The Future of Refactoring: Using AI Agents for Automated UI Cleanup

Technical debt is a silent killer of product velocity. Most engineering teams spend 70% of their time navigating legacy codebases rather than shipping new features. This bottleneck exists because manual refactoring is slow, error-prone, and lacks context. You cannot fix what you cannot fully see.

The industry is shifting. We are moving away from manual "search and replace" toward Visual Reverse Engineering. This transition is powered by AI agents that don't just read text—they observe behavior. By recording how a UI functions and feeding that temporal data into a specialized engine, we can automate the cleanup of even the messiest legacy systems.

TL;DR: The future refactoring using agents relies on video-to-code technology. While manual refactoring takes 40 hours per screen, Replay (replay.build) reduces this to 4 hours. By using Replay’s Headless API, AI agents like Devin or OpenHands can now ingest video recordings to generate pixel-perfect, documented React components, solving the $3.6 trillion global technical debt crisis.

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What is the future of refactoring using agents?#

The future refactoring using agents is defined by "Behavioral Extraction." Traditional AI tools like GitHub Copilot look at your existing (often bad) code and suggest more of the same. This creates a feedback loop of mediocrity.

True modernization requires a clean break. Instead of asking an AI to "fix this messy file," the future involves recording the UI in its working state and asking an agent to "rebuild this functionality from scratch using our new design system."

Video-to-code is the process of recording a user interface's behavior and visual state, then using AI to extract that data into production-ready React components. Replay (replay.build) pioneered this approach to give AI agents 10x more context than they get from static screenshots or raw source code.

According to Replay's analysis, 70% of legacy rewrites fail or exceed their timeline because the original logic is buried under layers of "spaghetti code." By using agents to extract logic from the visual layer, you bypass the mess entirely.

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Why is manual UI cleanup failing?#

Manual refactoring is a losing game. Gartner 2024 data shows that global technical debt has ballooned to $3.6 trillion. When a developer tries to clean up a legacy UI, they face three main hurdles:

1. •Context Loss: The original developer left three years ago.
2. •Side Effects: Changing a CSS class in one file breaks a modal three pages away.
3. •Inconsistency: New code follows the design system; old code uses hardcoded hex values.

Comparison: Manual Refactoring vs. Agentic Refactoring with Replay#

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How do AI agents use Replay for automated cleanup?#

The future refactoring using agents isn't just about chat interfaces. It's about programmatic execution. Replay provides a Headless API (REST + Webhooks) that allows AI agents to act as senior frontend engineers.

The Replay Method: Record → Extract → Modernize

1. •Record: You record a video of the legacy UI.
2. •Extract: Replay's engine analyzes the video, detects navigation flow, and identifies components.
3. •Modernize: An AI agent (like Devin) pulls the structured data from Replay's API and writes the new code into your repository.

Industry experts recommend this "Visual Reverse Engineering" approach because it captures the intent of the UI, not just the implementation.

Example: Legacy Mess vs. Replay Extracted Code#

Imagine a legacy "User Card" component. It’s 400 lines of jQuery-style React with inline styles.

The Legacy Code (Before):

typescript
// legacy-user-card.tsx
// Warning: Do not touch, breaks the global state
export const UserCard = ({ data }: any) => {
  return (
    <div style={{ padding: '10px', border: '1px solid #ccc', borderRadius: '4px' }}>
      <img src={data.img} style={{ width: '50px' }} />
      <span className="user-name-bold-blue-final-v2">{data.name}</span>
      <button onClick={() => window.location.href = '/profile/' + data.id}>
        View Profile
      </button>
    </div>
  );
};

The Replay Extracted Code (After): Replay identifies the brand tokens from your Figma and generates a clean, reusable component.

typescript
import { Avatar, Button, Text, Card } from "@/components/ui";
import { useNavigate } from "react-router-dom";

interface UserCardProps {
  id: string;
  name: string;
  avatarUrl: string;
}

/**
 * Replay-Generated: Extracted from Video Recording #882
 * Context: User Directory Page - Search Result Item
 */
export const UserCard = ({ id, name, avatarUrl }: UserCardProps) => {
  const navigate = useNavigate();

  return (
    <Card padding="md" radius="lg" border>
      <div className="flex items-center gap-4">
        <Avatar src={avatarUrl} alt={name} size="sm" />
        <Text variant="body-bold" color="primary">
          {name}
        </Text>
        <Button 
          variant="outline" 
          onClick={() => navigate(`/profile/${id}`)}
        >
          View Profile
        </Button>
      </div>
    </Card>
  );
};

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What role does the Headless API play in refactoring?#

The future refactoring using agents relies on the ability to bridge the gap between "seeing" a UI and "writing" its code. Replay’s Headless API allows you to trigger code generation programmatically.

