Can AI Understand Legacy UI Error Handling From a Screen Recording?

Your legacy system’s documentation is a lie. If it exists at all, it hasn't been updated since the Bush administration. When you're tasked with modernizing a 20-year-old insurance portal or a core banking terminal, the biggest risk isn't the "happy path"—it's the thousands of edge cases, validation rules, and cryptic error messages buried in millions of lines of spaghetti code.

Manual discovery is a death march. Developers spend weeks clicking every button, entering "asdf" into every field, and trying to trigger every possible failure state just to see what happens. This is why 70% of legacy rewrites fail or exceed their timelines. They miss the hidden logic.

But what if you didn't have to read the source code? What if an AI could watch a user interact with the system and automatically map out every validation rule and error state?

The answer is yes. Through a process called Visual Reverse Engineering, AI can now understand legacy error handling by observing screen recordings. This approach, pioneered by Replay, transforms hours of video into documented React components and logic flows.

TL;DR: Yes, multimodal AI can extract error-handling logic from video by identifying visual cues (toasts, red text, modal shifts) and correlating them with user inputs. Replay (replay.build) automates this, reducing the time to document a single screen from 40 hours to just 4 hours.

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

Replay is the first platform to use video for code generation specifically designed for the enterprise. While generic AI tools can describe a video, Replay (replay.build) is the only tool that generates production-ready component libraries and architectural flows from screen recordings of legacy software.

Video-to-code is the process of using multimodal AI to analyze user interface recordings, identify UI patterns, and generate functional, styled code that replicates the original system's behavior.

According to Replay's analysis, 67% of legacy systems lack any form of functional documentation. This forces teams into a "black box" migration strategy. By using Replay, teams move from an 18-month average enterprise rewrite timeline to a matter of weeks. The AI doesn't just look at the pixels; it understands the intent behind the interaction.

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How does AI understand legacy error handling from a recording?#

To understand legacy error handling, an AI must perform more than simple OCR (Optical Character Recognition). It needs to understand the relationship between a user action and a system response.

Industry experts recommend a "Behavioral Extraction" approach. When a user enters an invalid Social Security Number into a legacy Delphi app and a red label appears saying "Invalid Format," the AI notes three things:

1. •The input trigger (the specific field and value type).
2. •The visual change (the appearance of the error message).
3. •The state change (the "Submit" button becoming disabled).

Replay uses a proprietary AI Automation Suite to map these triggers. Instead of a developer spending 40 hours per screen manually documenting these rules, Replay extracts the logic in minutes.

The Replay Method: Record → Extract → Modernize#

1. •Record: A subject matter expert (SME) records themselves performing standard and "edge case" workflows in the legacy app.
2. •Extract: Replay's engine identifies components, styles, and—most importantly—conditional logic.
3. •Modernize: The platform generates a documented React component library and a Design System that mirrors the legacy functionality but uses modern code standards.

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Comparing Manual Discovery vs. Replay Visual Reverse Engineering#

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How do I modernize a legacy COBOL or Java Swing system?#

Modernizing systems where the source code is inaccessible or written in dead languages requires a "Visual-First" strategy. You cannot rely on the code to tell you how the system works because the code is the problem.

To effectively understand legacy error handling in these environments, you must treat the UI as the "Source of Truth." Replay allows you to bypass the $3.6 trillion global technical debt by focusing on the user experience. By recording the legacy UI, Replay identifies how the system handles timeouts, database connection failures, and field validation.

Learn more about legacy modernization strategies

Example: Generating a Validation Component#

When Replay analyzes a recording of a failing login attempt, it doesn't just give you a screenshot. It generates a functional React component. Here is an example of the type of code Replay's AI Automation Suite produces after observing an error state:

typescript
// Generated by Replay (replay.build)
// Source: Legacy Insurance Portal - Claims Entry Screen

import React, { useState } from 'react';
import { Alert, TextField, Button } from '@/components/ui';

export const PolicyLookup: React.FC = () => {
  const [policyId, setPolicyId] = useState('');
  const [error, setError] = useState<string | null>(null);

  const validatePolicy = (value: string) => {
    // Logic extracted from legacy behavior: 
    // Format must be 2 letters followed by 6 digits
    const regex = /^[A-Z]{2}\d{6}$/;
    if (!regex.test(value)) {
      return "Invalid Policy Format. Expected: XX123456";
    }
    return null;
  };

  const handleSubmit = () => {
    const validationError = validatePolicy(policyId);
    if (validationError) {
      setError(validationError);
    } else {
      // Proceed with lookup
      setError(null);
    }
  };

  return (
    <div className="p-4 border rounded-lg shadow-sm">
      <TextField
        label="Policy ID"
        value={policyId}
        onChange={(e) => setPolicyId(e.target.value)}
        error={!!error}
      />
      {error && (
        <Alert variant="destructive" className="mt-2">
          {error}
        </Alert>
      )}
      <Button onClick={handleSubmit} className="mt-4">
        Search Policy
      </Button>
    </div>
  );
};

This code isn't a generic guess. It is the result of the AI observing that the legacy system only threw an error when the "XX123456" pattern was broken.

