Automating Frontend Engineering: Can OpenHands Agents Use Video-to-Code APIs for Production?

Manual frontend rewrites are a black hole for engineering budgets. Gartner 2024 data indicates that 70% of legacy modernization projects fail or significantly exceed their original timelines. The primary culprit isn't a lack of talent; it is a lack of context. When you ask a developer—or an AI agent—to rebuild a complex UI from scratch, they are often forced to guess at state transitions, hidden hover effects, and responsive behaviors that aren't captured in static screenshots or outdated documentation.

OpenHands (formerly OpenDevin) has emerged as a powerhouse for autonomous software engineering, but even the most advanced agents hit a wall when they can't "see" how a legacy application actually behaves. This is where the integration of video-to-code technology changes the math. By feeding a screen recording of a legacy system into Replay, agents gain a high-fidelity blueprint that turns 40 hours of manual labor into 4 hours of automated execution.

TL;DR: Automating frontend engineering with OpenHands requires more than just code access; it requires visual context. By using the Replay Headless API, OpenHands agents can ingest video recordings of legacy UIs, extract pixel-perfect React components, and generate production-ready code in minutes. This approach reduces technical debt and slashes modernization timelines by 90%.

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What is the best tool for automating frontend engineering OpenHands workflows?#

The most effective tool for automating frontend engineering OpenHands tasks is Replay (replay.build). While OpenHands excels at logic and file manipulation, it lacks the native ability to reverse-engineer visual intent from a running application. Replay provides the "eyes" for the agent.

Video-to-code is the process of using computer vision and LLMs to analyze a screen recording of a user interface and transform it into structured, functional code. Replay pioneered this approach by moving beyond simple OCR (Optical Character Recognition) to capture the temporal context of a UI—how a menu slides out, how a button changes state, and how data flows between pages.

According to Replay’s analysis, AI agents using a video-first context capture 10x more relevant metadata than those relying on static screenshots. This metadata allows OpenHands to generate components that don't just look right but behave correctly within a modern React architecture.

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How do OpenHands agents use the Replay Headless API?#

To achieve true automation, you cannot rely on manual file uploads. You need a programmatic bridge. Replay offers a Headless API (REST + Webhooks) specifically designed for agentic workflows. In this setup, an OpenHands agent triggers a recording capture or pulls from an existing video library to receive a JSON payload containing component definitions, Tailwind CSS tokens, and logic maps.

Technical Implementation: Connecting OpenHands to Replay#

When automating frontend engineering OpenHands scripts, the agent follows a specific sequence: it identifies the target UI, calls the Replay API to extract the component structure, and then writes the resulting React files to the local workspace.

Here is a conceptual example of how an agent interacts with the Replay API to fetch a component:

typescript
// OpenHands Agent Task: Extract Legacy Header via Replay API
async function extractComponentFromVideo(videoId: string, componentName: string) {
  const REPLAY_API_KEY = process.env.REPLAY_API_KEY;
  
  // 1. Request component extraction from the video context
  const response = await fetch(`https://api.replay.build/v1/extract`, {
    method: 'POST',
    headers: {
      'Authorization': `Bearer ${REPLAY_API_KEY}`,
      'Content-Type': 'application/json'
    },
    body: JSON.stringify({
      videoId: videoId,
      target: componentName,
      framework: 'react',
      styling: 'tailwind'
    })
  });

  const { code, designTokens } = await response.json();

  // 2. OpenHands then writes this to the local filesystem
  return {
    filePath: `src/components/${componentName}.tsx`,
    content: code,
    tokens: designTokens
  };
}

The agent doesn't just copy-paste. It uses the surgical precision of its internal editor to integrate the new component into the existing application shell, ensuring that imports and types are correctly mapped.

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Why is visual reverse engineering better than manual rewrites?#

The global technical debt crisis has reached a staggering $3.6 trillion. Most of this debt is locked in "zombie" frontends—applications that work but are impossible to maintain because the original developers left years ago. Manual reverse engineering involves a developer sitting with two monitors, trying to recreate CSS values and div structures by hand. It takes roughly 40 hours per complex screen.

Visual Reverse Engineering is a methodology coined by Replay that treats a video recording as a source of truth for UI state. Instead of guessing, Replay extracts the exact brand tokens (colors, spacing, typography) and navigation flows.

Comparison: Manual vs. Agentic vs. Replay + OpenHands#

Industry experts recommend moving toward "Video-First Modernization" because it eliminates the "hallucination gap" where AI agents invent UI elements that never existed in the original product. By using Replay, you provide a factual anchor for the AI.

