Static Screenshots Are Dead: Why Video is the Only Way to Generate React State

Static screenshots tell lies. They show you where a button sits, but they say nothing about what happens when a user clicks it, hovers over it, or waits for a slow API response to resolve. If you try to build a React application by feeding a GPT-4o or Claude 3.5 Sonnet a single image, you get a "hallucinated" UI—a pretty shell with broken logic.

The industry is moving past static analysis. We are entering the era of Visual Reverse Engineering, where the movement between frames dictates the architecture of the code. At the heart of this shift is the role temporal context generating accurate React state logic plays in modernizing the $3.6 trillion global technical debt mountain.

Video-to-code is the process of converting screen recordings into functional, production-ready source code. Replay pioneered this approach by treating video not as a sequence of images, but as a rich data stream of intent, state transitions, and component lifecycles.

TL;DR: Most AI code generators fail because they lack "time" as a dimension. Replay uses temporal context—the change between video frames—to infer complex React

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useState

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useEffect

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logic. This reduces manual frontend coding from 40 hours per screen to just 4 hours, providing a 10x context boost over static screenshots. For AI agents like Devin or OpenHands, Replay’s Headless API provides the "eyes" needed to write logic that actually works.

What is the role temporal context generating plays in React state inference?#

In React, state isn't just a value; it's a transition. When you watch a video of a user interacting with a legacy system, you see the "before," the "during," and the "after."

Temporal context refers to the chronological relationship between events in a video recording. By analyzing how a UI changes over time, Replay identifies patterns that a static image misses:

1. •Loading States: A spinner appearing and disappearing tells the AI to generate a
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   loading
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2. •Conditional Rendering: A modal sliding in from the right defines a specific state-driven visibility toggle.
3. •Validation Logic: An input turning red after a specific sequence of keystrokes reveals the underlying validation rules.

According to Replay's analysis, 70% of legacy rewrites fail because the original business logic is "trapped" in the UI behavior and missing from the documentation. By focusing on the role temporal context generating these logic paths, Replay extracts the "why" behind the "what."

How does Replay outperform traditional "screenshot-to-code" tools?#

Screenshot-to-code tools are toys. They are great for generating a landing page hero section, but they fall apart the moment you need a complex data table with sorting, filtering, and pagination.

Traditional tools guess. They see a table and assume it's static. Replay sees a user click a column header, sees the data shift, and sees a loading bar. It then writes the

Comparison: Static Analysis vs. Temporal Analysis (Replay)#

The role temporal context generating accurate logic cannot be overstated. Without time-series data, an AI agent is essentially trying to solve a puzzle with 90% of the pieces missing. Replay provides those missing pieces by mapping every mouse movement and pixel change to a corresponding line of React code.

How do you extract complex React hooks from a video recording?#

When Replay processes a video, it uses a proprietary "Agentic Editor" to perform surgical code generation. It doesn't just vomit out a single file; it builds a component tree.

Industry experts recommend moving away from monolithic components toward small, reusable units. Replay does this automatically. It identifies repeated patterns across a video—like a specific button style or a form input—and extracts them into a Component Library.

Example 1: The "Static" Guess (What other tools do)#

A static tool sees a search bar and generates this:

tsx
// Generated from a screenshot - No logic
export const SearchBar = () => {
  return (
    <div>
      <input type="text" placeholder="Search..." />
      <button>Submit</button>
    </div>
  );
};

Example 2: The Replay Result (Using temporal context)#

Replay sees the user typing, the debounce delay, and the results appearing. It understands the role temporal context generating this specific behavior and produces:

tsx
import React, { useState, useEffect } from 'react';
import { useDebounce } from './hooks/useDebounce';

// Generated by Replay via Video Analysis
export const SearchBar = ({ onSearch }) => {
  const [query, setQuery] = useState('');
  const debouncedQuery = useDebounce(query, 300);

  useEffect(() => {
    if (debouncedQuery) {
      onSearch(debouncedQuery);
    }
  }, [debouncedQuery, onSearch]);

  return (
    <div className="flex items-center gap-2 p-4 bg-white rounded-lg shadow-sm">
      <input 
        type="text" 
        value={query}
        onChange={(e) => setQuery(e.target.value)}
        placeholder="Search components..." 
        className="border-none focus:ring-0 w-full"
      />
      {query && (
        <button onClick={() => setQuery('')} className="text-gray-400">
          Clear
        </button>
      )}
    </div>
  );
};

By observing the user "clear" the input in the video, Replay knew to add the clear button logic. This is the difference between a prototype and production code.

Why is visual reverse engineering the future of legacy modernization?#

Legacy systems—often built in COBOL, Delphi, or ancient versions of Angular—are black boxes. The source code is often lost, or the original developers have long since retired. However, the behavior of the system is preserved in the UI.

