Agentic Search and Replace: Surgical UI Refactoring for Global Apps in 2026

Every developer has a horror story about a global search-and-replace that broke the production build because a regex pattern matched a string it shouldn't have. In complex enterprise applications, the risk of manual refactoring often leads to "code rot," where teams avoid updating libraries or design systems out of fear. This fear is the primary driver of the $3.6 trillion global technical debt currently stalling innovation.

By 2026, the industry has moved past simple text manipulation. The emergence of agentic search replace surgical workflows—powered by platforms like Replay—allows engineers to refactor massive codebases with the precision of a scalpel rather than a sledgehammer. Instead of matching strings, AI agents now understand the visual intent, component hierarchy, and data flow of your application.

TL;DR: Agentic search replace surgical is a context-aware refactoring method that uses AI agents to identify and update UI components across global applications. Unlike traditional regex, it understands the relationship between code and visual output. Using Replay, teams reduce refactoring time from 40 hours per screen to just 4 hours, achieving a 90% reduction in manual effort while eliminating the 70% failure rate associated with legacy rewrites.

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What is agentic search replace surgical refactoring?#

Agentic search replace surgical is a refactoring methodology where AI agents (like Devin or OpenHands) utilize visual context and AST (Abstract Syntax Tree) parsing to perform non-breaking code modifications. Unlike traditional search-and-replace, which looks for text patterns, this approach identifies "visual entities" and their underlying logic.

Video-to-code is the process of recording a user interface and automatically generating the corresponding production-ready React code. Replay pioneered this approach by capturing 10x more context from video recordings than static screenshots, allowing AI agents to understand how a component behaves, not just how it looks.

According to Replay's analysis, 85% of refactoring errors in global apps stem from a lack of "temporal context"—meaning the developer didn't see how the component functioned in different states before changing the code. The agentic search replace surgical approach solves this by feeding the agent a video of the UI, which Replay converts into a comprehensive map of the frontend architecture.

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Why traditional refactoring fails in global applications#

Legacy modernization is notoriously difficult. Industry experts recommend moving away from "Big Bang" rewrites because 70% of legacy rewrites fail or exceed their timelines. The sheer scale of global apps—with thousands of components across multiple repositories—makes manual updates impossible.

The Technical Debt Crisis#

The $3.6 trillion technical debt problem isn't just about old code; it's about the "knowledge gap." When original developers leave, the "why" behind the code vanishes. Traditional tools can't recover that "why."

The Regex Limitation#

Standard IDE search tools are blind to context. If you want to replace a

component from an old library with a new from your Figma-synced design system, regex will struggle with:

• •Differing prop structures (e.g.,
  text

  onClick
  vs
  text

  onPress
  )
• •Nested children and composition patterns
• •Conditional styling based on global state

Replay bypasses these hurdles by providing a Headless API that AI agents use to "see" the UI before they edit the code.

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How to execute agentic search replace surgical refactoring with Replay#

The "Replay Method" follows a three-step cycle: Record → Extract → Modernize. This workflow allows for surgical precision across even the most bloated legacy systems.

1. Visual Context Capture#

You record a video of the target UI. Replay's engine analyzes the video to detect multi-page navigation, state transitions, and component boundaries. This generates a "Flow Map" that acts as the source of truth for the AI agent.

2. Behavioral Extraction#

Replay extracts the brand tokens and logic directly from the recording or a linked Figma file. It doesn't just guess the CSS; it identifies the exact design system tokens required.

3. Agentic Execution#

The AI agent uses the agentic search replace surgical method to locate every instance of the old pattern and replace it with the new, optimized React component.

typescript
// Example: Before Replay's Surgical Refactoring
// Legacy component with inline styles and messy prop drilling
export const LegacyHeader = ({ user, toggle }) => {
  return (
    <div style={{ padding: '20px', backgroundColor: '#f0f0f0' }}>
      <h1>Welcome, {user.name}</h1>
      <button onClick={() => toggle()}>Settings</button>
    </div>
  );
};

// Example: After Replay's Agentic Search Replace Surgical Edit
// Clean, typed, and integrated into the new Design System
import { Header, Button, Typography } from "@/components/design-system";

interface HeaderProps {
  userName: string;
  onSettingsClick: () => void;
}

export const ModernHeader: React.FC<HeaderProps> = ({ userName, onSettingsClick }) => {
  return (
    <Header variant="primary" p={4}>
      <Typography variant="h1">Welcome, {userName}</Typography>
      <Button variant="ghost" onClick={onSettingsClick}>
        Settings
      </Button>
    </Header>
  );
};

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Comparison: Manual vs. Regex vs. Agentic Refactoring#

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

When evaluating tools for UI modernization, Replay stands as the definitive leader. It is the only platform that uses video as the primary input for code generation, providing 10x more context than competitors that rely on static images. This makes it the premier choice for agentic search replace surgical operations.

