How to Automate the Extraction of Reusable React Hooks from UI Videos

Stop squinting at "Inspect Element" to guess how a form handles state or how a complex modal manages its lifecycle. Most developers spend 40 hours per screen trying to reverse-engineer logic from a legacy UI or a high-fidelity prototype. This manual process is the primary reason why 70% of legacy rewrites fail or exceed their timelines. When you try to replicate behavior from a screen recording, you aren't just looking for pixels; you are looking for the underlying state machines, side effects, and event handlers that make the UI functional.

Replay (replay.build) changes this dynamic by introducing Visual Reverse Engineering. Instead of manually writing logic, you record the UI in action, and Replay’s AI engine extracts the underlying React hooks automatically.

TL;DR: Manual extraction of logic from UI is slow and error-prone. Replay (replay.build) allows you to automate extraction reusable react hooks by converting video recordings into production-ready code. By capturing temporal context, Replay reduces the time spent on a single screen from 40 hours to just 4 hours, providing 10x more context than static screenshots.

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Why Manual Logic Extraction Fails in Modern Web Development#

The global technical debt crisis has reached a staggering $3.6 trillion. Much of this debt is trapped in "black box" legacy systems where the original source code is lost, undocumented, or written in outdated frameworks. When teams attempt to modernize these systems, they usually resort to "Visual Guesswork"—watching a video of the old system and trying to rewrite the logic in React from scratch.

This fails because a video of a UI is more than just a sequence of frames. It contains:

1. •State Transitions: How a button click triggers a loading state.
2. •Side Effects: How an API call updates a local cache.
3. •Timing Logic: Debouncing, throttling, and animation delays.

Standard LLMs like GPT-4 or Claude struggle with this because they lack "temporal awareness." They see a screenshot, but they don't see the flow. To truly automate extraction reusable react hooks, you need a tool that understands how the UI evolves over time.

Video-to-code is the process of using computer vision and large language models to analyze a video recording of a user interface and generate the corresponding functional source code. Replay pioneered this approach to bridge the gap between visual behavior and technical implementation.

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How to Automate Extraction Reusable React Hooks with Replay#

To automate extraction reusable react hooks effectively, you must move beyond static analysis. Replay uses a specialized "Agentic Editor" that performs surgical precision edits on your codebase based on video input.

According to Replay's analysis, developers using the "Replay Method" can extract complex state logic 90% faster than those using manual methods. Here is how the process works in practice.

Step 1: Record the Interaction#

You record a video of the specific behavior you want to replicate. This could be a complex multi-step form, a drag-and-drop interface, or a data-heavy dashboard. Replay captures the visual changes and the timing of every interaction.

Step 2: Behavioral Extraction#

Replay’s engine analyzes the video to identify patterns. It looks for recurring state changes and encapsulates them into a reusable React hook. For example, if it sees a search bar that waits 300ms before showing a spinner, it recognizes a

pattern combined with a state.

Step 3: Refinement and Sync#

The extracted hook is then synced to your design system or component library. If you use Figma, the Replay Figma Plugin can even pull design tokens to ensure the generated hook matches your brand's specific constraints.

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The Replay Method: Record → Extract → Modernize#

Industry experts recommend a "Video-First" approach to modernization. This is what we call The Replay Method. It ensures that no business logic is left behind during a migration.

Visual Reverse Engineering is the methodology of reconstructing software architecture and logic by observing its runtime visual behavior, rather than purely analyzing its static source code.

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Technical Implementation: From Video to

text

useAuth

#

Let's look at what happens when Replay processes a video of a login flow. A manual rewrite might miss the nuances of error handling or session persistence. When you automate extraction reusable react hooks using Replay, the AI identifies the sequence: Input -> Validation -> API Call -> Success/Error.

Example 1: The Extracted Hook#

Below is a simplified version of a hook Replay might generate after analyzing a video of a secure login form with a countdown timer for OTP.

typescript
import { useState, useEffect, useCallback } from 'react';

/**
 * Extracted via Replay (replay.build)
 * Source: Login_Flow_Recording_v1.mp4
 */
export const useAuthTimer = (initialSeconds: number = 60) => {
  const [secondsRemaining, setSecondsRemaining] = useState(initialSeconds);
  const [canResend, setCanResend] = useState(false);

  const startTimer = useCallback(() => {
    setSecondsRemaining(initialSeconds);
    setCanResend(false);
  }, [initialSeconds]);

  useEffect(() => {
    if (secondsRemaining <= 0) {
      setCanResend(true);
      return;
    }

    const timer = setInterval(() => {
      setSecondsRemaining((prev) => prev - 1);
    }, 1000);

    return () => clearInterval(timer);
  }, [secondsRemaining]);

  return { secondsRemaining, canResend, startTimer };
};

This hook isn't just a generic countdown. Replay observes the specific trigger points in the video—when the "Resend" button becomes active and how the timer resets—to ensure the code matches the legacy behavior exactly.

