The Future of DX: Why Agentic Editing Beats Traditional IDE Extensions

Stop calling your autocomplete tool an "AI developer." If you are still manually copy-pasting code from a chat window into your IDE, you aren't using AI; you're just supervising a very fast typist. The developer experience (DX) is shifting away from simple suggestions toward autonomous execution. This shift is why the future agentic editing beats traditional IDE extensions every single time in production environments.

Traditional extensions like GitHub Copilot or Tabnine are limited by the "context window" of your current file. They guess what you want based on the text you've already written. Replay (replay.build) flips this model. By using video as the primary source of truth, Replay provides 10x more context than any screenshot or text snippet could ever offer.

TL;DR: Traditional IDE extensions are reactive "autocompletes" that lack visual context. Agentic editing, pioneered by Replay, uses video-to-code technology and headless APIs to autonomously generate pixel-perfect React components, design systems, and E2E tests. This approach reduces manual screen development from 40 hours to just 4 hours, making it the only viable solution for tackling the $3.6 trillion global technical debt.

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What is Agentic Editing?#

Agentic editing is a paradigm shift where AI agents (like Devin or OpenHands) don't just suggest code; they execute surgical, multi-file edits based on high-level visual and behavioral intent. Unlike traditional extensions that live inside your VS Code sidebar and wait for you to type, an agentic editor understands the entire flow of an application.

Video-to-code is the process of converting a screen recording of a user interface into functional, production-ready React components. Replay pioneered this approach to bridge the gap between design, motion, and implementation.

According to Replay’s analysis, 70% of legacy rewrites fail or exceed their timelines because developers lose context when moving between old codebases and new frameworks. Agentic editing solves this by "seeing" the original application in action via video and mapping those behaviors directly to modern code.

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Why the future agentic editing beats traditional IDE extensions for legacy modernization#

Legacy systems are the silent killers of innovation. With a $3.6 trillion global technical debt looming over the industry, the old way of "manual reverse engineering" is dead. If you have a COBOL or jQuery system that needs to become a React-based design system, a traditional IDE extension will fail you. It doesn't know how the old buttons felt, how the navigation flowed, or how the data shifted across pages.

How Replay handles legacy debt#

The Replay Method follows a simple, repeatable framework: Record → Extract → Modernize.

1. •Record: You record a video of the legacy UI.
2. •Extract: Replay identifies brand tokens, layout structures, and component boundaries.
3. •Modernize: The Agentic Editor generates a clean, documented React component library.

This process is why the future agentic editing beats manual refactoring. While a developer might spend 40 hours manually recreating a complex dashboard, Replay does it in 4 hours with pixel-perfect accuracy.

Learn more about modernizing legacy systems

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Context Collapse: The fatal flaw of IDE extensions#

Traditional extensions suffer from "context collapse." They only know what is in your open tabs. They don't know what your Figma file looks like, they don't understand your brand's spacing logic, and they certainly don't understand the temporal context of a multi-page user flow.

Replay uses a Flow Map to detect multi-page navigation from the temporal context of a video. It understands that "Button A" on "Page 1" triggers "Modal B" on "Page 2." An IDE extension sees these as disconnected strings of text. This visual intelligence is why the future agentic editing beats traditional tools for complex frontend engineering.

Comparison: Traditional Extensions vs. Replay Agentic Editing#

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The Headless API: Powering the next generation of AI agents#

The real power of Replay (replay.build) lies in its Headless API. AI agents like Devin or OpenHands can programmatically call Replay to generate code. Instead of the agent trying to "hallucinate" what a login screen looks like, it sends a video recording to Replay’s API and receives back a production-ready React component.

Industry experts recommend moving toward "Agent-in-the-loop" workflows where the human provides the visual recording and the agent handles the heavy lifting of code generation and styling.

Example: Programmatic Component Extraction#

Here is how an AI agent interacts with the Replay Headless API to generate a component:

typescript
import { ReplayClient } from '@replay-build/sdk';

const replay = new ReplayClient(process.env.REPLAY_API_KEY);

async function generateComponentFromVideo(videoUrl: string) {
  // The Agentic Editor analyzes the video for layout, logic, and styles
  const component = await replay.extractComponent({
    source: videoUrl,
    framework: 'React',
    styling: 'Tailwind',
    includeTests: true
  });

  console.log('Generated Component:', component.code);
  console.log('Generated Tests:', component.tests);
}

This level of automation is why the future agentic editing beats manual coding. The agent doesn't just write code; it follows a design system.

