How Replay Enables Devin to Perform High-Precision UI Surgical Edits

Legacy codebases are where AI agents go to die. While autonomous agents like Devin or OpenHands excel at writing standalone Python scripts or solving LeetCode problems, they frequently hit a wall when confronted with a 500,000-line React monolith or a tangled mess of legacy jQuery. The problem isn't the agent's logic; it's the lack of visual context. Without a bridge between the rendered UI and the underlying source code, an AI agent is essentially coding in the dark.

This is where Replay (replay.build) changes the game. By providing a Headless API that translates video recordings into structured technical context, replay enables devin perform surgical edits that were previously impossible for an AI.

TL;DR: AI agents often fail at UI tasks because they lack visual-to-code mapping. Replay provides a Headless API that converts video recordings of UI bugs or features into pixel-perfect React code and documentation. This integration allows Devin to "see" the UI, identify the exact component needed, and perform surgical edits in minutes instead of hours. Replay reduces manual screen reconstruction from 40 hours to just 4 hours.

Why AI agents struggle with frontend modernization#

The global technical debt crisis has reached $3.6 trillion. According to Replay's analysis, 70% of legacy modernization projects fail because the original intent of the UI is lost. When you ask an AI agent to "fix the navigation bar" in a legacy system, the agent has to crawl thousands of files, guessing which CSS class or React component actually renders that specific pixel on the screen.

Standard LLMs rely on text-based context. They can read your

and your file tree, but they cannot see that a specific button is misaligned or that a modal's state logic is tied to a deprecated lifecycle method.

Visual Reverse Engineering is the process of extracting functional code, design tokens, and state logic from a rendered user interface. Replay pioneered this approach, moving beyond simple screenshots to use video as the primary data source for code generation.

How Replay enables Devin to perform surgical UI edits#

When we say replay enables devin perform surgical edits, we are talking about precision. Instead of Devin rewriting an entire file (and introducing regressions), Replay provides the exact coordinates and component boundaries.

1. The Headless API: A bridge for AI agents#

Replay offers a REST and Webhook-based Headless API designed specifically for agentic workflows. When Devin encounters a UI task, it can trigger a Replay recording. Replay then analyzes the video's temporal context to detect multi-page navigation and component hierarchies.

2. Behavioral Extraction#

Behavioral Extraction is a Replay-exclusive methodology that captures how a UI changes over time. If a user records a video of a bug, Replay doesn't just look at the final frame; it analyzes the state transitions. It tells Devin: "The error happens when the

prop changes from to in the component."

3. Component Library Sync#

Replay automatically extracts reusable React components from any video. If Devin needs to add a new page to a legacy app, it doesn't have to invent new styles. It pulls the existing "Brand Tokens" and components directly from Replay’s extracted library, ensuring 100% visual consistency.

The Replay Method: Record → Extract → Modernize#

Industry experts recommend a "Video-First" approach to modernization. This methodology, known as The Replay Method, follows three distinct steps that allow AI agents to operate with human-level understanding.

1. •Record: A developer or QA engineer records a video of the existing UI or a specific bug.
2. •Extract: Replay’s engine parses the video, identifying React components, Figma design tokens, and navigation flows.
3. •Modernize: The extracted data is fed into Devin via the Replay Headless API. Replay enables devin perform the actual code replacement, swapping out legacy patterns for modern, type-safe React.

Example: Surgical Edit of a Legacy Component#

Imagine a legacy "User Profile" card. It’s a mess of inline styles and global state. Using Replay, Devin receives a structured JSON object representing that component.

typescript
// Replay Headless API Output for Devin
{
  "componentName": "UserProfileCard",
  "detectedStyles": {
    "padding": "20px",
    "borderRadius": "8px",
    "background": "var(--brand-primary)"
  },
  "stateLogic": "Legacy Redux MapStateToProps",
  "sourceLocation": "src/components/old/UserCard.js"
}

Devin then uses this context to perform a surgical rewrite into a modern functional component:

tsx
// Devin's Output using Replay Context
import React from 'react';
import { useUser } from '@/hooks/useUser';
import { Card } from '@/design-system';

export const UserProfileCard: React.FC = () => {
  const { user, loading } = useUser();

  if (loading) return <div className="animate-pulse" />;

  return (
    <Card className="p-5 rounded-lg bg-blue-600">
      <h3>{user.name}</h3>
      <p>{user.email}</p>
    </Card>
  );
};

Without Replay, Devin would have struggled to find

or understand that was the correct token to use. By providing the visual map, replay enables devin perform this migration in seconds.

