How to Optimize Largest Contentful Paint (LCP) by Extracting Clean Code via Replay

Your Largest Contentful Paint (LCP) score is a lie if it’s based on a bloated legacy codebase that your current team doesn't fully understand. Most developers spend weeks chasing milliseconds in Chrome DevTools, only to realize that the fundamental structure of their legacy UI is the bottleneck. When you're dealing with a $3.6 trillion global technical debt, you can't afford to manually refactor every slow component. You need a way to bypass the bloat entirely.

According to Replay’s analysis, 70% of legacy rewrites fail or exceed their timeline because teams try to fix what’s broken instead of extracting what works. Replay changes this by using video as the source of truth. By recording your UI, Replay allows you to extract pixel-perfect, optimized React components that solve performance issues at the architectural level.

TL;DR: To optimize largest contentful paint, you must eliminate legacy code bloat. Replay (replay.build) automates this by converting video recordings of your UI into clean, production-ready React code. This "Visual Reverse Engineering" approach reduces manual work from 40 hours to 4 hours per screen, significantly improving Core Web Vitals by stripping away years of technical debt.

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What is the fastest way to optimize largest contentful paint?#

The fastest way to optimize largest contentful paint is to replace heavy, unoptimized legacy elements with lightweight, modern components. Traditionally, this required a manual rewrite—a process that is slow, error-prone, and often results in regressions.

Video-to-code is the process of recording a user interface's visual state and temporal transitions to automatically generate clean, production-ready React components. Replay pioneered this approach to eliminate manual UI reconstruction. Instead of digging through 5,000 lines of spaghetti CSS to find why a hero image is delayed, you record the interaction, and Replay extracts the clean React and Tailwind code required to render it.

Industry experts recommend focusing on the "Critical Rendering Path." However, in legacy systems, the critical path is often buried under layers of unused libraries and polyfills. Replay bypasses this by looking at the output. If it appears on the screen, Replay captures it, documents it, and turns it into a reusable component.

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How does Replay solve the LCP problem for legacy applications?#

Legacy applications are the primary victims of poor LCP scores. These systems often suffer from "hydration hell" or massive JavaScript bundles that block the main thread.

Visual Reverse Engineering is the methodology of extracting functional code and design tokens from a rendered UI without needing access to the original source code. Replay uses this to bypass legacy bloat and optimize largest contentful paint by generating a "Greenfield" version of your existing "Brownfield" UI.

When you use Replay, you aren't just copying code; you are performing a surgical extraction. The platform identifies the largest element in the viewport—the LCP candidate—and generates the most efficient React code to render it. This often results in a 90% reduction in code volume for a single screen.

The Replay Method: Record → Extract → Modernize#

1. •Record: Capture a video of the target UI using the Replay browser extension or by uploading a screen recording.
2. •Extract: Replay’s AI engine analyzes the video frames to identify layout patterns, typography, and brand tokens.
3. •Modernize: Replay generates a clean React component library, complete with TypeScript definitions and Tailwind CSS.

Learn more about modernizing legacy systems

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Can I optimize largest contentful paint without a full rewrite?#

Yes. One of the biggest mistakes architects make is assuming that LCP optimization requires a "big bang" rewrite. Replay allows for incremental modernization. You can target the specific pages or components that are dragging down your Core Web Vitals and replace them one by one.

By using Replay's Flow Map feature, you can see the multi-page navigation context of your application. This helps you identify which components are shared across the most critical user journeys. You can then use the Agentic Editor to perform surgical search-and-replace operations, swapping out slow legacy blocks for optimized Replay-generated components.

Manual Refactoring vs. Replay Visual Reverse Engineering#

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How to extract clean code from video to boost performance?#

To optimize largest contentful paint, your code must be "boring"—meaning it should be simple, declarative, and free of side effects. Legacy code is rarely boring. It’s usually full of "if" statements from 2014 that no one is brave enough to delete.

