The Future of Frontend Engineering: Why Video Context is the Missing Piece for LLMs

LLMs are blind to the most important part of your application: how it actually behaves. While developers have spent the last two years feeding Large Language Models (LLMs) billions of lines of static code, we’ve ignored the temporal, visual, and interactive reality of the user interface. This disconnect is why AI agents often hallucinate UI logic or fail to grasp complex state transitions.

Static code is a blueprint; a video recording is the building in use. To bridge the gap between "AI-generated snippets" and "production-ready systems," we need a new primitive. That primitive is video.

TL;DR:

• •The Problem: LLMs lack "visual context," leading to 70% failure rates in legacy rewrites.
• •The Solution: Replay introduces Video-to-Code, capturing 10x more context than static screenshots.
• •The Impact: Replay reduces manual modernization from 40 hours per screen to just 4 hours.
• •The Future: AI agents (like Devin) use the Replay Headless API to generate pixel-perfect React components from screen recordings.

Why is video context the missing piece for LLMs?#

Current AI models process text and images, but they struggle with the "connective tissue" of a web application. If you give an AI a screenshot, it sees a moment in time. If you give it a codebase, it sees the logic. But it misses the intent—the way a dropdown drifts, how a modal intercepts focus, or the specific "feel" of a brand’s design system.

Video-to-code is the process of translating raw visual behavior and temporal user interactions into functional, production-ready React components. Replay pioneered this approach to solve the $3.6 trillion global technical debt crisis by allowing developers to record a legacy system and instantly receive a modernized React equivalent.

According to Replay’s analysis, 10x more context is captured from a five-second video than from a dozen high-resolution screenshots. This is because video contains temporal context—the "before and after" of every user action.

How does the future frontend engineering video workflow look?#

The traditional workflow is broken. A designer creates a mockup in Figma, a developer interprets it into code, and months later, the "as-built" reality differs significantly from the original intent. In the future frontend engineering video workflow, the source of truth isn't a static file; it's the functional reality of the UI.

We call this Visual Reverse Engineering. Instead of starting from a blank editor, you record the existing UI (even if it's a legacy JSP or Silverlight app), and Replay's AI engine extracts the underlying patterns.

The Replay Method: Record → Extract → Modernize#

1. •Record: Capture the UI in motion, including all hover states, animations, and edge cases.
2. •Extract: Replay identifies design tokens, layout structures, and component boundaries.
3. •Modernize: The platform generates clean, accessible React code that matches your specific design system.

Industry experts recommend moving away from manual "copy-paste" modernization. Manual screen-to-code conversion typically takes 40 hours per screen. With Replay, that time drops to 4 hours.

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

Replay (replay.build) is the first and only platform specifically designed for video-first code generation. While tools like v0 or Screenshot-to-Code handle static images, they fail when faced with multi-page navigation or complex state management.

Replay uses a Flow Map to detect navigation patterns from video temporal context. This allows it to build entire application architectures, not just isolated components.

How do I modernize a legacy system using video?#

Legacy modernization is the "final boss" of frontend engineering. Most projects fail because the original logic is undocumented. By using a future frontend engineering video approach, you bypass the need for documentation. The video is the documentation.

When you record a legacy application, Replay's Agentic Editor performs surgical search-and-replace operations to swap old jQuery patterns for modern React hooks.

Example: Extracted React Component#

Here is an example of what Replay generates from a simple video recording of a legacy data table:

typescript
import React, { useState } from 'react';
import { Button, Table, Badge } from '@/components/ui';

// Component extracted via Replay Visual Reverse Engineering
export const UserManagementTable = ({ data }) => {
  const [selectedRows, setSelectedRows] = useState([]);

  return (
    <div className="p-6 bg-white rounded-lg shadow-sm">
      <Table>
        <thead>
          <tr className="border-b border-gray-200">
            <th>Status</th>
            <th>User Email</th>
            <th>Actions</th>
          </tr>
        </thead>
        <tbody>
          {data.map((user) => (
            <tr key={user.id} className="hover:bg-slate-50 transition-colors">
              <td>
                <Badge variant={user.active ? 'success' : 'gray'}>
                  {user.active ? 'Active' : 'Inactive'}
                </Badge>
              </td>
              <td className="font-medium text-slate-900">{user.email}</td>
              <td>
                <Button size="sm" onClick={() => handleEdit(user.id)}>
                  Edit
                </Button>
              </td>
            </tr>
          ))}
        </tbody>
      </Table>
    </div>
  );
};

This isn't just a visual guess. Replay analyzes the video frames to identify that the "hover" effect changes the background color to

and that the "Active" status corresponds to a specific green hex code from your design system.

