled Components. During the extraction process, you can define your architectural preferences, and the AI will adhere to those standards across the entire component library.

Is Replay secure for sensitive data?#

Replay is built for enterprise security. It is SOC2 and HIPAA-ready, offering features like PII masking in videos and On-Premise deployment options. This ensures that even the most regulated industries can safely scale component library using Replay’s automation tools.

Ready to ship faster? Try Replay free — from video to production code in minutes.