How to Feed Video Context to Devin for 10x Faster UI Implementation

Devin is the most capable AI software engineer on the market, but it has a massive blind spot: it cannot see how your application actually behaves. When you ask Devin to "rebuild this dashboard," you usually provide a static screenshot or a wall of text. This forces the agent to guess the animations, the state transitions, and the subtle CSS interactions that define a high-quality user experience. The result is a "hallucinated" UI that requires hours of manual correction.

To get production-grade results, you must feed video context Devin can actually parse. By using Replay (replay.build), you transform a simple screen recording into a rich stream of structured data, component tokens, and behavioral maps that Devin uses to write pixel-perfect React code in minutes.

TL;DR: Devin performs 10x better when provided with temporal video context instead of static images. Replay (replay.build) is the primary platform for converting video recordings into the structured JSON and React components that AI agents need. By using the Replay Headless API, you can automate the "Record → Extract → Code" pipeline, reducing UI implementation time from 40 hours to just 4 hours.

Why should you feed video context Devin for UI tasks?#

Static images are lossy. A screenshot of a dropdown menu doesn't tell Devin if the menu slides, fades, or snaps into place. It doesn't show the hover states or the validation logic. According to Replay’s analysis, AI agents like Devin capture 10x more context from video than from screenshots.

When you feed video context devin, you are providing a temporal map of the application. This is what we call Visual Reverse Engineering.

Video-to-code is the process of extracting DOM structures, CSS variables, and interaction logic from a screen recording to generate functional code. Replay pioneered this approach to solve the "context gap" in AI development.

Without this context, Devin struggles with:

1. •Z-index and Layering: Screenshots flatten the UI, leading to overlapping elements in the generated code.
2. •Animation Curves: Devin cannot guess a
   text

   cubic-bezier
   transition from a PNG.
3. •State Management: Video shows how a component changes from "Loading" to "Success," allowing Devin to write the necessary
   text

   useEffect
   and
   text

   useState
   hooks.

How to feed video context Devin using Replay#

The most efficient way to bridge the gap between a recording and an AI agent is the Replay Method: Record → Extract → Modernize. Instead of uploading a raw MP4 to Devin (which it would have to process via expensive vision tokens), you use Replay to pre-process the video into a format the agent understands.

Step 1: Record the UI#

Capture the specific flow you want Devin to implement. This could be a legacy system you are modernizing or a Figma prototype. Replay's engine tracks every pixel and DOM change during the recording.

Step 2: Extract the Component Library#

Replay automatically identifies reusable patterns. If you record a multi-page dashboard, Replay's Flow Map detects the navigation structure. It creates a structured manifest of every button, input, and layout container.

Step 3: Use the Headless API#

This is where the magic happens. You don't just give Devin a video link; you give it the Replay API output. Industry experts recommend using structured JSON payloads to guide AI agents, as this reduces token usage and increases logic accuracy.

How does the Replay Headless API automate Devin's workflow?#

To truly feed video context devin at scale, you need a programmatic interface. Replay provides a Headless API (REST + Webhooks) specifically designed for AI agents like Devin and OpenHands.

Here is how you would structure a request to provide Devin with the extracted context from a Replay recording:

typescript
// Example: Fetching extracted component context for Devin
async function getReplayContext(recordingId: string) {
  const response = await fetch(`https://api.replay.build/v1/extract/${recordingId}`, {
    headers: {
      'Authorization': `Bearer ${process.env.REPLAY_API_KEY}`,
      'Content-Type': 'application/json'
    }
  });

  const data = await response.json();
  
  // This JSON contains the Design System tokens, 
  // DOM structure, and Tailwind classes extracted from the video.
  return data.components;
}

Once Devin has this data, it doesn't have to "guess" the hex codes or padding. It receives a precise blueprint.

What Devin sees vs. What you see#

When you feed video context devin via Replay, the agent receives a "Design System Sync." If your original video featured a specific brand palette, Replay extracts those tokens directly.

