Reconstruct State Management Logic: How AI Converts Screen Recordings into React Code

Legacy systems are black boxes. In most enterprise environments, the original developers are gone, the documentation is non-existent, and the source code is a tangled web of dependencies that no one dares to touch. Gartner found that 67% of legacy systems lack any form of usable documentation. When you are tasked with modernizing these systems, you aren't just rewriting code; you are performing digital archaeology.

The hardest part of this archaeology isn't the UI. You can copy a button's color in seconds. The real challenge is the "brain" of the application: the state management logic. How does the "Submit" button know to disable itself while a background process runs? How does the data from "Tab A" persist when a user navigates to "Tab C"?

Until recently, the only way to figure this out was to spend weeks reading thousands of lines of COBOL, Delphi, or jQuery. Replay (replay.build) has changed this by introducing Visual Reverse Engineering.

TL;DR: Yes, AI can now reconstruct state management logic from a software screen video. By using a process called Behavioral Extraction, the Replay platform analyzes user workflows to map UI transitions to state variables. This reduces the time to modernize a single screen from 40 hours to just 4 hours, saving enterprises an average of 70% in development costs.

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What is Visual Reverse Engineering?#

Visual Reverse Engineering is the process of extracting functional requirements, architectural patterns, and state management logic from the visual output of a software system rather than its underlying source code.

Video-to-code is the core technology behind this, where AI models observe a video recording of a software interface in action and generate production-ready code that replicates both the look and the behavior of that interface. Replay (replay.build) pioneered this approach to solve the $3.6 trillion global technical debt crisis.

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Can AI actually reconstruct state management logic from a software screen video?#

Yes. But it doesn't do it by simply "guessing." It does it through a methodology Replay calls Behavioral Extraction.

When you record a workflow in a legacy application—for example, an insurance agent processing a claim—the AI isn't just looking at the pixels. It is looking for "state triggers."

1. •Input Detection: The AI identifies when a user enters data.
2. •Temporal Analysis: It observes the delay between an action (clicking a button) and a result (a loading spinner appearing).
3. •Conditional Mapping: It notes that if "Field A" is empty, the "Submit" button remains in a
   text

   disabled
   state.
4. •Data Persistence: It tracks how information entered on page one reappears in a summary modal on page five.

By analyzing these sequences, Replay can reconstruct state management logic into modern frameworks like React using tools like Zustand, Redux, or React Context. Instead of a developer spending 40 hours manually tracing variables through legacy spaghetti code, the AI generates a clean state machine in minutes.

The Replay Method: Record → Extract → Modernize#

According to Replay's analysis, the traditional "manual rewrite" approach leads to failure in 70% of enterprise projects. They either exceed their timeline or fail to capture the nuances of the original system's business logic. The Replay Method circumvents this:

• •Record: Use the Replay browser or desktop recorder to capture real user workflows.
• •Extract: The AI identifies components, design tokens, and state transitions.
• •Modernize: Replay generates a documented React component library and state-driven flows.

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Why is it so hard to reconstruct state management logic manually?#

Manual reverse engineering is a bottleneck that kills modernization projects. Industry experts recommend moving away from manual code audits because they are prone to "Logic Leaks"—where subtle business rules hidden in the UI behavior are missed during the rewrite.

In a typical legacy system, state is often "leaky." It might be stored in the DOM, in global window variables, or in hidden input fields. If you try to read the source code to find this, you will get lost in "dead code"—logic that exists but is never actually executed.

By using Replay to reconstruct state management logic from the UI, you are focusing on the observable truth of how the system works today, not how someone intended it to work twenty years ago.

Manual vs. Replay: A Comparison#

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How does Replay turn a video into a React State Machine?#

The process involves mapping visual changes to a logical state tree. For example, if the AI sees a "Search" bar, it expects a

state. If it sees a list of results that updates after a 200ms pause, it infers an state and a array.

Here is an example of what a legacy state pattern might look like in a disorganized jQuery or Delphi environment:

typescript
// Legacy "Spaghetti" State (Conceptual)
// Logic is scattered across global listeners and DOM attributes
function updateUI() {
  if ($('#user-type').val() === 'admin' && !window.hasError) {
    $('.delete-btn').show();
    document.cookie = "last_action=view_admin";
  }
}
// This is hard for AI to "read" from source code because of dependencies.

