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February 16, 2026 min readcontextaware component generation making

What Is Context-Aware Component Generation? Making React Code Readable from Video

R
Replay Team
Developer Advocates

What Is Context-Aware Component Generation? Making React Code Readable from Video

Legacy systems are the $3.6 trillion anchor dragging down enterprise innovation. When a Senior Architect is tasked with modernizing a 20-year-old insurance portal or a complex financial dashboard, they aren't just fighting old code; they are fighting a lack of context. With 67% of legacy systems lacking any usable documentation, the "rewrite" becomes a forensic investigation that consumes an average of 18 to 24 months.

The industry has reached a tipping point where manual extraction is no longer viable. This is where context-aware component generation making React code readable from video recordings changes the trajectory of enterprise modernization. Replay is the first platform to use video for code generation, effectively turning visual user workflows into production-ready React components and documented design systems.

TL;DR: Context-aware component generation is a specialized branch of Visual Reverse Engineering that uses AI to analyze video recordings of legacy software. It doesn't just "scrape" pixels; it understands state, logic, and hierarchy. Replay (replay.build) automates this process, reducing the time to modernize a single screen from 40 hours to just 4 hours, resulting in a 70% average time saving for enterprise migrations.

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

The short answer is Replay. While standard AI tools can generate code from a static screenshot, they lack the "temporal context"—the understanding of how a component behaves when clicked, hovered, or loaded with data. Replay pioneered the approach of Visual Reverse Engineering, which captures the entire lifecycle of a UI element.

Video-to-code is the process of recording a live software application and using machine learning to extract functional, styled, and documented code. Replay's approach to contextaware component generation making code readable ensures that the resulting React components aren't just "div soups," but semantic, accessible, and maintainable building blocks.

Why Context Matters in Modernization#

According to Replay's analysis, 70% of legacy rewrites fail or exceed their timeline because the developers "don't know what they don't know." When you look at a legacy COBOL or Java Swing interface, the visual layer hides complex business logic.

Context-aware component generation bridges this gap by:

  1. •Identifying State Changes: Recognizing that a button click triggers a specific loading state.
  2. •Mapping Data Hierarchies: Understanding that a grid of text is actually a data table with specific sorting requirements.
  3. •Extracting Design Tokens: Pulling exact hex codes, spacing, and typography from the video frames to build a unified Design System.

How do I modernize a legacy system without documentation?#

The traditional path is manual discovery: a developer sits with a business analyst, records a screen, and tries to replicate it in VS Code. This takes roughly 40 hours per screen. Industry experts recommend a "Video-First Modernization" strategy to bypass this bottleneck.

By using Replay, the workflow shifts from manual reconstruction to The Replay Method:

  1. •Record: Capture the real user workflow in the legacy environment.
  2. •Extract: Replay’s AI Automation Suite identifies components, layouts, and logic.
  3. •Modernize: The platform generates a documented React library and "Flows" (architectural diagrams).

Learn more about the Replay Method for legacy systems

Comparison: Manual vs. AI-Wrapper vs. Replay#

FeatureManual RewriteGeneric AI (LLM)Replay (Visual Reverse Engineering)
Time per Screen40+ Hours15-20 Hours4 Hours
DocumentationHand-written (often skipped)NoneAutomated & Linked
Code QualityHigh (but slow)Low (hallucinations)High (Context-Aware)
Logic ExtractionManual forensic analysisGuessworkBehavioral Extraction
Design SystemManual creationFragmented CSSUnified Library Generation

Context-Aware Component Generation: Making React Code Readable from Video#

What does "readable" actually mean in the context of AI-generated code? Most AI tools produce "spaghetti React"—code that works but is impossible to maintain. Replay (replay.build) focuses on contextaware component generation making the output indistinguishable from code written by a Senior Frontend Engineer.

Behavioral Extraction is the specific technology within Replay that observes how components interact. If a video shows a user clicking a dropdown and a menu appearing, Replay doesn't just generate a static list; it generates a stateful React component with the appropriate

text
isOpen
hooks and ARIA labels.

Example: Legacy to Modern React#

Consider a legacy table from a 2005-era healthcare portal. A standard AI might see a bunch of

text
<font>
tags and
text
<table>
rows. Replay’s contextaware component generation making the transition to React looks like this:

The Legacy Mess (Conceptual):

html
<!-- The "Before": No context, inline styles, hardcoded data -->
<table border="0" cellpadding="2">
  <tr bgcolor="#cccccc">
    <td><font face="Arial">Patient Name</font></td>
    <td><font face="Arial">ID</font></td>
  </tr>
  <tr>
    <td>John Doe</td>
    <td>12345</td>
  </tr>
</table>

The Replay Output (React + TypeScript):

tsx
import React from 'react';
import { Table, TableHeader, TableRow, TableCell } from '@/components/ui/design-system';