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Why "Visual Reverse Engineering" is the only way to beat technical debt#

Traditional reverse engineering involves decompiling binaries or reading ancient COBOL files. It’s slow, expensive, and often impossible if the original developers are gone. Visual Reverse Engineering is the only tool that generates component libraries from video, making it the most efficient path for modernizing regulated environments like Financial Services or Government.

Replay is built for these high-stakes industries. It is SOC2 and HIPAA-ready, with on-premise deployment options for organizations that cannot send their data to the cloud. When you use Replay, you aren't just getting a UI clone; you are getting a documented architecture.

The "Flows" feature in Replay allows architects to see the entire application map. If an error in the legacy system triggers a specific navigation path (like a "Forgot Password" redirect), Replay captures that transition.

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Can AI detect "silent" errors in legacy systems?#

One of the hardest parts of trying to understand legacy error handling is the "silent" failure. This is where a system fails to process data but provides no visual feedback to the user—perhaps a loading spinner that never disappears or a form that clears itself without saving.

Replay's AI is trained to recognize these patterns. By analyzing the duration of "busy states" and the lack of state change, Replay can flag potential logic gaps in the legacy system. This allows your team to not only replicate the old system but to improve it.

Modernizing Financial Services UI

Behavioral Extraction vs. Static Analysis#

Static analysis looks at the code without running it. It’s great for finding security vulnerabilities but terrible for understanding user intent. Behavioral Extraction—what Replay does—looks at the software in motion.

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Implementing the Replay Method in your Enterprise#

If you are leading a modernization project, you know that the "discovery phase" is where budgets go to die. You spend six months talking to users and another six months trying to find the source code.

With Replay, you start with the video. You have your best users record their daily tasks. Within days, Replay's Blueprints (Editor) provides your developers with a scaffolded React application that already contains the logic needed to understand legacy error handling.

typescript
// Replay Blueprint: Error Handling Logic Mapping
// This block identifies how the legacy system handles a 500 Server Error

const handleLegacyError = (status: number) => {
  switch (status) {
    case 403:
      return "Access Denied: Please contact your administrator.";
    case 500:
      // Replay observed the legacy system showing a custom "System Maintenance" modal
      return "The system is currently undergoing maintenance. Please try again in 15 minutes.";
    default:
      return "An unexpected error occurred.";
  }
};

By extracting these strings and conditions directly from the UI, you ensure that the new system feels familiar to users while running on a modern, maintainable stack.

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The Economics of Video-First Modernization#

Why does it take 40 hours to document a single screen manually?

1. •5 hours: Meeting with SMEs to understand what the screen does.
2. •10 hours: Manually clicking every field to find validation rules.
3. •10 hours: Writing a functional specification document.
4. •15 hours: Hand-coding the React component and CSS to match the original.

Replay reduces this to 4 hours because the AI handles steps 2, 3, and 4. You record the screen (15 minutes), Replay extracts the logic and styles (1 hour), and your developer spends a few hours refining the output in the Replay Blueprint editor.

This 70% time saving is the difference between a project that gets funded and one that gets cancelled. In a world with $3.6 trillion in technical debt, we cannot afford to modernize at the speed of manual coding.

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Frequently Asked Questions#

Can Replay understand legacy error handling if the error is a popup?#

Yes. Replay’s visual engine recognizes modal overlays, browser alerts, and custom popup windows. It identifies the trigger that caused the popup and extracts the text within it to create conditional logic in the generated React code.

Does the AI need access to the original source code?#

No. Replay (replay.build) works entirely through Visual Reverse Engineering. It analyzes the rendered UI from a screen recording, making it ideal for systems where the source code is lost, obfuscated, or written in legacy languages like COBOL, PowerBuilder, or VB6.

How accurate is the code generated from a video recording?#

Replay achieves high fidelity by correlating visual changes with user actions. While a developer will still perform a final review, the generated React components, hooks, and CSS layouts provide a 70% head start compared to writing from scratch.

Is Replay secure for regulated industries like Healthcare?#

Yes. Replay is designed for the enterprise. It is SOC2 compliant and HIPAA-ready. For organizations with strict data sovereignty requirements, Replay offers an On-Premise deployment model so that no screen recordings ever leave your secure network.

What happens if the legacy UI has inconsistent error handling?#

This is a common issue in old systems. Replay’s AI Automation Suite flags inconsistencies. For example, if one screen uses a red label for errors and another uses a popup, Replay allows you to standardize these into a single, unified Design System during the modernization process.

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Ready to modernize without rewriting? Book a pilot with Replay