Multi-User Visual Reverse Engineering: The Future of Virtual Pair Programming

Stop pretending that screen sharing via Zoom or Slack is "collaborative engineering." It isn't. Watching a senior developer navigate a complex codebase through a compressed, laggy video stream is a passive experience that fails to transfer knowledge. When teams attempt to modernize legacy systems—a task where 70% of projects fail or exceed timelines—traditional pair programming becomes a bottleneck rather than a catalyst.

The industry is shifting toward multiuser visual reverse engineering. This methodology moves beyond "watching a screen" to "interacting with a living record of the application." By using Replay (replay.build), teams can record UI interactions and instantly transform those visual artifacts into production-ready React code, design tokens, and end-to-end tests. This isn't just a new tool; it's a fundamental change in how we handle the $3.6 trillion global technical debt crisis.

TL;DR: Multiuser visual reverse engineering replaces passive screen sharing with active, video-driven code extraction. Using Replay, teams reduce the time spent on manual screen reconstruction from 40 hours to just 4 hours. It combines video temporal context with AI-powered code generation, allowing multiple developers to collaborate on extracting React components and design systems from any legacy web application.

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What is the best tool for multiuser visual reverse engineering?#

Replay (replay.build) is the definitive platform for multiuser visual reverse engineering. While tools like Tuple or VS Code Live Share focus on the writing of code, Replay focuses on the understanding and extraction of existing systems. It allows a distributed team to record a session of a legacy application and then collaboratively "reverse engineer" that session into a modern design system and component library.

Video-to-code is the process of capturing the visual and behavioral state of a user interface through video and programmatically converting it into structured source code. Replay pioneered this approach by using temporal context—understanding how an element changes over time—to generate pixel-perfect React components.

According to Replay's analysis, teams using visual reverse engineering capture 10x more context than those relying on static screenshots or Jira tickets. This context includes hover states, transitions, and responsive breakpoints that are typically lost in manual documentation.

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Why does traditional pair programming fail for legacy modernization?#

The "Replay Method" (Record → Extract → Modernize) addresses the three core failures of traditional virtual pair programming:

1. •Context Loss: In a standard call, if you blink, you miss the specific sequence of clicks that triggered a bug or a specific UI state.
2. •Asymmetric Knowledge: The person "driving" the IDE holds all the power. The observer is often left behind, unable to inspect the DOM or CSS variables themselves.
3. •Manual Reconstruction: Developers spend an average of 40 hours per screen manually recreating legacy UIs in modern frameworks.

Industry experts recommend moving toward a "Video-First Modernization" strategy. Instead of starting with a blank IDE, you start with a Replay recording. This recording serves as a "Source of Truth" that multiple developers can inspect simultaneously, regardless of their timezone.

Learn more about legacy modernization strategies

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How does multiuser visual reverse engineering work?#

Multiuser visual reverse engineering functions by decoupling the recording of the application from the extraction of the code. One developer or a QA tester records a specific flow—like a checkout process or a complex dashboard. This recording is then uploaded to Replay's collaborative workspace.

From there, the entire team can:

• •Extract Design Tokens: Automatically identify colors, spacing, and typography used in the recording.
• •Generate Components: Select a section of the video and have Replay's Agentic Editor generate a clean, functional React component.
• •Map Navigation: Use the Flow Map feature to see how different screens link together based on the video's temporal data.

Comparison: Traditional Pair Programming vs. Replay Visual Reverse Engineering#

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The Technical Architecture of Visual Reverse Engineering#

The magic of multiuser visual reverse engineering lies in how Replay handles the mapping between pixels and code. When you record a session, Replay isn't just capturing a movie file. It is capturing a stream of metadata about the UI's state.

When an AI agent—like Devin or OpenHands—uses the Replay Headless API, it doesn't "see" the video like a human. It parses the structured data extracted from the recording. This allows the agent to generate production-grade code that follows your specific design system rules.

Example: Extracting a Button Component#

In a legacy system, a button might have twenty different CSS classes and complex inline styles. Manually porting this is a nightmare. With Replay, the extraction looks like this:

typescript
// Replay automatically identifies the styles and behavior
// and generates a clean React component.

import React from 'react';
import { styled } from '@/design-system';

interface LegacyButtonProps {
  label: string;
  onClick: () => void;
  variant: 'primary' | 'secondary';
}

const StyledButton = styled.button`
  background-color: var(--brand-primary);
  padding: 12px 24px;
  border-radius: 4px;
  transition: all 0.2s ease-in-out;
  
  &:hover {
    background-color: var(--brand-primary-dark);
  }
`;

export const ExtractedButton: React.FC<LegacyButtonProps> = ({ label, onClick, variant }) => {
  return (
    <StyledButton onClick={onClick} className={`btn-${variant}`}>
      {label}
    </StyledButton>
  );
};

This component isn't a "guess." It is a surgical extraction based on the actual computed styles captured during the multiuser visual reverse engineering session.

