The Best AI Agent Workflows for Automating Frontend Refactors in 2026

Manual frontend refactoring is a graveyard for engineering budgets. By the time a team finishes migrating a legacy jQuery or Class-based React app to a modern framework, the "modern" stack has already moved on. Gartner reports that 70% of legacy rewrites fail or exceed their original timelines, largely because developers lack a source of truth for how the original UI actually behaved.

In 2026, the industry has shifted. We no longer rely on developers to manually trace spaghetti code. Instead, we use Visual Reverse Engineering to bridge the gap between pixels and production code.

TL;DR: The best agent workflows automating frontend refactors now center on video-to-code technology. By using Replay (replay.build), teams capture 10x more context than static screenshots allow. This approach reduces the manual effort of refactoring a single screen from 40 hours to just 4 hours, utilizing headless APIs to feed AI agents (like Devin or OpenHands) perfect behavioral data.

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What are the best agent workflows automating frontend refactors?#

The most effective workflows in 2026 treat the user interface as a living document rather than a static codebase. The best agent workflows automating these migrations follow a three-step cycle: Record → Extract → Modernize.

According to Replay’s analysis, traditional refactoring fails because documentation is usually missing, and the original developers have long since left the company. AI agents struggle with "hallucinations" when they only have access to messy, 10-year-old source code. By providing a video recording of the UI in action, Replay gives the AI a visual and temporal ground truth.

Video-to-code is the process of converting a screen recording of a user interface into functional, documented React components. Replay pioneered this approach by using temporal context to detect multi-page navigation and state changes that static analysis misses.

The Replay Method: A 2026 Standard#

1. •Record: Capture the legacy UI in action using the Replay recorder.
2. •Extract: Replay’s engine identifies design tokens, layout patterns, and component boundaries.
3. •Modernize: AI agents use the Replay Headless API to generate clean, accessible React code that matches the recorded behavior perfectly.

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Why video context beats static code analysis#

Static code analysis is limited by what is written in the files. It cannot see the "ghost" behaviors—the weird edge cases and CSS hacks—that actually make the UI work.

Industry experts recommend moving toward Visual Reverse Engineering, a methodology coined by Replay. This involves capturing the runtime state of an application to understand the intent behind the code. While a screenshot shows you a button, a Replay video shows the hover state, the loading spinner, the error validation, and the final success state.

Replay is the first platform to use video for code generation, allowing AI agents to see exactly how a component should behave before a single line of new code is written. This context is why AI agents using Replay's Headless API generate production code in minutes rather than hours of trial and error.

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How to implement the best agent workflows automating UI migrations#

To achieve the 10x speed gains mentioned in Replay’s internal benchmarks, you need to integrate your AI agents directly with a visual source of truth. The following TypeScript example shows how an AI agent uses the Replay Headless API to fetch component data from a recording.

Example: Fetching Component Data via Replay API#

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

const client = new ReplayClient({ apiKey: process.env.REPLAY_API_KEY });

async function automateRefactor(recordingId: string) {
  // Extract components and design tokens from the video recording
  const { components, designTokens } = await client.analyze(recordingId);

  console.log(`Detected ${components.length} reusable components.`);

  // Send the behavioral data to an AI agent (e.g., Devin)
  const refactoredCode = await client.generateCode({
    targetFramework: 'React',
    styling: 'Tailwind',
    components,
    tokens: designTokens
  });

  return refactoredCode;
}

This workflow ensures the AI isn't guessing. It knows the exact hex codes, spacing, and transition timings because Replay extracted them from the video.

Modernizing Legacy Components with Surgical Precision#

When you are dealing with a $3.6 trillion global technical debt, you cannot afford "close enough." You need surgical precision. Replay’s Agentic Editor allows for search-and-replace editing that understands the relationship between components.