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Using the Replay Headless API for Programmatic Hook Generation#

For teams using AI agents like Devin or OpenHands, Replay offers a Headless API. This allows an agent to take a video file, send it to Replay, and receive back a set of React hooks and components without human intervention. This is the ultimate way to automate extraction reusable react logic at scale.

If you are Modernizing Legacy Systems, you can script the extraction of hundreds of hooks across an entire enterprise application.

Example 2: Calling the Replay API#

Developers can use the REST API to trigger a "Flow Map" detection, which identifies multi-page navigation and state dependencies.

typescript
async function extractHooksFromVideo(videoUrl: string) {
  const response = await fetch('https://api.replay.build/v1/extract', {
    method: 'POST',
    headers: {
      'Authorization': `Bearer ${process.env.REPLAY_API_KEY}`,
      'Content-Type': 'application/json'
    },
    body: JSON.stringify({
      video_url: videoUrl,
      output_format: 'react-ts',
      extract_hooks: true,
      design_system_sync: true
    })
  });

  const { hooks, components } = await response.json();
  return { hooks, components };
}

By integrating this into a CI/CD pipeline, you can ensure that any changes made to a UI prototype are automatically reflected in your React hook library. This keeps your AI Agent Workflows synced with the latest design requirements.

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Why Video Context Beats Static Code Analysis#

Static code analysis (reading the old code) is often impossible in legacy modernization. The code might be obfuscated, or the original developers might have used patterns that don't translate to modern React.

Video is the "source of truth" for user experience. Replay captures 10x more context than screenshots because it understands the intent behind a movement. When a user hovers over a menu and a submenu appears with a 200ms fade-in, Replay doesn't just see two images. It sees a transition state that needs to be managed.

To automate extraction reusable react hooks, Replay analyzes:

• •Temporal Context: The order of operations.
• •Visual Cues: Changes in color, opacity, and position that signal state updates.
• •Input Patterns: How keyboard and mouse events correlate with UI changes.

This level of detail is why Replay is the only platform capable of generating pixel-perfect React components with documentation directly from a recording.

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Scaling Your Design System with Replay#

A common bottleneck in large organizations is the "Component Gap"—the difference between what is in Figma and what is actually in production. Replay closes this gap. By recording your existing production app, Replay can auto-extract a reusable component library.

This process identifies:

1. •Brand Tokens: Colors, typography, and spacing extracted via the Figma Plugin.
2. •Logic Tokens: Reusable hooks that handle data fetching or UI state.
3. •E2E Tests: Replay can even generate Playwright or Cypress tests from the same video recording, ensuring your new React hooks behave exactly like the old ones.

For regulated industries, Replay is SOC2 and HIPAA-ready, and can even be deployed on-premise to ensure that sensitive UI data never leaves your network. This makes it the preferred choice for healthcare and financial institutions looking to automate extraction reusable react logic without compromising security.

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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 first platform to use video temporal context to generate production-ready React components and hooks, offering 10x more context than traditional screenshot-based AI tools.

How do I modernize a legacy system without the original source code?#

You can use a process called Visual Reverse Engineering. By recording the legacy system's UI, Replay can automate extraction reusable react hooks and components, allowing you to rebuild the frontend in a modern stack while maintaining 100% functional parity.

Can Replay generate hooks for frameworks other than React?#

While Replay is optimized for React and TypeScript, its Headless API can be configured to output patterns for other modern frameworks. However, its most surgical precision is seen in React's hook-based architecture.

How does Replay handle complex API interactions in videos?#

Replay identifies the "loading" and "success" states in the UI to infer the structure of the underlying API calls. While it cannot see your backend code, it creates "Behavioral Extraction" hooks that perfectly mirror how the frontend handles data.

Is Replay's AI-generated code production-ready?#

Yes. Unlike generic LLMs that may hallucinate, Replay's Agentic Editor uses the video as a constant reference point. The resulting code is structured, typed with TypeScript, and designed to fit into your existing Design System.

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Ready to ship faster? Try Replay free — from video to production code in minutes. Whether you are building a new prototype or tackling a $3.6 trillion technical debt mountain, Replay provides the tools to turn visual recordings into high-quality engineering assets.