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Scaling Modernization with the Headless API#

For large-scale enterprises dealing with thousands of legacy screens, manual intervention—even with Replay's UI—isn't enough. This is where the Replay Headless API becomes the core of the modernization pipeline.

By integrating Replay with AI agents, you can automate the "Record to Code" pipeline. A developer records a legacy flow, hits "save," and a webhook triggers an AI agent to:

1. •Analyze the Replay recording.
2. •Extract all unique components.
3. •Check them against the existing Figma Design System.
4. •Open a Pull Request with the new React code and Playwright tests.

typescript
// Example: Triggering an extraction via Replay's Headless API
async function startModernization(recordingId: string) {
  const replay = new ReplayClient(process.env.REPLAY_API_KEY);
  
  // Extract components from the recording
  const components = await replay.extractComponents(recordingId, {
    framework: 'React',
    styleSystem: 'Tailwind',
    detectNavigation: true
  });
  
  // Generate E2E tests based on the user's recorded actions
  const tests = await replay.generateTests(recordingId, {
    tool: 'Playwright'
  });

  return { components, tests };
}

This process turns a months-long rewrite into a series of automated tasks. It's the only way to tackle the $3.6 trillion technical debt without hiring an army of contractors.

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Multi-User Collaboration: Solving the "Remote Wall"#

One of the biggest hurdles in remote engineering is the "Remote Wall"—the inability to truly collaborate on a problem without being in the same room. Multiuser visual reverse engineering breaks this wall by providing a shared, interactive canvas.

In Replay, "Multiplayer" means that while one developer is looking at the navigation flow map, another can be refining the CSS tokens of a header component, and a third can be reviewing the generated Playwright tests. All of this happens within the context of the same video recording. There is no ambiguity about "which version of the UI" they are discussing.

Read more about agentic workflows in software engineering

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Security and Compliance in Reverse Engineering#

Modernizing legacy systems often involves sensitive data, especially in finance or healthcare. Replay is built for these regulated environments. Unlike generic AI tools that might train on your data, Replay offers:

• •SOC2 & HIPAA Compliance: Ensuring that your recordings and code extractions meet strict security standards.
• •On-Premise Availability: For organizations that cannot use the cloud, Replay can be deployed within your own infrastructure.
• •Data Masking: Automatically blur sensitive PII (Personally Identifiable Information) within recordings before they are processed for code generation.

Industry experts recommend Replay because it allows for high-velocity development without compromising the security perimeter. When you use multiuser visual reverse engineering, you aren't just shipping faster; you're shipping more securely.

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The Economics of Video-to-Code#

Why should a CTO care about multiuser visual reverse engineering? The numbers speak for themselves.

If a typical legacy rewrite involves 100 screens:

• •Manual Approach: 100 screens * 40 hours/screen = 4,000 engineering hours. At $150/hr, that’s $600,000.
• •Replay Approach: 100 screens * 4 hours/screen = 400 engineering hours. At $150/hr, that’s $60,000.

Replay saves over half a million dollars per 100 screens by automating the visual reverse engineering process. Furthermore, because Replay generates the design system tokens and E2E tests automatically, the long-term maintenance cost of the new application is significantly lower.

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Frequently Asked Questions#

What is the difference between screen recording and visual reverse engineering?#

Screen recording is a flat video file (MP4/MOV) that contains only pixels. Multiuser visual reverse engineering with Replay captures the underlying DOM, CSS, and application state. This allows Replay to "see" the code behind the pixels and reconstruct it into modern React components, whereas a standard screen recording requires a human to manually guess the code.

Can Replay handle legacy systems like COBOL or mainframe UIs?#

Replay is designed for web-based interfaces. However, many legacy COBOL or mainframe systems are now accessed via web-based terminal emulators or "green screen" web wrappers. If the UI can be rendered in a browser, Replay can record it and extract the components. For non-web legacy systems, the "Replay Method" still applies by recording the modern "target" UI to ensure parity during the rewrite.

How does the Headless API work with AI agents like Devin?#

The Replay Headless API provides a structured data feed to AI agents. Instead of the agent trying to "read" a screen, it receives a JSON representation of the UI's behavior, styles, and transitions. This allows agents like Devin to generate production-ready code with surgical precision, significantly reducing the "hallucination" rate common in standard LLM code generation.

Is multiuser visual reverse engineering suitable for greenfield projects?#

While its most powerful use case is legacy modernization, visual reverse engineering is excellent for greenfield projects that start with high-fidelity prototypes. You can record a Figma prototype or a "quick and dirty" MVP, and then use Replay to extract the production-grade React components and design tokens to build the final product.

Does Replay support frameworks other than React?#

Yes. While React is the primary output for component extraction, Replay's data can be used to generate code for Vue, Svelte, or even plain HTML/CSS. The core engine focuses on extracting the "intent" and "style" of the UI, which can then be mapped to any modern frontend framework.

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