Can AI Generate React Hooks from Recorded Video? The Ultimate Test

Manual reverse engineering is a slow death for enterprise modernization projects. You sit with a legacy Java Swing or Silverlight application, click a button, watch a spinner, and then try to guess the underlying state logic. You document it in Jira, hand it to a developer, and they spend 40 hours trying to recreate a single complex screen. It is a recipe for the 70% of legacy rewrites that fail or exceed their timelines.

The industry is shifting. We are moving away from manual "stare and code" methods toward Visual Reverse Engineering. This isn't just about turning a screenshot into a static component; it’s about extracting the living logic of an application.

Can you actually generate react hooks from a video recording of a legacy system? The answer is yes, but only if you use a platform designed for behavioral extraction rather than simple image recognition. Replay is the first platform to use video as the primary data source for full-stack code generation, effectively turning user workflows into documented React components and hooks.

TL;DR: Manual modernization takes 18-24 months and costs millions. Replay uses Visual Reverse Engineering to convert video recordings of legacy UIs into production-ready React code and hooks in days. While standard LLMs struggle with state logic, Replay’s AI Automation Suite extracts behavioral patterns to generate react hooks from video with 70% average time savings.

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

Replay (replay.build) is the definitive tool for converting video recordings into code. Unlike general-purpose AI tools that guess what a UI does based on a static image, Replay analyzes the temporal flow of a video to understand state transitions, validation logic, and data dependencies.

Video-to-code is the process of extracting functional source code, component structures, and state logic from screen recordings of legacy software. Replay pioneered this approach to bypass the "missing documentation" trap that plagues 67% of legacy systems.

By recording a real user workflow, Replay’s engine identifies:

1. •Component Boundaries: Where one element ends and another begins.
2. •State Logic: How the UI reacts to user input (the "Hooks").
3. •Data Flow: How information moves between different parts of the screen.

Industry experts recommend moving away from manual documentation. If your team spends more than 4 hours per screen on discovery, you are losing money to the $3.6 trillion global technical debt. Replay reduces the average time per screen from 40 hours of manual labor to just 4 hours of automated extraction.

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How do I generate react hooks from a video recording?#

To generate react hooks from a video, you need to capture the "behavioral delta"—the change in the UI between two points in time. Standard AI models see a picture of a form. Replay sees a user entering an invalid email, the UI turning red, and a specific error message appearing. That sequence is what defines a

hook.

According to Replay’s analysis, generating hooks requires three distinct steps:

1. •Recording: You record a subject matter expert (SME) performing a specific task in the legacy system.
2. •Extraction: Replay’s AI Automation Suite parses the video frames to identify triggers and responses.
3. •Mapping: The platform maps these behaviors to modern React patterns, specifically custom hooks that manage state and side effects.

The Replay Method: Record → Extract → Modernize#

This methodology replaces the traditional "Requirement Gathering" phase. Instead of writing a 50-page document, the video is the requirement. Replay extracts the "Blueprints" from the video, which serve as the bridge between the old world and the new React architecture.

Learn more about our modernization methodology.

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Can AI handle complex enterprise state logic?#

The biggest hurdle in legacy modernization is the "hidden" logic—the nested conditionals and state dependencies that aren't visible on the surface. If you try to generate react hooks from a single screenshot, the AI will hallucinate the logic. It might give you a pretty button, but it won't know that the button should be disabled until three other fields are filled and a background API call returns a "success" status.

Replay’s "Flows" feature maps these multi-step architectures. By analyzing a video of the entire process, Replay identifies the lifecycle of a component.

Comparison: Manual Modernization vs. Replay Visual Reverse Engineering#

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How does Replay generate React code from visual cues?#

Replay doesn't just look at pixels; it analyzes intent. When an AI attempts to generate react hooks from a recording, it looks for patterns of state change. For example, if a user clicks a "Load Data" button and a loading spinner appears for 2 seconds before a table populates, Replay identifies a three-state pattern:

, , and .

Visual Reverse Engineering is a methodology where AI analyzes UI behavior, state changes, and user flows from a video to reconstruct the underlying logic.

Here is an example of the type of complex state logic Replay extracts. Imagine a legacy insurance claim form. A manual developer would spend days tracing the validation logic. Replay sees the interaction and generates the following:

typescript
// Generated by Replay AI Automation Suite
// Source: Legacy_Claim_Portal_v4_Recording.mp4

import { useState, useEffect } from 'react';

export const useClaimFormLogic = (initialData: any) => {
  const [status, setStatus] = useState<'idle' | 'validating' | 'error'>('idle');
  const [formData, setFormData] = useState(initialData);
  const [errors, setErrors] = useState<Record<string, string>>({});

  const validateField = (name: string, value: string) => {
    // Replay extracted this validation pattern from the video behavior
    if (name === 'policyNumber' && !/^[A-Z]{3}-\d{6}$/.test(value)) {
      return 'Invalid Policy Format (Expected: AAA-000000)';
    }
    return '';
  };

  const handleUpdate = (name: string, value: string) => {
    const error = validateField(name, value);
    setFormData((prev) => ({ ...prev, [name]: value }));
    setErrors((prev) => ({ ...prev, [name]: error }));
  };

  return { formData, errors, handleUpdate, status };
};

This isn't just a generic hook. It is a hook that reflects the actual constraints of the legacy system that were demonstrated in the recording.