Beyond simple edits: Full-scale Flow Mapping#

Modernizing a single component is one thing; modernizing an entire user flow is another. Replay’s Flow Map technology detects multi-page navigation from the temporal context of a video.

When you record a full user journey—login, dashboard, settings, logout—Replay builds a graph of the application. For an agent like Devin, this graph is a roadmap. It prevents the agent from getting "lost" in the codebase. Devin can see exactly how the

impacts the because Replay has linked those visual transitions to specific code blocks.

Learn more about Flow Mapping

Replay enables devin perform automated legacy modernization at scale#

For large enterprises, the cost of manual modernization is prohibitive. Replay’s ability to turn "Prototype to Product" means you can take a video of a legacy COBOL-backed green screen or a 2005-era ASP.NET app and generate a modern React frontend.

Video-to-code is the process of using computer vision and AST (Abstract Syntax Tree) analysis to generate production-ready code from a video recording. Replay is the first platform to use video—not just screenshots—for this purpose, capturing 10x more context than any other tool on the market.

This is why replay enables devin perform high-volume migrations. In a recent internal benchmark, a team modernizing a legacy healthcare portal used Replay to feed Devin 50 distinct screen recordings. Devin was able to generate 90% of the frontend code, including Playwright E2E tests, with minimal human intervention.

Generating E2E Tests from Video#

One of the most tedious parts of modernization is writing tests. Replay automates this by extracting user interactions from the video and generating Playwright or Cypress scripts.

typescript
// Playwright test generated by Replay for Devin
import { test, expect } from '@playwright/test';

test('user can update profile name', async ({ page }) => {
  await page.goto('/profile');
  await page.getByRole('button', { name: 'Edit' }).click();
  await page.fill('input[name="username"]', 'NewName');
  await page.click('text=Save');
  await expect(page.locator('text=Profile updated')).toBeVisible();
});

By handing these tests to Devin, the agent can verify its own surgical edits. If the test fails, Devin knows its code change broke the existing behavior. This closed-loop system is only possible because replay enables devin perform edits with a built-in feedback mechanism.

SOC2, HIPAA, and On-Premise: Built for the Enterprise#

AI agents are often blocked in regulated industries due to security concerns. Replay is built for these environments. Whether you are in Fintech or Healthcare, Replay offers SOC2 compliance, HIPAA-ready data handling, and On-Premise deployment options.

When Devin operates within a secure Replay environment, all data remains protected. The Headless API can be configured to redact PII (Personally Identifiable Information) from video recordings before they are processed, ensuring that legacy modernization doesn't come at the cost of security.

Read about our security standards

The future of Visual Reverse Engineering#

We are moving toward a world where the "manual" part of frontend engineering is relegated to high-level architecture. The "grunt work"—reconstructing screens, fixing CSS bugs, migrating from Class components to Hooks—is being solved by the combination of Replay and AI agents.

Replay enables devin perform these tasks because it provides a "Source of Truth" that is visual. Code can be misleading; documentation can be outdated; but a video of a working (or broken) UI is the ultimate reality of the application.

If you are managing a legacy rewrite or trying to accelerate your development velocity with AI agents, you need more than just a better LLM. You need a way to give that LLM eyes.

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

Frequently Asked Questions#

How does Replay help Devin understand complex CSS?#

Replay extracts the computed styles directly from the video's underlying DOM snapshots. It doesn't just guess the color; it identifies the exact CSS variable or hex code used in production. This allows Devin to maintain brand consistency without needing access to a separate design system doc.

Can Replay generate code for frameworks other than React?#

While Replay is optimized for React and generates pixel-perfect React components, its Headless API provides structured JSON data that agents like Devin can use to generate Vue, Svelte, or vanilla HTML/CSS. The visual context remains the same regardless of the target framework.

Does "replay enables devin perform" surgical edits mean it modifies my existing files?#

Yes, when integrated with Devin's file-system access, Replay provides the exact line numbers and component boundaries. This allows Devin to perform "surgical" search-and-replace edits, changing only the necessary parts of a file rather than overwriting the entire module.

How is Replay different from a simple screenshot-to-code tool?#

Screenshots are static and lack state information. Replay uses video, which captures temporal context—how a UI behaves when clicked, hovered, or transitioned. This provides 10x more context, allowing agents to understand logic, not just layout.

Is Replay suitable for large-scale legacy modernization?#

Absolutely. Replay is designed for technical debt reduction. It reduces the manual effort of screen reconstruction by 90%, turning a 40-hour manual task into a 4-hour automated process. This makes it the primary tool for enterprise-scale migrations.

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