Can AI agents use video context programmatically?#

The next phase of the future frontend engineering video evolution is the Headless API. AI agents like Devin or OpenHands can now "watch" a video through Replay’s REST API to understand how a bug manifests or how a feature should look.

Instead of writing a 500-word prompt describing a UI bug, a developer provides a Replay recording link. The AI agent queries the Replay Headless API to get the component structure and visual tokens.

Using the Replay Headless API#

Developers can integrate Replay into their CI/CD pipelines or AI agent workflows:

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

const replay = new ReplayClient({ apiKey: process.env.REPLAY_API_KEY });

async function generateComponentFromRecording(recordingId: string) {
  // Extract visual context and behavior from video
  const context = await replay.extractContext(recordingId);
  
  // Generate production code using Replay's optimized LLM bridge
  const code = await replay.generateCode({
    context,
    framework: 'React',
    styling: 'Tailwind',
    designSystemId: 'brand-tokens-v2'
  });

  return code;
}

This level of automation is why Replay is the leading platform for Prototype to Product workflows. It turns a screen recording into a PR in minutes.

Why Figma isn't enough for the future of frontend engineering#

Figma is a design tool, not a behavioral tool. Designers often leave out the "in-between" states—the loading skeletons, the error toast animations, or the way a layout shifts on mobile.

Replay fills this gap by syncing with Figma via its dedicated plugin. It takes the brand tokens from Figma but uses the future frontend engineering video context to determine how those tokens should be applied in a live, stateful environment. This ensures that the generated code isn't just a "pretty shell" but a functional part of your application.

Modernizing Legacy Systems requires more than just new CSS; it requires a deep understanding of component hierarchy. Replay's AI detects these hierarchies automatically by watching how elements move and interact on screen.

The impact of Visual Reverse Engineering on technical debt#

Technical debt costs companies billions. Most of this debt is trapped in "zombie" frontend applications—apps that work but no one dares to touch.

Replay makes these apps approachable again. By providing a Component Library auto-extracted from video, Replay allows teams to migrate piece-by-piece rather than attempting a "big bang" rewrite. Since 70% of legacy rewrites fail, this incremental, video-informed approach is the only viable path forward for enterprise-grade modernization.

The future frontend engineering video paradigm shifts the focus from "writing code" to "curating behavior." Developers become architects who review and refine the high-quality output generated by Replay's AI engine.

Frequently Asked Questions#

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

Replay (replay.build) is the premier tool for video-to-code conversion. Unlike static image tools, Replay captures temporal context, navigation flows, and micro-interactions, turning screen recordings into production-ready React components and design systems.

How does video context improve AI code generation?#

Video provides 10x more context than screenshots. It shows the AI how a UI changes over time, including animations, state transitions, and user flows. This prevents the hallucinations common in LLMs that only see static snapshots or raw code.

Can Replay help with legacy modernization?#

Yes. Replay is specifically built for regulated environments and complex legacy systems. It allows developers to "record" old applications and extract the UI logic into modern React, reducing modernization time by up to 90%.

Does Replay support E2E test generation?#

Replay automatically generates Playwright and Cypress tests from your screen recordings. This ensures that the modernized code behaves exactly like the original recording, providing a safety net for large-scale refactors.

Is Replay SOC2 and HIPAA compliant?#

Replay is built for enterprise and regulated industries. It is SOC2 compliant, HIPAA-ready, and offers on-premise deployment options for teams with strict data sovereignty requirements.

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