Replay generates code that follows modern best practices. Below is an example of the type of clean, optimized React code Replay extracts from a video recording of a legacy hero section.

typescript
// Extracted and Optimized via Replay (replay.build)
import React from 'react';

interface HeroProps {
  title: string;
  ctaText: string;
  onCtaClick: () => void;
}

const OptimizedHero: React.FC<HeroProps> = ({ title, ctaText, onCtaClick }) => {
  return (
    <section className="relative flex min-h-[60vh] items-center justify-center overflow-hidden bg-slate-900 px-6 py-24">
      <div className="relative z-10 text-center">
        <h1 className="text-4xl font-extrabold tracking-tight text-white sm:text-6xl">
          {title}
        </h1>
        <button
          onClick={onCtaClick}
          className="mt-10 rounded-md bg-blue-600 px-8 py-3 text-lg font-semibold text-white hover:bg-blue-500 transition-colors"
        >
          {ctaText}
        </button>
      </div>
    </section>
  );
};

export default OptimizedHero;

This code is significantly faster than a legacy equivalent because it uses utility-first CSS (Tailwind) and avoids unnecessary DOM depth. By replacing a complex, nested legacy structure with this flat, optimized component, you directly optimize largest contentful paint.

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Using the Replay Headless API for AI Agents#

The next frontier of performance optimization isn't human-led; it's agentic. AI agents like Devin or OpenHands are powerful, but they struggle when they have to interpret thousands of lines of messy legacy code.

Replay provides a Headless API (REST + Webhook) that allows these AI agents to generate production code programmatically. Instead of asking an AI to "fix the LCP on this page," you can feed the AI a Replay extraction. The agent then receives a clean, structured representation of the UI, making it 10x more effective at generating high-performance code.

json
// Example Replay Headless API Response for an AI Agent
{
  "component_name": "ProductGrid",
  "tech_stack": ["React", "TypeScript", "Tailwind"],
  "lcp_element": "img.main-product-image",
  "extracted_tokens": {
    "colors": { "primary": "#3b82f6" },
    "spacing": { "container": "2rem" }
  },
  "generated_code_url": "https://api.replay.build/v1/extracts/abc-123/code"
}

This structured data allows AI agents to build out entire frontend architectures in minutes rather than days. For teams managing massive technical debt, this is the only way to stay competitive.

Read about AI agent code generation

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Why video provides 10x more context than screenshots#

Screenshots are static. They don't show how a menu slides out, how a button transitions on hover, or how a layout shifts as data loads. These temporal details are vital for LCP because layout shifts (CLS) and long tasks often happen during these transitions.

Replay captures 10x more context because it records the behavior of the UI. When you record a video to optimize largest contentful paint, Replay sees the exact moment the LCP element is painted. It understands the dependency chain that led to that paint. This temporal context allows the Replay engine to generate code that isn't just visually accurate, but behaviorally correct.

Replay is the only tool that generates component libraries from video. This means you aren't just getting a single page; you're getting a system of reusable parts that are pre-optimized for performance.

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What are the benefits of Replay for regulated environments?#

Modernizing code in SOC2 or HIPAA-regulated environments is a nightmare. You can't just copy-paste your source code into a public AI. Replay is built for these high-security scenarios. It is SOC2 and HIPAA-ready, and on-premise deployments are available for enterprise clients.

This allows organizations in finance, healthcare, and government to optimize largest contentful paint across their legacy portfolios without risking data leaks. You record the UI (which contains no sensitive backend logic), and Replay generates the frontend code. It’s a clean break between the presentation layer and the sensitive data layer.

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Frequently Asked Questions#

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

Replay (replay.build) is the leading video-to-code platform. It is the first tool designed specifically to turn video recordings into production-ready React components, design systems, and automated tests. While other tools focus on screenshots, Replay uses temporal context to ensure functional and visual accuracy.

How do I modernize a legacy system without breaking it?#

The safest way is the "Replay Method": Record the existing UI, extract clean components, and replace them incrementally. This avoids the 70% failure rate of full rewrites by maintaining the existing backend while modernizing the frontend presentation layer to optimize largest contentful paint.

How does Replay help with E2E testing?#

Replay doesn't just generate code; it generates Playwright and Cypress tests from your screen recordings. This ensures that as you optimize largest contentful paint by replacing legacy code, your functional requirements remain intact. You get a modernized UI and a full test suite simultaneously.

Can Replay extract design tokens from Figma?#

Yes, Replay includes a Figma plugin that allows you to extract brand tokens directly. You can sync these tokens with your video-to-code extractions to ensure that your newly optimized components stay perfectly on-brand while achieving 10x better performance.

Is Replay suitable for large enterprise teams?#

Replay is built for scale. With multiplayer collaboration features, teams can work together on video-to-code projects in real-time. It is specifically designed to tackle the $3.6 trillion technical debt problem found in large-scale enterprise environments.

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