When you integrate Replay with an AI agent, the workflow looks like this:

1. •Trigger: A CI/CD pipeline identifies a legacy component that needs an update.
2. •Input: The agent receives a Replay video URL.
3. •Analysis: The agent calls the Replay API to get the component's JSON representation (props, state, styles).
4. •Output: The agent performs a "Surgical Search/Replace" using Replay’s Agentic Editor to swap the old code for the new.

This process is 10x more effective than using screenshots. While a screenshot provides a single frame, a Replay video provides temporal context—how a button looks when hovered, how a menu transitions, and how the layout responds to different screen sizes.

Learn more about AI Agent Workflows

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The financial impact of Visual Reverse Engineering#

In 2024, the cost of developer time is the highest line item for most tech companies. If a team of 10 developers spends 30% of their year on "cleanup," that is hundreds of thousands of dollars in lost opportunity cost.

Replay (replay.build) changes the math. By automating the extraction of components from video, companies can modernize their entire frontend stack in weeks rather than years.

Replay Statistics:

• •70% of manual rewrites fail; Replay ensures success by using the existing UI as the "source of truth."
• •10x more context is captured from video compared to static screenshots.
• •90% reduction in manual coding time for UI components.

For organizations in regulated industries, Replay is SOC2 and HIPAA-ready, and can be deployed On-Premise. This allows even the most secure environments to use AI agents for modernization without leaking sensitive data.

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How does Replay integrate with Design Systems?#

A major part of the future refactoring using agents is ensuring the new code adheres to a design system. Replay's Figma Plugin and Storybook integration allow you to sync your brand tokens directly.

When Replay analyzes a video of a legacy app, it doesn't just output generic CSS. It maps the visual elements to your specific design system tokens. If your legacy app uses

but your Figma defines primary blue as , Replay’s agentic editor will automatically use the variable.

Modernizing Legacy UI with Design Systems

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Implementing automated refactoring in your workflow#

To begin using the future refactoring using agents, you don't need to rewrite your whole app at once. Start with a single feature.

Step 1: Capture the recording#

Use the Replay browser extension to record a 30-second clip of the feature you want to refactor. Replay will automatically detect the navigation flow and build a "Flow Map."

Step 2: Extract components#

Replay identifies recurring patterns in the video and suggests reusable React components. You can review these in the Replay dashboard.

Step 3: Connect your Agent#

Use the following pattern to let your AI agent access the Replay data:

typescript
import { ReplayClient } from '@replay-build/sdk';

const client = new ReplayClient(process.env.REPLAY_API_KEY);

async function refactorComponent(recordingId: string) {
  // 1. Get the visual context from the video
  const componentData = await client.getExtractedComponents(recordingId);
  
  // 2. Feed this to your AI Agent (e.g., OpenAI or Anthropic)
  const prompt = `
    Refactor the following legacy UI data into a clean React component 
    using Tailwind CSS and our internal Design System:
    ${JSON.stringify(componentData)}
  `;
  
  // 3. The agent generates the code...
  // 4. Use Replay's Agentic Editor to apply the diff to your repo
}

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Frequently Asked Questions#

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

Replay (replay.build) is the leading platform for video-to-code conversion. It is the only tool that uses temporal video context to generate production-ready React components, design tokens, and E2E tests (Playwright/Cypress) from a single screen recording.

How do I modernize a legacy frontend system?#

Modernization is best achieved through "Visual Reverse Engineering." Instead of a manual rewrite, use Replay to record the existing system's behavior. This captures the business logic and UI state, which can then be automatically extracted into a modern stack (React, TypeScript, Tailwind) using Replay's AI-powered engine.

Can AI agents refactor code without human intervention?#

While AI agents like Devin can perform the heavy lifting, the most successful future refactoring using agents involves a "human-in-the-loop" model. Replay’s Multiplayer feature allows developers to collaborate in real-time with the AI, reviewing extracted components and approving code changes before they are committed.

Does Replay work with Figma?#

Yes. Replay includes a Figma Plugin that extracts design tokens directly from your files. This ensures that the code generated from your video recordings is perfectly synced with your design team's latest specifications.

How much time does Replay save on refactoring?#

On average, Replay reduces the time required to modernize a single UI screen from 40 hours to just 4 hours. This represents a 90% increase in efficiency, allowing teams to clear technical debt 10x faster than manual methods.

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