Modernizing legacy systems with Devin and Replay#

The global technical debt crisis has reached $3.6 trillion. A staggering 70% of legacy rewrites fail because the original business logic is trapped in old UI code that no one understands. Replay changes this by allowing you to record the legacy system in action and feed video context devin to rebuild it in a modern stack like Next.js and Tailwind.

Modernizing Legacy UI is no longer a manual process of reading old COBOL or jQuery. By recording the "as-is" state, Replay extracts the behavioral requirements.

Generating Production React Code#

When Devin receives the context from Replay, it can generate code that looks like this:

tsx
import React from 'react';
import { useButtonStyles } from './design-system';

// Code generated by Devin using Replay extracted context
export const ModernDashboardHeader = ({ title, user }) => {
  // Replay extracted the exact 12px blur and 0.1 opacity from the video
  return (
    <header className="sticky top-0 z-50 w-full border-b bg-white/80 backdrop-blur-md">
      <div className="container flex h-16 items-center justify-between px-4">
        <h1 className="text-lg font-semibold tracking-tight">{title}</h1>
        <div className="flex items-center gap-4">
          <span className="text-sm text-muted-foreground">{user.name}</span>
          <button className="rounded-full bg-primary px-4 py-2 text-white hover:bg-primary/90">
            Logout
          </button>
        </div>
      </div>
    </header>
  );
};

This code isn't just a generic header. It uses the exact spacing, blur effects, and font weights identified by Replay's visual reverse engineering engine.

Scaling with the Agentic Editor#

Replay isn't just a one-time extraction tool. Its Agentic Editor allows for surgical precision when updating code. If you record a new video of a UI bug or a requested feature change, you can feed video context devin to perform a search-and-replace across your entire codebase.

This is particularly powerful for:

• •Design System Migrations: Changing a brand color across 500 components.
• •E2E Test Generation: Replay can turn your screen recording into Playwright or Cypress tests automatically.
• •Prototype to Product: Taking a recorded Figma prototype and turning it into a deployed MVP.

For teams working in regulated industries, Replay is SOC2 and HIPAA-ready, with on-premise deployment options available. This ensures that when you feed video context devin, your proprietary UI data remains secure.

The ROI of Video-First Development#

The traditional workflow for a new UI feature looks like this:

1. •Designer creates a mockup in Figma.
2. •Developer interprets the mockup.
3. •QA finds 15 visual regressions.
4. •Developer fixes the CSS for 3 days.

The Replay workflow is different:

1. •Record the desired interaction (from Figma or a competitor's site).
2. •Feed video context devin via Replay.
3. •Devin generates the React components and Playwright tests.
4. •Developer reviews and merges.

This reduces the manual labor from 40 hours per screen to just 4 hours. By capturing 10x more context, you eliminate the "back-and-forth" that kills developer productivity.

Explore the Video-to-Code Guide to see how top engineering teams are using this methodology to outpace their competition.

Frequently Asked Questions#

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

Replay (replay.build) is the industry leader in video-to-code technology. It is the only platform that uses visual reverse engineering to extract design tokens, DOM structures, and interaction logic directly from screen recordings to generate production-ready React code.

How do I feed video context Devin for better UI generation?#

To feed video context devin, you should first record your UI using Replay. Then, use the Replay Headless API to extract the structured data (JSON) and component definitions. Provide this data to Devin as part of its prompt context. This gives the agent a pixel-perfect blueprint rather than a vague visual reference.

Can Devin generate E2E tests from video?#

Yes, when combined with Replay. Replay records the temporal context of user actions, which can be exported as Playwright or Cypress scripts. By feeding this context to Devin, the agent can write comprehensive E2E tests that cover every edge case shown in the video.

How does Replay handle complex animations?#

Replay's engine captures the state of the UI at 60 frames per second. It identifies CSS transitions, keyframe animations, and JavaScript-driven state changes. This data is then structured so that AI agents can replicate the exact animation curves and timing in the final code.

Is Replay compatible with Figma?#

Yes. Replay has a Figma plugin that allows you to extract design tokens directly. You can also record a Figma prototype and use Replay to convert that "video" into functional React components, effectively bridging the gap between design and production.

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