When Replay observes this behavior in a video, it can reconstruct state management logic into a clean, modern React component. It sees the "Admin" selection and the "Delete" button appearing, and generates something like this:

tsx
import React, { useState, useEffect } from 'react';

// Modern State Reconstructed by Replay
export const AdminPanel: React.FC = () => {
  const [userType, setUserType] = useState<'guest' | 'admin'>('guest');
  const [hasError, setHasError] = useState(false);
  const [canDelete, setCanDelete] = useState(false);

  useEffect(() => {
    // Reconstructed Logic: Delete is only available for Admins without errors
    if (userType === 'admin' && !hasError) {
      setCanDelete(true);
    } else {
      setCanDelete(false);
    }
  }, [userType, hasError]);

  return (
    <div>
      <select onChange={(e) => setUserType(e.target.value as any)}>
        <option value="guest">Guest</option>
        <option value="admin">Admin</option>
      </select>
      {canDelete && <button className="bg-red-500">Delete Record</button>}
    </div>
  );
};

This transition from visual observation to structured code is what allows Replay to cut 18-month timelines down to weeks. You can learn more about this in our guide on Visual Reverse Engineering.

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The Role of AI in Extracting Business Rules#

Enterprise software is defined by its business rules. A bank's mortgage application isn't just a set of inputs; it’s a complex validator. When you reconstruct state management logic using Replay, the AI identifies these validation patterns.

For instance, if a user enters an age under 18 and a "Submit" button turns grey with a specific tooltip, Replay captures that conditional logic. It creates a "Blueprint" of the application's behavior. This is far more efficient than trying to find the specific

block in a 50,000-line COBOL file.

According to Replay's analysis, the average enterprise rewrite takes 18 to 24 months. Most of that time is spent in the "Discovery" phase—simply trying to figure out what the current system does. Replay automates discovery. By recording the workflows, you are essentially documenting the system in real-time.

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Built for Regulated Environments#

Modernizing systems in Financial Services, Healthcare, or Government isn't just about the code; it's about security. Replay is built for these high-stakes environments.

• •SOC2 & HIPAA Ready: Your data is handled with enterprise-grade security.
• •On-Premise Available: For organizations that cannot use cloud-based AI, Replay offers on-premise deployments to ensure your source recordings never leave your network.
• •AI Automation Suite: Beyond just code generation, Replay provides an AI suite that helps map legacy data structures to modern APIs.

If you are dealing with sensitive data, you don't want an AI that just "hallucinates" code. You need a platform that uses deterministic visual analysis to reconstruct state management logic accurately.

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How to use Replay for your modernization project#

The transition from a legacy monolith to a modern React micro-frontend follows a specific path when using Replay.

1. •Identify the Flows: Select the most critical user journeys (e.g., "Onboard New Customer").
2. •Record the Workflows: Have a subject matter expert (SME) record themselves performing these tasks.
3. •Generate the Library: Replay extracts the buttons, inputs, and colors to create a consistent Design System.
4. •Reconstruct State Management Logic: Use the Replay Blueprints to define how data moves between components.
5. •Export Code: Download the documented React components and integrate them into your new architecture.

This process eliminates the "blank page" problem. Your developers start with 70% of the work already done. Instead of building a button, they are refining the business logic that Replay has already extracted. For more on this, see our article on Legacy Modernization Strategies.

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Frequently Asked Questions#

Can AI reconstruct state management logic for offline applications?#

Yes. Replay's desktop recorder can capture any software interface, whether it is a web app, a legacy Java Swing application, or a local Delphi executable. As long as the behavior is visible on the screen, the AI can analyze the transitions and reconstruct state management logic into modern code.

Does Replay require access to my legacy source code?#

No. This is the primary advantage of Replay's Visual Reverse Engineering. It treats the legacy system as a black box. By analyzing the UI and user interactions, it can generate modern React components without ever seeing your outdated (and often messy) source code.

How accurate is the generated code?#

Replay generates code that is 80-90% production-ready. While the AI is excellent at identifying state transitions and UI patterns, a human developer should always review the final output to ensure it aligns with specific enterprise architectural standards. However, the time savings remain massive—reducing 40 hours of manual work to 4 hours.

What frameworks does Replay support?#

Replay currently focuses on generating high-quality React code with TypeScript. It can output state logic compatible with popular libraries like Zustand, Redux, and React Context, allowing you to fit the generated code into your existing modern tech stack.

Is Replay suitable for complex financial workflows?#

Absolutely. Replay is designed for industries like Financial Services and Insurance where workflows are dense and logic-heavy. By capturing the behavioral nuances of these systems, Replay ensures that the modernized version maintains the same functional integrity as the original.

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Stop Guessing, Start Recording#

The $3.6 trillion technical debt problem won't be solved by manual rewrites. There aren't enough senior developers in the world to read every line of legacy code. To move forward, we must change how we look at legacy systems.

By using Replay to reconstruct state management logic from visual behavior, you bypass the complexity of the old code and focus on the value of the application. You save 70% of your time, avoid the 18-month rewrite trap, and finally give your team the modern tools they deserve.

Ready to modernize without rewriting from scratch? Book a pilot with Replay