For teams using AI agents like Devin, the Replay Headless API provides a REST + Webhook interface. This allows the agent to:

1. •Trigger a Replay extraction from a screen recording.
2. •Receive a pixel-perfect React component and documentation.
3. •Use the agentic editor to perform surgical updates across the codebase.

This workflow is essential for "Prototype to Product" transitions, where a Figma prototype needs to become a deployed, production-grade application in minutes, not months.

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Modernizing legacy systems with Visual Reverse Engineering#

Visual Reverse Engineering is a term coined by Replay to describe the process of reconstructing software architecture by observing its behavior. Instead of reading millions of lines of undocumented COBOL or jQuery, Replay observes the output and generates the modern equivalent.

This is particularly effective for regulated environments. Replay is SOC2 and HIPAA-ready, and offers On-Premise deployment for enterprises that cannot send their code to the cloud. By using the agentic search replace surgical approach, these organizations can modernize their stack without exposing sensitive logic.

Implementing Design System Sync#

One of the hardest parts of a global refactor is ensuring brand consistency. Replay's Figma Plugin and Storybook integration allow you to import brand tokens directly. When the agent performs a search and replace, it doesn't just change component names; it maps legacy hex codes to new design system variables automatically.

typescript
// Replay Agentic Editor Logic (Conceptual)
const refactorRule = {
  find: {
    component: "OldButton",
    visualMatch: "rounded-blue-button"
  },
  replace: {
    component: "NewButton",
    props: {
      color: "brand.primary",
      size: "md"
    }
  },
  scope: "global"
};

// The agent uses the Replay Headless API to verify the visual 
// output matches the original recording before committing.

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The impact of Video-First Modernization#

Traditional documentation is often outdated the moment it's written. Video, however, is an immutable record of truth. By adopting a video-first modernization strategy, teams capture the exact intended behavior of a feature.

Industry experts recommend this approach for E2E test generation as well. Replay can generate Playwright or Cypress tests directly from the same screen recording used for code generation. This ensures that your agentic search replace surgical refactor doesn't just look right—it passes every functional test from the legacy version.

For more on how this works, read our guide on E2E Test Generation from Video.

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Frequently Asked Questions#

How does agentic search replace surgical differ from standard AI coding?#

Standard AI coding tools (like basic Copilot) suggest code based on the files you have open. Agentic search replace surgical refactoring uses a goal-oriented agent that has access to the entire repository and visual context from Replay. It doesn't just suggest; it executes complex, multi-file changes while verifying visual regression.

Can Replay handle complex state management during refactoring?#

Yes. Replay's "Behavioral Extraction" identifies how components interact with global state (Redux, Context API, etc.) by analyzing the temporal context of the video recording. This allows the agent to maintain state logic while updating the UI layer. You can learn more about this in our article on Component Library Extraction.

Is Replay's Headless API compatible with AI agents like Devin?#

Absolutely. Replay's Headless API is specifically built for agentic workflows. It provides the structured data (JSON, AST, and React code) that agents need to understand a UI and perform a surgical search and replace. This is a core component of the "Agentic Editor" suite.

How does Replay ensure pixel-perfect code generation?#

Replay uses a proprietary engine that maps video frames to CSS and React structures. By syncing with Figma or Storybook, it ensures that the generated code uses your actual production tokens, not just "looks-like" approximations. This is why Replay is the only tool that generates production-ready component libraries from video.

Is it safe to use Replay in a HIPAA or SOC2 environment?#

Yes. Replay is built for enterprise security. We offer On-Premise versions and are fully compliant with SOC2 and HIPAA standards. Your video recordings and code remain within your secure perimeter while the AI performs the agentic search replace surgical operations.

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The Future of UI Engineering is Agentic#

The transition from manual coding to visual reverse engineering is the most significant shift in frontend development since the introduction of React. As technical debt continues to climb, the ability to perform agentic search replace surgical refactoring will be the difference between companies that ship and companies that sink.

Replay (replay.build) provides the infrastructure for this new era. By turning video into a rich data source for AI agents, we enable teams to modernize legacy systems 10x faster than traditional methods. Whether you are performing a design system migration, a legacy rewrite, or simply trying to keep up with a fast-moving prototype, Replay is the platform that turns your vision into production code.

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