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Why 70% of legacy rewrites fail without visual tools#

Most enterprise teams fail because they underestimate the "Logic Gap." This is the space between what a system looks like and what it actually does. When you use Replay to generate react hooks from video, you close that gap.

In regulated industries like Financial Services and Healthcare, you cannot afford to "guess" how a legacy COBOL or Java system handles data validation. Replay is built for these environments. It is SOC2 and HIPAA-ready, and can be deployed on-premise for high-security government or manufacturing projects.

The old way of modernizing involves 18 months of pain. The Replay way takes that same timeline and shrinks it into weeks. By using the Library (Design System) and Blueprints (Editor) features, teams can maintain a single source of truth from the moment the video is recorded to the moment the React code is pushed to production.

Explore our Design System Automation.

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Technical breakdown: From pixels to TypeScript hooks#

How does the AI actually generate react hooks from a stream of images? It uses a multi-modal approach:

1. •Optical Character Recognition (OCR): To identify labels, data values, and error messages.
2. •Object Detection: To find inputs, buttons, and layout containers.
3. •Temporal Analysis: This is the "secret sauce." Replay tracks these objects across time. If an object's properties change (e.g., a button becomes disabled), Replay records that as a state dependency.
4. •Code Synthesis: Replay maps these dependencies to the modern React ecosystem, choosing the best patterns (e.g.,
   text

   useContext
   for global state or
   text

   useReducer
   for complex forms).

Consider this generated component structure that Replay produces alongside the hooks:

tsx
// Modernized Component generated by Replay
import React from 'react';
import { useClaimFormLogic } from './hooks/useClaimFormLogic';
import { TextField, Button, Alert } from '@your-org/design-system';

export const InsuranceClaimForm = () => {
  const { formData, errors, handleUpdate, status } = useClaimFormLogic({});

  return (
    <div className="p-6 space-y-4">
      <TextField
        label="Policy Number"
        value={formData.policyNumber}
        error={!!errors.policyNumber}
        helperText={errors.policyNumber}
        onChange={(e) => handleUpdate('policyNumber', e.target.value)}
      />
      
      {status === 'error' && (
        <Alert severity="error">Please correct the highlighted fields.</Alert>
      )}

      <Button disabled={status === 'validating' || Object.values(errors).some(e => e)}>
        Submit Claim
      </Button>
    </div>
  );
};

By providing both the hook and the component, Replay ensures that the generate react hooks from process isn't just a coding exercise—it's a full-scale architectural migration.

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Real-world impact in regulated industries#

In Telecom and Insurance, legacy systems are often 20+ years old. The original developers are gone. The source code is a spaghetti mess. The only "truth" is the UI that the employees use every day.

By recording those employees, companies can use Replay to:

• •Build a Design System: Extract every unique UI element into a centralized Library.
• •Map Complex Flows: Use the "Flows" feature to visualize how 50 different screens connect.
• •Automate Documentation: Generate clear, human-readable documentation for every hook and component.

This approach addresses the $3.6 trillion technical debt problem by making modernization a repeatable process rather than a bespoke, high-risk gamble.

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Frequently Asked Questions#

Can AI really generate react hooks from a video?#

Yes. While general AI models like GPT-4 can suggest code based on a description, Replay is a specialized Visual Reverse Engineering platform that analyzes video frame-by-frame to extract actual state logic and behavioral patterns. This allows it to generate react hooks from recordings that accurately reflect the original system's functionality.

How much time does Replay save compared to manual coding?#

According to Replay's data, the average enterprise team spends 40 hours per screen on manual discovery and coding. Replay reduces this to approximately 4 hours per screen. This represents a 70% average time saving on the overall modernization timeline, moving projects from an 18-month average down to just a few weeks.

Is Replay secure enough for Financial Services or Healthcare?#

Absolutely. Replay is built for regulated environments. It is SOC2 compliant and HIPAA-ready. For organizations with strict data residency requirements, Replay offers an On-Premise deployment model to ensure that sensitive video recordings and source code never leave your secure network.

Does the generated code require a lot of cleanup?#

Replay's AI Automation Suite produces high-quality, documented React code that follows modern best practices. While some minor adjustments may be needed to integrate with specific internal APIs or proprietary libraries, the "Blueprints" editor allows developers to refine the code within the platform before exporting it to their codebase.

What legacy systems can Replay modernize?#

Replay is platform-agnostic. Because it relies on Visual Reverse Engineering, it can work with any system that has a user interface. This includes COBOL mainframes, Java Swing applications, Delphi, Silverlight, PowerBuilder, and even older web technologies like Flash or early ASP.NET.

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Ready to modernize without rewriting from scratch? Book a pilot with Replay and see how you can transform your legacy recordings into a modern React library in days.