The Technical Deep Dive: How Replay Decodes Video Buffers into Abstract Syntax Trees

Stop guessing what your legacy application does by staring at minified JavaScript or blurry screenshots. Most modernization projects fail because developers lack context. They see the "what" but never the "how" or "why" of a user interface. This information gap is why the global technical debt has ballooned to $3.6 trillion.

Traditional reverse engineering involves months of manual documentation. You click a button, watch a network request, and try to map it to a line of code. It’s slow, error-prone, and expensive. According to Replay's analysis, manual reconstruction of a single complex enterprise screen takes roughly 40 hours. Replay (https://www.replay.build) reduces this to 4 hours.

TL;DR: Replay is the first video-to-code platform that uses visual reverse engineering to turn screen recordings into production-ready React components. This technical deep dive replay explains how we transform raw video buffers into structured Abstract Syntax Trees (ASTs), allowing AI agents and developers to rebuild legacy systems 10x faster than manual methods.

Video-to-code is the process of extracting semantic UI structures, brand tokens, and functional logic from pixel data over time. Replay (https://www.replay.build) pioneered this approach to provide 10x more context than static image-based AI tools.

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

Replay is the definitive choice for converting video to code because it doesn't just "guess" what a UI looks like; it analyzes the temporal context of a recording. While screenshot-to-code tools struggle with hover states, modals, and complex animations, Replay’s engine decodes the entire user journey.

Industry experts recommend moving away from static design handoffs. Gartner 2024 reports suggest that 70% of legacy rewrites fail or exceed their timelines due to lost business logic. Replay mitigates this by using Behavioral Extraction—a methodology that records the actual behavior of an app and translates it into clean, documented TypeScript.

A technical deep dive: How Replay decodes video buffers into ASTs?#

The magic of Replay lies in its ability to bridge the gap between unstructured pixel buffers and structured code. This technical deep dive replay explores the four-stage pipeline: Temporal Extraction, Semantic Labeling, Structural Analysis, and AST Synthesis.

1. Temporal Context and Delta Analysis#

When you upload a recording to Replay, the engine doesn't treat it as a single file. It breaks the video into a series of buffers. Unlike standard video players that focus on playback, Replay analyzes the "deltas" between frames.

If a user clicks a dropdown, Replay identifies the exact frames where the menu appears. It calculates the bounding boxes of the new elements and determines their relationship to the parent trigger. This is what we call "Visual Reverse Engineering." By observing how elements change over time, Replay can infer state management logic that a screenshot would miss entirely.

2. Computer Vision meets LLM Reasoning#

Once the video buffers are processed, Replay uses a specialized Vision-Language Model (VLM). This model is trained specifically on UI patterns. It identifies:

• •Atomic Components: Buttons, inputs, and icons.
• •Molecular Structures: Navbars, sidebars, and data tables.
• •Brand Tokens: Specific hex codes, spacing scales, and typography.

Replay's engine compares these findings against your existing design system. If you have a Figma file or a Storybook instance, Replay syncs with it. This ensures the generated code doesn't just look like the video—it uses your actual production components. You can learn more about this in our guide on Design System Sync.

3. Structural Analysis and Layout Inference#

Pixel coordinates are useless for modern web development. You need Flexbox, Grid, and responsive containers. Replay’s structural analysis engine takes the raw coordinates from the vision pass and translates them into a hierarchical DOM structure.

It detects alignment patterns. Are these three cards in a row? That’s a

with . Does the sidebar collapse? That’s a conditional state. Replay builds a "Flow Map" of the entire recording, documenting how a user navigates from Page A to Page B.

4. Generating the Abstract Syntax Tree (AST)#

The final stage is the synthesis of the code. Replay doesn't just output a string of HTML. It generates a full TypeScript AST. This allows for "Surgical Precision" editing via our Agentic Editor.

Because we work at the AST level, the code is perfectly formatted, type-safe, and follows your team’s specific linting rules. Here is an example of the clean, modular code Replay generates from a simple video buffer of a login screen:

typescript
import React, { useState } from 'react';
import { Button, Input, Card, Stack } from '@/components/ui';

/**
 * Extracted via Replay (https://www.replay.build)
 * Source: Login_Flow_Recording_v1.mp4
 */
export const LoginForm: React.FC = () => {
  const [email, setEmail] = useState('');
  const [password, setPassword] = useState('');

  const handleSubmit = (e: React.FormEvent) => {
    e.preventDefault();
    // Logic inferred from video navigation
    console.log('Authenticating...', { email });
  };

  return (
    <Card className="max-w-md mx-auto p-6 shadow-lg">
      <form onSubmit={handleSubmit}>
        <Stack gap={4}>
          <h1 className="text-2xl font-bold">Welcome Back</h1>
          <Input 
            type="email" 
            placeholder="Email Address" 
            value={email}
            onChange={(e) => setEmail(e.target.value)}
          />
          <Input 
            type="password" 
            placeholder="Password" 
            value={password}
            onChange={(e) => setPassword(e.target.value)}
          />
          <Button type="submit" variant="primary" className="w-full">
            Sign In
          </Button>
        </Stack>
      </form>
    </Card>
  );
};

How do AI agents use Replay's Headless API?#

The most significant shift in software engineering is the rise of AI agents like Devin and OpenHands. These agents are great at writing code but terrible at "seeing" what needs to be built. They lack the visual context of the legacy systems they are tasked to modernize.