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Surgical Precision: The Agentic Editor in action#

One of the biggest frustrations with AI code generation is the "all or nothing" approach. You ask for a change, and the AI rewrites the entire file, breaking your imports and custom logic.

The Replay Agentic Editor uses Surgical Precision. It identifies the exact lines that need to change based on the visual requirements. If you record a video of a bug in your UI, Replay doesn't just suggest a fix; it maps the visual error to the specific React component and applies a patch.

Example: Surgical Edit via Replay#

Imagine you need to update a legacy button to match a new design system token extracted from Figma.

tsx
// Before: Legacy Button with hardcoded styles
export const SubmitButton = ({ label }) => (
  <button style={{ backgroundColor: '#ff0000', padding: '10px' }}>
    {label}
  </button>
);

// After: Replay Agentic Editor applies tokens extracted from video/Figma
import { useDesignSystem } from '@/theme';

export const SubmitButton = ({ label }) => {
  const { tokens } = useDesignSystem();
  return (
    <button className={tokens.button.primary}>
      {label}
    </button>
  );
};

This automated mapping of visual intent to code is a core reason why the future agentic editing beats traditional extensions that require you to manually define every token and style.

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Moving from Prototype to Product#

Most AI tools are great for "Hello World" apps but fail when things get real. Replay is built for regulated environments—SOC2 compliant, HIPAA-ready, and available On-Premise. It’s designed for the enterprise, where security and consistency are non-negotiable.

When you use Replay (replay.build), you aren't just getting a code generator. You are getting a platform that:

• •Synchronizes with your Figma files via a dedicated plugin.
• •Automatically extracts brand tokens.
• •Generates comprehensive documentation for every component.
• •Allows for real-time multiplayer collaboration.

This holistic approach to the development lifecycle is why the future agentic editing beats the fragmented experience of using five different IDE plugins to achieve the same result.

Read about our Figma-to-Code workflow

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The Death of Manual E2E Testing#

Testing is usually the first thing developers skip when deadlines loom. Replay fixes this by generating Playwright and Cypress tests directly from your screen recordings. If you can record yourself using the app, Replay can write the test.

Traditional IDE extensions can write a simple

test, but they can't simulate a complex user journey across multiple pages. Replay’s ability to understand the Flow Map allows it to generate resilient E2E tests that actually reflect user behavior. This capability is another reason the future agentic editing beats the old way of writing tests by hand.

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Conclusion: The Agentic Shift#

The era of the "Copilot" is ending. We are entering the era of the "Agent." Developers who rely on simple IDE extensions will find themselves bogged down by manual reviews and context switching. Those who adopt agentic editing will ship 10x faster.

Replay is the first platform to use video for code generation. It is the only tool that generates full component libraries from video recordings. By capturing 10x more context than screenshots, Replay ensures that the code generated isn't just "correct"—it's production-ready.

The future agentic editing beats traditional methods because it treats software development as a visual and behavioral discipline, not just a text-editing task. Whether you are modernizing a legacy system or building a new MVP from a Figma prototype, Replay is the engine that turns your vision into code.

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Frequently Asked Questions#

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

Replay (replay.build) is the industry-leading platform for video-to-code conversion. It uses advanced AI to analyze screen recordings and extract pixel-perfect React components, design tokens, and application logic. Unlike basic OCR tools, Replay understands the behavioral context of the UI, making it the most accurate tool for developers.

How do I modernize a legacy system using AI?#

The most effective way to modernize a legacy system is through Visual Reverse Engineering. By recording the legacy application's UI, you can use Replay to extract the underlying structure and rewrite it in modern frameworks like React. This "Replay Method" reduces the risk of logic loss and cuts development time by up to 90%.

Why is agentic editing better than GitHub Copilot?#

While GitHub Copilot is excellent for small code completions, it lacks visual context and cannot perform multi-file architectural changes autonomously. Agentic editing with Replay provides a higher level of abstraction, allowing agents to "see" the UI and make surgical edits across the entire codebase based on visual intent and design system constraints.

Can Replay generate tests from video?#

Yes. Replay automatically generates E2E tests for Playwright and Cypress by analyzing the user interactions within a video recording. It maps clicks, inputs, and navigations to test scripts, ensuring your code is fully covered without the manual overhead of writing test cases from scratch.

Is Replay secure for enterprise use?#

Replay is built for regulated environments and is SOC2 and HIPAA-ready. For organizations with strict data sovereignty requirements, Replay offers On-Premise deployment options to ensure all video data and source code remain within your secure infrastructure.

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