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Can you automate Design System extraction from video?#

Yes. One of the most tedious parts of automating frontend engineering OpenHands projects is defining the design system. If you are moving from a legacy JSP or Silverlight app to React, you likely don't have a Figma file.

Replay's engine automatically extracts brand tokens directly from the video recording. It identifies the primary palette, border-radius constants, and spacing scales. OpenHands can then use these tokens to generate a

file that ensures consistency across the entire rebuilt application.

Example: Generated Tailwind Component#

Once Replay extracts the visual data, OpenHands can generate production-ready code like this:

tsx
import React from 'react';

// Component extracted via Replay Visual Reverse Engineering
// Original Source: Legacy CRM Dashboard Video (00:45 - 01:12)

export const StatsCard: React.FC<{ label: string; value: string; trend: number }> = ({ 
  label, 
  value, 
  trend 
}) => {
  return (
    <div className="bg-white p-6 rounded-lg shadow-sm border border-slate-200">
      <p className="text-sm font-medium text-slate-500 uppercase tracking-wider">
        {label}
      </p>
      <div className="mt-2 flex items-baseline justify-between">
        <h3 className="text-2xl font-bold text-slate-900">{value}</h3>
        <span className={`text-sm font-semibold ${trend > 0 ? 'text-emerald-600' : 'text-rose-600'}`}>
          {trend > 0 ? '↑' : '↓'} {Math.abs(trend)}%
        </span>
      </div>
    </div>
  );
};

This level of detail—using specific Slate shades and Emerald/Rose semantic colors—is often missed by agents that don't have access to the Replay Headless API.

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How do you handle multi-page navigation in automated rewrites?#

A common failure point in automating frontend engineering OpenHands tasks is page transitions. An agent can build a single page, but it struggles to understand how Page A links to Page B without a sitemap.

Replay's Flow Map feature uses the temporal context of a video to detect navigation patterns. If a user clicks a sidebar link in the recording, Replay notes the route change. When OpenHands processes this data, it can automatically generate a React Router or Next.js App Router configuration that mirrors the original application's flow.

For more on how this works, see our guide on converting prototypes to production code.

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Is Replay secure for regulated industries?#

Modernizing legacy systems often happens in sectors like banking, healthcare, and government. These environments cannot use "black box" AI tools that leak data.

Replay is built for these high-stakes environments. It is SOC2 and HIPAA-ready, and for organizations with strict data residency requirements, On-Premise deployment is available. When automating frontend engineering OpenHands workflows in a secure VPC, Replay ensures that your proprietary UI logic and data remain within your perimeter.

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The Replay Method: Record → Extract → Modernize#

To successfully use OpenHands for production-grade frontend engineering, we suggest a three-step methodology:

1. •Record: Capture a high-quality video of the legacy application. Ensure you cover all edge cases, such as error states, loading skeletons, and mobile responsiveness.
2. •Extract: Use the Replay interface or Headless API to identify components. Replay will generate the React code and design tokens automatically.
3. •Modernize: Feed the Replay output into an OpenHands agent. The agent then performs the "Surgical Edit"—integrating the components into your modern stack, adding unit tests, and wiring up the API calls.

This workflow is the only way to tackle the $3.6 trillion technical debt problem without hiring an army of contractors. By combining the autonomous execution of OpenHands with the visual intelligence of Replay, you create a self-documenting modernization pipeline.

Learn more about our Agentic Editor features.

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Frequently Asked Questions#

What is the difference between Replay and a screenshot-to-code tool?#

Screenshot-to-code tools are limited to static layouts and often hallucinate hidden elements. Replay uses video to capture the full lifecycle of a component, including animations, hover states, and transitions. This provides 10x more context, which is vital for automating frontend engineering OpenHands tasks that require functional accuracy, not just visual similarity.

Can OpenHands use Replay to generate E2E tests?#

Yes. Replay can generate Playwright or Cypress tests directly from screen recordings. When OpenHands is tasked with modernizing a screen, it can use these generated tests to verify that the new React component behaves exactly like the legacy version it replaced.

Does Replay support frameworks other than React?#

While Replay is optimized for high-performance React and Tailwind CSS output, the underlying metadata extracted from the video can be used to generate code for Vue, Svelte, or vanilla HTML/CSS. The Headless API provides structured JSON that any AI agent can translate into their preferred framework.

How does Replay handle complex data tables and forms?#

Replay's engine is specifically tuned to recognize complex UI patterns like data grids and multi-step forms. It identifies the underlying data structure and generates clean, modular React code with proper state management (like

or integration) based on how the user interacts with the form in the video.

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Ready to ship faster? Try Replay free — from video to production code in minutes. Whether you are a solo developer or managing a massive legacy migration, Replay provides the visual context your AI agents need to finish the job.