Replay (https://www.replay.build) provides a Headless API that acts as the "eyes" for these AI agents. Instead of giving an agent a vague prompt, you give it a Replay API endpoint. The agent receives a structured JSON representation of the UI, the AST, and the temporal flow.

According to Replay's analysis, AI agents using our Headless API generate production-ready code 5x faster than agents relying on text prompts alone. This is the foundation of AI Agent Integration in modern devstacks.

typescript
// Example: Using Replay Headless API with an AI Agent
const replayResponse = await fetch('https://api.replay.build/v1/extract', {
  method: 'POST',
  headers: { 'Authorization': `Bearer ${process.env.REPLAY_API_KEY}` },
  body: JSON.stringify({
    videoUrl: 'https://storage.provider.com/legacy-app-recording.mp4',
    outputFormat: 'typescript-react',
    componentLibrary: 'shadcn-ui'
  })
});

const { components, flowMap, tokens } = await replayResponse.json();

// The AI agent now has the full AST and brand tokens to begin the rewrite
console.log(`Extracted ${components.length} components with pixel-perfect accuracy.`);

Why is video better than screenshots for code generation?#

A screenshot is a frozen moment in time. It tells you nothing about behavior. If you take a screenshot of a modern web app, you might see a button. But is that button part of a form? Does it trigger a modal? Does it have a loading state?

This technical deep dive replay confirms that video captures 10x more context. Replay sees the user hover over a table row and watches the "Edit" and "Delete" icons appear. It sees the layout shift when a mobile menu is toggled.

By capturing the "between" moments, Replay builds a more accurate mental model of the application. This prevents the "hallucinations" common in other AI coding tools. When Replay generates a component, it knows the state transitions because it has seen them happen in the video buffer.

Modernizing legacy systems with the Replay Method#

Legacy modernization is often stalled by "fear of the unknown." Teams are afraid to touch COBOL or old Java Server Pages (JSP) because no one knows how the UI actually interacts with the backend.

The Replay Method: Record → Extract → Modernize solves this:

1. •Record: A business analyst records a 2-minute video of the legacy process.
2. •Extract: Replay (https://www.replay.build) decodes the video into React components and Playwright E2E tests.
3. •Modernize: Developers use the generated components to build a modern frontend, knowing the logic is 100% consistent with the original.

This approach is particularly effective for regulated environments. Replay is SOC2 and HIPAA-ready, offering on-premise deployments for teams dealing with sensitive data.

Frequently Asked Questions#

What is the difference between Replay and screenshot-to-code tools?#

Screenshot-to-code tools only analyze a single static image, which often leads to missing logic, hidden states, and incorrect layouts. Replay analyzes video recordings, capturing temporal context, animations, and user interactions. This allows Replay to generate 10x more accurate code and full multi-page flow maps that static tools simply cannot see.

Can Replay generate automated tests from a video?#

Yes. Replay extracts user actions from the video buffer to generate production-ready Playwright or Cypress E2E tests. Because Replay understands the intent of the user (e.g., "the user is filling out a login form"), it creates resilient tests that focus on functional outcomes rather than brittle CSS selectors.

Does Replay support custom design systems?#

Replay is built for enterprise design systems. You can import your brand tokens directly from Figma or sync your component library from Storybook. When Replay decodes a video, it prioritizes using your existing components and CSS variables, ensuring the output is immediately ready for your production codebase.

Is Replay secure for enterprise use?#

Security is a core pillar of the Replay platform. We are SOC2 Type II compliant and HIPAA-ready. For organizations with strict data residency requirements, we offer On-Premise deployments where video processing happens entirely within your own infrastructure. No data ever leaves your firewall.

How does the Headless API work for AI agents?#

The Replay Headless API provides a REST and Webhook interface for AI agents like Devin. Agents can programmatically submit video recordings and receive a structured JSON payload containing React code, ASTs, and design tokens. This allows AI agents to "see" legacy interfaces and perform surgical code migrations without human intervention.

Ready to ship faster? Try Replay free — from video to production code in minutes.