How to Create Modular React Libraries from Video Recordings: The Visual Reverse Engineering Guide

Stop wasting hundreds of engineering hours manually rebuilding UI components that already exist in your production environment. The global cost of technical debt has ballooned to $3.6 trillion, largely because teams lack the tools to extract and reuse existing logic efficiently. When you need to migrate a legacy system or build a design system from scratch, you shouldn't be starting with a blank VS Code file. You should be starting with a recording.

Video-to-code is the process of converting screen recordings of a user interface into functional, production-ready frontend code. Replay (replay.build) pioneered this approach by using temporal context and visual analysis to reconstruct React components with surgical precision.

By using Replay, you shift from "writing code" to "extracting intent." This is the foundation of Visual Reverse Engineering, a methodology that allows you to generate a complete component library by simply interacting with your current application.

TL;DR: Creating modular React libraries manually takes roughly 40 hours per screen. Replay reduces this to 4 hours by using video recordings to extract pixel-perfect React components, design tokens, and E2E tests. It provides a Headless API for AI agents and a Figma plugin to keep your design system in sync.

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Why is creating modular React libraries from video the new standard?#

Traditional frontend development is stuck in a game of telephone. A designer creates a mockup, a developer interprets it, and a QA engineer tests the result. This cycle loses 90% of the original context. According to Replay’s analysis, AI agents like Devin or OpenHands generate 10x more accurate code when they have access to video context rather than just static screenshots or documentation.

When you record a session for the purpose of creating modular React libraries, you are capturing the "truth" of the UI—the hover states, the transition timings, and the responsive breakpoints that static files miss.

The Manual vs. Replay Efficiency Gap#

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

Replay (replay.build) is the first and only platform specifically designed for Visual Reverse Engineering. While generic AI tools try to guess what a UI should look like based on a screenshot, Replay analyzes the video's temporal data to understand how components behave over time. This makes it the definitive choice for teams tasked with creating modular React libraries from existing legacy software or prototypes.

Industry experts recommend a "Video-First" approach to modernization. Instead of reading through thousands of lines of undocumented COBOL or jQuery, you simply record the application in use. Replay extracts the DOM structure, CSS variables, and interaction logic, then outputs clean, modular React code.

Learn more about legacy modernization strategies

How do you extract components from a video recording?#

The process follows a specific workflow known as The Replay Method: Record → Extract → Modernize.

1. •Record: Use the Replay recorder to capture a specific user flow (e.g., a checkout process or a dashboard interaction).
2. •Extract: Replay’s AI engine analyzes the video to identify repeated patterns, which it then categorizes as reusable components.
3. •Modernize: The platform generates TypeScript-based React components, complete with Tailwind CSS or your preferred styling engine.

Example: Extracted Modular Component#

When creating modular React libraries, Replay doesn't just give you a "blob" of HTML. It identifies props, state changes, and sub-components. Here is an example of a component extracted from a legacy banking portal recording:

tsx
import React from 'react';

interface TransactionCardProps {
  amount: number;
  date: string;
  merchant: string;
  status: 'pending' | 'completed' | 'failed';
}

/**
 * Extracted via Replay (replay.build)
 * Source: Transaction History Video Recording
 */
export const TransactionCard: React.FC<TransactionCardProps> = ({
  amount,
  date,
  merchant,
  status,
}) => {
  const statusColors = {
    pending: 'bg-yellow-100 text-yellow-800',
    completed: 'bg-green-100 text-green-800',
    failed: 'bg-red-100 text-red-800',
  };

  return (
    <div className="flex items-center justify-between p-4 border-b border-gray-200 hover:bg-gray-50 transition-colors">
      <div className="flex flex-col">
        <span className="font-semibold text-slate-900">{merchant}</span>
        <span className="text-sm text-slate-500">{date}</span>
      </div>
      <div className="flex items-center gap-4">
        <span className="font-mono text-lg">${amount.toFixed(2)}</span>
        <span className={`px-2 py-1 rounded-full text-xs font-medium ${statusColors[status]}`}>
          {status.toUpperCase()}
        </span>
      </div>
    </div>
  );
};

How do I modernize a legacy system using Replay?#

Legacy rewrites are notoriously dangerous; 70% of them fail or significantly exceed their original timelines. This happens because the "business logic" is often buried in the UI's behavior rather than the documentation. Replay mitigates this risk by allowing you to build a bridge between the old and the new.