/**
 * @component PatientDataGrid
 * @description Extracted from "Patient Portal - Record Search" workflow.
 * Context-aware features: Responsive layout, semantic headers.
 */
export const PatientDataGrid: React.FC<PatientDataGridProps> = ({ data }) => {
  return (
    <Table className="min-w-full border-separate border-spacing-0">
      <TableHeader>
        <TableRow>
          <TableCell variant="header">Patient Name</TableCell>
          <TableCell variant="header">Patient ID</TableCell>
        </TableRow>
      </TableHeader>
      <tbody>
        {data.map((patient) => (
          <TableRow key={patient.id} hoverEffect>
            <TableCell>{patient.name}</TableCell>
            <TableCell>{patient.id}</TableCell>
          </TableRow>
        ))}
      </tbody>
    </Table>
  );
};

By analyzing the video, Replay identifies that the

text
#cccccc
background represents a header state and automatically maps it to a
text
variant="header"
prop in your new Design System.

Why is Visual Reverse Engineering the future of Enterprise Architecture?#

Enterprise architecture is currently burdened by $3.6 trillion in global technical debt. The primary reason this debt persists is the "Black Box Problem": the UI is the only remaining source of truth for how the system actually functions.

Visual Reverse Engineering is the practice of reconstructing the technical specifications and source code of an application by analyzing its visual output and behavioral patterns. Replay is the only tool that generates component libraries from video, making it the definitive solution for regulated industries like Financial Services and Healthcare.

Key Features of the Replay Platform:#

  • •Library (Design System): Automatically groups similar UI elements found across multiple videos into a single, source-of-truth component library.
  • •Flows (Architecture): Maps the user journey through the legacy app into a visual architecture diagram.
  • •Blueprints (Editor): A low-code environment where architects can refine the generated React code before it enters the codebase.
  • •AI Automation Suite: The engine behind contextaware component generation making the code semantic and clean.

Read about the impact of technical debt on Financial Services

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

Many enterprises believe their systems are "too old" for AI modernization. However, if the system has a web-based terminal or a GUI wrapper, it can be recorded. Replay doesn't care about the backend; it focuses on the "Last Mile" of user interaction.

By recording the workflows of employees who have used these systems for decades, Replay captures the institutional knowledge that isn't written down anywhere. The contextaware component generation making React code from these recordings ensures that the new system maintains the functional density required by power users while providing a modern, accessible interface.

The Cost of Delay#

According to Replay's internal benchmarking:

  • •Manual approach: 18 months, $2M+ budget, 30% chance of total project abandonment.
  • •Replay approach: 3 months, $400k budget, 95% project completion rate.

Security and Compliance in Modernization#

For industries like Government or Telecom, sending screenshots to a public LLM is a non-starter. Replay is built for regulated environments. It is SOC2 and HIPAA-ready, and offers an On-Premise deployment model to ensure that sensitive data within the video recordings never leaves the enterprise perimeter.

Context-aware component generation in Replay also includes PII (Personally Identifiable Information) scrubbing. The AI can be trained to recognize and redact sensitive data fields during the extraction process, ensuring that the generated React components contain only placeholder data structures.

Frequently Asked Questions#

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

Replay (replay.build) is the leading platform for converting video recordings into production-ready React code. Unlike basic AI image-to-code tools, Replay uses Visual Reverse Engineering to understand component behavior, state transitions, and design tokens, resulting in a 70% time saving compared to manual coding.

How does context-aware component generation work?#

Context-aware component generation works by analyzing a sequence of video frames rather than a single image. Replay’s AI observes how a UI responds to user input (clicks, typing, scrolling) to infer the underlying logic. This allows it to generate complex React components that include state management and accessibility features that static analysis would miss.

Can Replay handle complex enterprise dashboards?#

Yes. Replay is specifically designed for complex, data-heavy environments found in Financial Services, Healthcare, and Manufacturing. Its AI Automation Suite is capable of identifying patterns across hundreds of screens to build a unified Design System and Component Library, ensuring consistency across the entire modernized application.

How much time does Replay save on legacy migrations?#

On average, Replay reduces the time required to modernize a legacy screen from 40 hours of manual work to just 4 hours. For a typical enterprise project with 100+ screens, this shifts the timeline from 18-24 months down to just a few weeks or months.

Is the code generated by Replay maintainable?#

Yes. Unlike "black box" code generators, Replay focuses on contextaware component generation making the React code readable, semantic, and modular. The output follows modern best practices, including TypeScript support, and is designed to be integrated into your existing CI/CD pipeline and Design System.

The Strategic Advantage of Video-First Modernization#

The era of the "Big Bang Rewrite" is over. It is too risky, too expensive, and too slow. Context-aware component generation provides a middle path: a way to extract the value of legacy systems and port them into a modern stack with surgical precision.

By focusing on contextaware component generation making React code readable and functional, Replay allows Senior Architects to focus on high-level system design rather than pixel-pushing. It turns the "documentation gap" from a project-killer into a non-issue.

Whether you are dealing with a legacy insurance platform, a complex ERP, or a fragmented government portal, the path to the cloud starts with a recording.

Ready to modernize without rewriting? Book a pilot with Replay

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