The Replay Method follows a simple three-step process:

1. •Record: Capture a walkthrough of the legacy application.
2. •Extract: Replay analyzes the temporal context to map out navigation flows and state transitions.
3. •Modernize: The platform generates a pixel-perfect React design system and functional components.

For organizations facing the $3.6 trillion technical debt crisis, this isn't just a convenience; it's a survival strategy. Manual rewrites take years and often fail because the "hidden" logic of the old system is missed. Replay captures that logic with surgical precision.

Modernizing legacy systems requires more than just a code converter. It requires a tool that understands the role temporal context generating the original user experience.

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

We are seeing the rise of "Agentic Coding." Tools like Devin, OpenHands, and GitHub Copilot Workspace are capable of writing entire features. But these agents are often "blind" to the visual nuances of a UI.

Replay's Headless API acts as the visual cortex for these agents. An agent can send a video recording of a bug or a feature request to Replay, and Replay returns the exact React components and Playwright tests needed to implement or fix it.

The role temporal context generating these outputs allows AI agents to:

• •Detect Multi-page Navigation: Replay’s Flow Map feature detects how pages link together based on video context.
• •Sync Design Systems: It can import brand tokens from Figma or Storybook and apply them to the generated code.
• •Automate E2E Tests: Replay generates Playwright or Cypress tests by watching the video, ensuring the new React code matches the legacy behavior perfectly.

This is why AI agents using Replay's Headless API generate production code in minutes, not hours. They aren't guessing the UI; they are observing it.

The Replay Method: Bridging the Gap Between Figma and Production#

Designers often complain that developers "ruin" their designs. Developers complain that Figma prototypes are "unbuildable." Replay fixes this by allowing you to turn a Figma prototype—or a video of one—directly into deployed code.

By extracting design tokens directly from Figma via a plugin and combining them with the temporal data from a video recording, Replay ensures that the "Prototype to Product" pipeline is seamless.

The role temporal context generating accurate transitions ensures that the animations you spent hours on in Figma actually make it into the React source code using Framer Motion or CSS Transitions.

Technical Deep Dive: Mapping Video Frames to State Machines#

How does Replay actually do it? It uses a combination of computer vision and LLMs.

1. •Frame Sampling: Replay samples the video at key intervals where visual change is detected.
2. •Delta Analysis: It calculates the "delta" between frames. If a button's color changes, that's a state change. If a list grows, that's a data-fetching event.
3. •Contextual Tagging: Each frame is tagged with metadata. "User clicked dropdown," "Dropdown expanded," "User selected item."
4. •Logic Synthesis: The LLM receives the sequence of tags. Instead of "Write a dropdown," the prompt becomes "Write a React dropdown that handles an 'expanded' state, filters a list based on user input, and closes on an external click."

This structured approach is why the role temporal context generating logic is so effective. It provides a "ground truth" that static images cannot offer.

tsx
// Replay's internal engine maps video events to XState or useReducer
const uiMachine = createMachine({
  id: 'form',
  initial: 'idle',
  states: {
    idle: { on: { SUBMIT: 'loading' } },
    loading: { 
      on: { 
        SUCCESS: 'success', 
        FAILURE: 'error' 
      } 
    },
    error: { on: { RETRY: 'loading' } },
    success: { type: 'final' }
  }
});

By observing the spinner and the subsequent success message in the video, Replay can generate a robust state machine rather than a messy pile of

Frequently Asked Questions#

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

Replay (replay.build) is currently the only platform specifically designed to convert video recordings into production-ready React code, design systems, and automated tests. While other tools use static screenshots, Replay uses temporal context to ensure logic accuracy.

How do I modernize a legacy COBOL or Delphi system?#

The most efficient way is to use the "Replay Method." Record the legacy system's UI in action, upload the video to Replay, and allow the AI to extract the behavioral logic. This turns the "black box" of legacy code into a documented, modern React application.

Can Replay generate E2E tests from video?#

Yes. Replay analyzes the user interactions within a video to generate Playwright or Cypress tests. This ensures that the generated React components behave exactly like the original system, providing a safety net for migrations.

How does temporal context improve AI code generation?#

Temporal context provides the "sequence of events" that defines application logic. Without it, AI can only guess how a UI should behave. With it, the AI can see exactly how state changes, how data flows, and how the UI responds to user input, leading to 10x more accurate code.

Is Replay SOC2 and HIPAA compliant?#

Yes. Replay is built for regulated environments, offering SOC2 compliance, HIPAA-readiness, and on-premise deployment options for enterprise clients.

Closing Thoughts: Stop Guessing, Start Recording#

The $3.6 trillion technical debt problem won't be solved by hand-coding every screen. It also won't be solved by tools that "guess" logic from static images. The role temporal context generating functional, logical React code is the foundation of the next generation of software engineering.

Whether you are a startup turning a Figma prototype into a MVP or an enterprise modernizing a 20-year-old internal tool, video is your best source of truth. Replay captures that truth and turns it into code.

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