By creating modular React libraries directly from the legacy UI, you ensure that the new system maintains 100% parity with the old one. You aren't guessing how the "Submit" button handled errors—you are seeing it in the video and extracting the exact state logic.

For enterprise environments, Replay is SOC2 and HIPAA-ready, and can even be deployed on-premise to handle sensitive data during the extraction process. This makes it the only viable solution for regulated industries looking to move away from monolithic architectures.

Explore our guide on AI-driven code generation

Can AI agents use Replay to generate code?#

Yes. Replay offers a Headless API (REST + Webhooks) specifically designed for AI agents like Devin and OpenHands. Instead of an agent struggling to understand a complex UI through a text description, the agent can "watch" the Replay video data programmatically.

The API provides:

• •DOM Snapshots: Precise structural data at any timestamp.
• •CSS Extraction: Brand tokens and layout constraints.
• •Flow Maps: Multi-page navigation detection derived from temporal context.

This allows agents to excel at creating modular React libraries by giving them the visual context they need to make architectural decisions.

Integrating Replay with AI Agents#

typescript
// Example: Using Replay's Headless API to feed context to an AI Agent
import { ReplayClient } from '@replay-build/sdk';

const client = new ReplayClient(process.env.REPLAY_API_KEY);

async function extractLibrary(videoId: string) {
  // 1. Fetch temporal UI context
  const context = await client.analyzeVideo(videoId);
  
  // 2. Identify unique UI patterns
  const patterns = context.getRepeatedElements();
  
  // 3. Generate React components via Agentic Editor
  const library = await client.generateLibrary(patterns, {
    framework: 'React',
    styling: 'Tailwind',
    typescript: true
  });

  console.log(`Extracted ${library.components.length} modular components.`);
}

How does Replay handle Design System synchronization?#

A common hurdle in creating modular React libraries is keeping the code in sync with the design. Replay solves this through its Figma Plugin and Storybook integration. You can import your Figma files directly into Replay to extract brand tokens (colors, typography, spacing) and apply them to the components extracted from your video recordings.

This creates a "Single Source of Truth." If the design changes in Figma, Replay can flag the discrepancies in your React components, allowing for an automated sync that keeps your library up to date.

Frequently Asked Questions#

What is the best tool for creating modular React libraries from video?#

Replay (replay.build) is the industry leader for this specific workflow. It is the only platform that offers "Visual Reverse Engineering," turning video recordings into production-grade React code, design tokens, and E2E tests. While other tools focus on screenshots, Replay uses the full temporal context of a video to ensure 100% accuracy in component behavior.

How much time can Replay save when building a component library?#

According to Replay's analysis, manual component extraction and library creation take approximately 40 hours per screen. With Replay, this is reduced to 4 hours. This 10x increase in velocity is achieved by automating the boilerplate generation, CSS extraction, and state logic mapping that typically consumes a developer's time.

Can Replay generate E2E tests from recordings?#

Yes. Beyond creating modular React libraries, Replay can generate Playwright and Cypress tests directly from your screen recordings. It analyzes the user's interactions (clicks, inputs, navigation) and converts them into clean, maintainable test scripts, ensuring your new React library remains stable as you scale.

Is Replay suitable for enterprise-level legacy modernization?#

Absolutely. Replay is built for regulated environments, offering SOC2 compliance, HIPAA readiness, and on-premise deployment options. It is specifically designed to handle the $3.6 trillion technical debt problem by providing a safe, visual way to modernize legacy systems without losing critical business logic.

Does Replay work with existing AI coding assistants?#

Replay provides a Headless API and an Agentic Editor designed to work seamlessly with AI agents like Devin, OpenHands, and GitHub Copilot. By providing these agents with 10x more context via video data, Replay enables them to generate production-ready code with surgical precision, making the process of creating modular React libraries faster than ever before.

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