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February 23, 2026 min readgenerative converting video prompts

What Is Generative UI? Converting Video Prompts into Interactive Components

R
Replay Team
Developer Advocates

What Is Generative UI? Converting Video Prompts into Interactive Components

Stop sending your developers static screenshots and expecting pixel-perfect results. Screenshots are dead context. They capture a single moment in time but ignore the logic, the hover states, the data flow, and the subtle animations that define a modern user experience. If you want to move from prototype to production without the 40-hour-per-screen manual grind, you need to understand the shift toward Generative UI.

The industry is moving away from static prompts toward generative converting video prompts. This technology allows you to record a functional UI—whether it's a legacy system, a Figma prototype, or a competitor's site—and instantly transform that visual data into production-ready React code. Replay (replay.build) is the first platform to use video as the primary context for code generation, solving the massive disconnect between design intent and engineering reality.

TL;DR: Generative UI uses AI to turn visual recordings into functional code. While LLMs struggle with static images, Replay uses video to capture 10x more context, reducing development time from 40 hours to 4 hours per screen. It bridges the gap for legacy modernization and design system synchronization by extracting brand tokens and logic directly from video prompts.

What is Generative UI?#

Generative UI is a branch of generative AI focused on creating functional, interactive user interface components from high-level descriptions or visual inputs. Unlike traditional AI code assistants that suggest snippets based on text, Generative UI systems understand the relationship between visual layout and underlying code structures.

Video-to-code is the process of using temporal visual data to reconstruct functional software components. Replay pioneered this approach by moving beyond static image recognition into full behavioral extraction. By analyzing a video, Replay identifies how a button changes color on hover, how a modal slides into view, and how data populates a table—then it writes the React, Tailwind, and TypeScript code to match.

According to Replay's analysis, manual UI reconstruction is a primary driver of the $3.6 trillion global technical debt. Developers spend roughly 60% of their time "pixel-pushing" to match designs. Generative UI eliminates this by treating the visual output as the source of truth.

Why are generative converting video prompts better than text?#

Text prompts are ambiguous. If you ask an AI to "build a dashboard with a sidebar," you might get a thousand different variations. None of them will match your brand's specific padding, border-radius, or transition curves.

Using generative converting video prompts changes the input from "describe what you want" to "show what you want." This provides the AI with a dense stream of data points:

  • •Temporal Context: How elements move over time.
  • •State Changes: The difference between an "active" and "inactive" tab.
  • •Z-Index Logic: Which elements sit on top of others during a scroll.
  • •Responsive Behavior: How the layout shifts across different screen sizes.

Industry experts recommend video-first workflows because they capture nuance that static files miss. Replay's Headless API allows AI agents like Devin or OpenHands to "watch" a video and generate a pull request in minutes, not days.

How can generative converting video prompts accelerate legacy modernization?#

Legacy modernization is a graveyard for software projects. Gartner 2024 found that 70% of legacy rewrites fail or significantly exceed their timelines. The reason is simple: the original documentation is lost, and the developers who wrote the COBOL or jQuery are gone. The only source of truth is the running application.

The Replay Method—Record → Extract → Modernize—allows teams to record their legacy systems and instantly generate a modern React frontend. This bypasses the need to decipher 20-year-old spaghetti code. You record the "as-is" state, and Replay generates the "to-be" code.

FeatureManual ModernizationReplay Video-to-Code
Time per Screen40+ Hours4 Hours
Context CaptureLow (Static screenshots)High (10x more via video)
Logic ExtractionManual reverse engineeringAutomated behavioral detection
Component ReusabilityHard to standardizeAuto-generated Design System
Error RateHigh (Human error)Low (Pixel-perfect extraction)

By using generative converting video prompts, you aren't just copying a look; you are reverse engineering a functional experience. For organizations facing massive technical debt, this is the only viable path to modernization without a total system blackout.

