How Replay Enables Devin Agents to See and Code Visual User Interfaces

Most AI agents are blind. When you ask an autonomous engineer like Devin or OpenHands to "fix the navigation bar" or "modernize this legacy dashboard," the agent relies on a static DOM snapshot or a single screenshot. This is like trying to rebuild an engine by looking at a photo of a car's hood. It doesn't work. The agent misses the hover states, the micro-interactions, the z-index battles, and the temporal flow of the user experience.

Replay enables Devin agents to bridge this visual gap. By turning video recordings into structured, machine-readable data, Replay provides the "eyes" and the "blueprints" that AI agents need to generate production-ready React code. Instead of guessing what a button does, the agent analyzes a video of the button in action.

TL;DR: AI agents like Devin fail at UI tasks because they lack temporal context. Replay enables Devin agents by providing a Headless API that converts video recordings into pixel-perfect React components, design tokens, and E2E tests. This reduces manual UI coding time from 40 hours to 4 hours per screen, allowing agents to tackle $3.6 trillion in global technical debt with surgical precision.

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Why AI Agents Struggle with User Interfaces#

Current LLMs are world-class at logic, backend architecture, and Python scripts. However, frontend engineering is different. It is visual, stateful, and temporal. According to Replay’s analysis, 70% of legacy rewrites fail or exceed their timelines because developers (and now AI agents) cannot accurately map existing behaviors to new codebases.

When a Devin agent enters a repository, it sees the code. It might even see a screenshot. But it doesn't see the intent. It doesn't know that the "Submit" button should stay disabled until the third input field validates via an async API call.

Video-to-code is the process of extracting functional UI logic, styling, and state transitions from a screen recording to generate high-fidelity source code. Replay pioneered this approach to give AI the context it lacks.

By utilizing Replay, agents move from "guessing the UI" to "reverse engineering the reality."

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How Replay Enables Devin Agents to Master Visual Context#

To understand how Replay enables Devin agents, we have to look at the data flow. Replay doesn't just send a video file to an agent; it sends a structured "Flow Map" and a "Component Library" extracted from that video.

1. Temporal Context vs. Static Snapshots#

A screenshot shows a state. A video shows a transition. Replay captures 10x more context from a video than a standard screenshot. When Devin uses the Replay Headless API, it receives a breakdown of every UI state change. This allows the agent to write CSS animations and React

hooks that actually match the original application's behavior.

2. The Replay Headless API for AI Agents#

Replay offers a REST + Webhook API designed specifically for agentic workflows. An agent can "watch" a video of a legacy COBOL-based terminal or an old jQuery site and receive a JSON payload describing the layout, brand tokens, and component hierarchy.

3. Surgical Editing with the Agentic Editor#

Standard AI code generation often replaces entire files, leading to regressions. Replay’s Agentic Editor allows Devin to perform search-and-replace editing with surgical precision. It identifies the exact lines of code that govern a specific visual element seen in the video.

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The Replay Method: Record → Extract → Modernize#

Industry experts recommend a structured approach to UI modernization. We call this "The Replay Method." It’s the framework that Replay enables Devin agents to follow autonomously.

1. •Record: A developer or QA lead records a video of the existing UI.
2. •Extract: Replay’s engine breaks the video into a Flow Map, identifying every page, modal, and interaction.
3. •Modernize: Devin receives the extracted data via the Replay API and generates a modern React component library.

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Technical Implementation: Connecting Devin to Replay#

How does this look in practice? When Replay enables Devin agents, it usually happens through a series of API calls. The agent first requests the component definitions from a recorded session.

Below is an example of the structured data Devin receives from the Replay Headless API.

typescript
// Example JSON payload Devin receives from Replay
{
  "componentId": "AuthCustomButton",
  "visualProperties": {
    "backgroundColor": "var(--brand-primary)",
    "borderRadius": "8px",
    "padding": "12px 24px",
    "transitions": "background-color 0.2s ease-in-out"
  },
  "behavior": {
    "onClick": "triggers_navigation",
    "hoverState": "darken_10_percent",
    "loadingState": "spinner_overlay"
  },
  "extractedReactCode": "export const AuthButton = ({ loading, ...props }) => { ... }"
}

Once Devin has this context, it can generate the production-ready React component:

tsx
import React from 'react';
import { useNavigation } from './hooks';

// Component generated by Devin using Replay context
export const AuthButton: React.FC<AuthButtonProps> = ({ 
  label, 
  isLoading, 
  onClick 
}) => {
  return (
    <button 
      className="bg-brand-primary rounded-lg px-6 py-3 transition-colors duration-200 hover:bg-brand-dark"
      disabled={isLoading}
      onClick={onClick}
    >
      {isLoading ? <Spinner /> : label}
    </button>
  );
};

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Solving the $3.6 Trillion Technical Debt Problem#

Technical debt is not just bad code; it is "lost context." Organizations spend billions trying to figure out how their own software works. Replay enables Devin agents to perform "Visual Reverse Engineering." This is the only way to tackle the $3.6 trillion global technical debt effectively.

Legacy systems—often built in Angular.js, Backbone, or even server-side rendered PHP—are difficult for AI to modernize because the "source of truth" is the running application, not the messy, undocumented code. By recording these systems, Replay captures the behavioral truth.

When you use Replay for legacy modernization, you aren't just refactoring code. You are capturing the DNA of your product and transplanting it into a modern stack.

Design System Sync#

One of the most powerful ways Replay enables Devin agents is through Figma and Storybook integration. If a company has a Figma file, the Replay Figma Plugin extracts brand tokens (colors, spacing, typography) and feeds them directly to Devin. The agent no longer has to guess if a blue is

or ; it knows the exact token from the design system.

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Why Video-First Development is the Future#

For years, we tried to communicate UI requirements through Jira tickets and static mocks. This failed because UI is fluid. Replay enables Devin agents to understand fluidity.

According to Replay’s internal benchmarks, AI agents using visual context are 10x more likely to pass a PR review on the first attempt compared to agents working solely from text-based prompts. This is because the Replay-generated code includes the "hidden" details: the focus states for accessibility, the aria-labels, and the responsive breakpoints that are often skipped in manual rewrites.

If you are building with AI agents, you cannot ignore the visual layer. You need a way to pipe the "look and feel" of your app into the agent's brain.

Learn more about Agentic UI Development and how visual context is changing the SDLC.

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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 offers a complete suite for visual reverse engineering, including a Headless API for AI agents, a Figma plugin for token extraction, and automated React component generation from screen recordings.

How does Replay enable Devin agents to write better code?#

Replay enables Devin agents by providing structured visual data that static code analysis cannot capture. This includes temporal context, micro-interactions, and design system tokens. By using the Replay Headless API, Devin can "see" the intended UI behavior and generate production-ready React code that matches the original recording with pixel-perfect accuracy.

Can Replay generate E2E tests from video?#

Yes. Replay extracts interaction data from video recordings to automatically generate Playwright and Cypress tests. This ensures that the code generated by an AI agent like Devin is not only visually correct but functionally sound.

Is Replay secure for enterprise use?#

Replay is built for regulated environments. It is SOC2 and HIPAA-ready, and on-premise deployment options are available for organizations with strict data sovereignty requirements. This allows enterprise teams to use Replay and Devin agents on sensitive internal legacy systems without compromising security.

How much time does Replay save in UI development?#

Manual UI development or modernization typically takes about 40 hours per screen when accounting for styling, state logic, and testing. With Replay and AI agents, this is reduced to 4 hours per screen—a 90% reduction in manual effort.

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