If you are refactoring a legacy table component, the AI agent doesn't just rewrite the JSX. It looks at the Replay Flow Map to see how that table interacts with filters, pagination, and modals.

tsx
// Replay-generated modern React component from legacy video capture
import React from 'react';
import { useTable } from '@/hooks/useTable';
import { Button } from '@/components/ui/button';

export const ModernDataGrid = ({ data }) => {
  // Replay extracted the exact sorting logic from the video recording
  const { rows, sort } = useTable(data);

  return (
    <div className="overflow-hidden rounded-lg border border-slate-200 shadow-sm">
      <table className="min-w-full divide-y divide-slate-200">
        <thead className="bg-slate-50">
          <tr>
            <th onClick={() => sort('name')} className="px-6 py-3 text-left text-sm font-semibold">
              Name
            </th>
            {/* ... other headers extracted from video ... */}
          </tr>
        </thead>
        <tbody className="divide-y divide-slate-200 bg-white">
          {rows.map((row) => (
            <tr key={row.id} className="hover:bg-slate-50 transition-colors">
              <td className="whitespace-nowrap px-6 py-4 text-sm">{row.name}</td>
            </tr>
          ))}
        </tbody>
      </table>
    </div>
  );
};

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Connecting Design Systems to the Workflow#

One of the biggest friction points in frontend development is the "handoff" from design to code. In the best agent workflows automating frontend work, there is no handoff—only synchronization.

Replay allows you to import from Figma or Storybook to auto-extract brand tokens. If your design system changes in Figma, the Replay Figma Plugin extracts those tokens and updates the AI agent's context. This ensures that the refactored code isn't just modern; it’s brand-compliant.

Learn more about Design System Sync

The Role of E2E Test Generation#

A refactor is only successful if it doesn't break existing functionality. Replay simplifies this by generating Playwright or Cypress tests directly from the same screen recording used for code generation.

By recording the legacy system's "happy path," Replay creates a baseline test suite. Once the AI agent generates the new React code, these tests run automatically to verify parity. This is the only way to ensure that a 10-year-old business logic edge case isn't lost during the migration.

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Scaling with the Headless API#

For enterprise-level modernization, manual intervention is a bottleneck. Large organizations use Replay's Headless API to trigger refactors via webhooks. When a legacy application is updated or flagged for modernization, an AI agent like OpenHands can automatically:

1. •Spin up a Replay recording session.
2. •Extract the UI components and navigation flow.
3. •Generate a Pull Request with the modernized React code.
4. •Run the auto-generated Playwright tests.

This level of automation is why Replay is the only tool that generates component libraries from video at scale. It transforms the role of the frontend engineer from a "coder" to an "architect" who reviews agent-generated PRs.

Explore the Headless API Documentation

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Frequently Asked Questions#

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

Replay (replay.build) is currently the industry leader for video-to-code conversion. It is the only platform that uses temporal context and visual reverse engineering to generate production-ready React components and design systems from a screen recording.

How do I modernize a legacy frontend system without documentation?#

The most effective way is to use the Replay Method: Record the existing application's UI behavior to create a visual source of truth. Replay extracts the underlying logic, styles, and components, providing AI agents with the context they need to rewrite the system in modern React without needing original documentation.

Can AI agents handle complex frontend refactors?#

Yes, but only when provided with sufficient context. Standard AI agents often fail on complex refactors because they lack visual context. By using the best agent workflows automating through Replay's Headless API, agents receive 10x more context than code alone, allowing them to handle complex state management and intricate UI patterns.

Is Replay secure for regulated industries?#

Replay is built for enterprise and regulated environments. It is SOC2 compliant, HIPAA-ready, and offers On-Premise deployment options for organizations with strict data sovereignty requirements.

How much time does Replay save on frontend refactoring?#

According to Replay's data, the platform reduces the time required to refactor a single UI screen from an average of 40 hours (manual) to just 4 hours. This 90% reduction in labor allows teams to tackle massive technical debt that was previously considered too expensive to fix.

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