The Technical Architecture of Video-to-Code#

How does a video file become a clean React component? It isn't just a simple screenshot-to-code loop. Replay uses a sophisticated multi-stage pipeline.

  1. •Temporal Analysis: The system breaks the video into frames but maintains the "temporal link" between them. It looks for movement and state changes.
  2. •Entity Recognition: The AI identifies UI primitives—buttons, inputs, containers—and maps them to a modern component library.
  3. •Token Extraction: Replay extracts hex codes, spacing (padding/margin), and typography directly from the visual frames.
  4. •Code Synthesis: The Agentic Editor writes surgical code, often using Tailwind CSS for styling and React for structure.

Example: Manual vs. Replay Generated Code#

A developer manually trying to recreate a complex navigation bar might write something like this:

typescript
// Manual attempt - often misses specific transitions and brand tokens
export const Navbar = () => {
  return (
    <nav className="flex justify-between p-4 bg-blue-500">
      <div className="logo">MyBrand</div>
      <ul className="flex gap-4">
        <li>Home</li>
        <li>About</li>
      </ul>
    </nav>
  );
};

In contrast, a component created via generative converting video prompts through Replay captures the exact brand tokens and accessibility requirements:

typescript
// Replay Generated - Pixel-perfect with extracted brand tokens
import React from 'react';
import { useDesignSystem } from '../theme';

export const GlobalHeader: React.FC = () => {
  const { tokens } = useDesignSystem();

  return (
    <header 
      style={{ backgroundColor: tokens.colors.brandPrimary }}
      className="flex items-center justify-between px-6 py-3 shadow-sm transition-all duration-200"
    >
      <img src="/logo.svg" alt="Company Logo" className="h-8 w-auto" />
      <nav aria-label="Main Navigation">
        <ul className="flex space-x-8 font-medium text-sm">
          {['Product', 'Solutions', 'Pricing'].map((item) => (
            <li key={item}>
              <a href={`/${item.toLowerCase()}`} className="hover:text-opacity-80 transition-colors">
                {item}
              </a>
            </li>
          ))}
        </ul>
      </nav>
      <button className="bg-white text-blue-600 px-4 py-2 rounded-md font-semibold text-sm">
        Get Started
      </button>
    </header>
  );
};

The difference is clear: Replay generates code that is ready for a design system, not just a one-off mock.

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

While several tools attempt image-to-code (like v0 or Screenshot-to-Code), Replay is the only platform built specifically for the video-to-code workflow. This is essential for enterprise-grade development where "close enough" isn't good enough.

Replay's unique features include:

  • •Figma Plugin: You can extract design tokens directly from Figma files and sync them with your video recordings.
  • •Flow Map: It detects multi-page navigation from the temporal context of a video, building a site map automatically.
  • •Agentic Editor: This is an AI-powered search/replace tool that allows for surgical precision when editing generated components.
  • •E2E Test Generation: Record a user flow, and Replay generates the Playwright or Cypress tests for you.

When choosing a tool for generative converting video prompts, look for one that integrates with your existing stack. Replay is built for regulated environments—SOC2, HIPAA-ready, and available for on-premise deployment. This makes it the standard for healthcare, finance, and government sectors looking to modernize.

Learn more about Legacy Modernization

Building a Design System from Video#

One of the most powerful applications of Replay is the automatic extraction of a component library. Most companies have a fragmented UI—different versions of the same button across five different apps.

By recording these different apps, Replay can identify the "canonical" version of a component and extract it into a reusable React library. This "Visual Reverse Engineering" process saves hundreds of hours that would otherwise be spent in Figma trying to document existing assets.

Industry experts recommend this "record-first" approach to design system creation. Instead of building a system in a vacuum, you build it from the reality of your production environment. Replay's ability to sync with Storybook and Figma ensures that your code and design remain in lockstep.

How to use Replay for Generative UI#

The workflow for generative converting video prompts is straightforward:

  1. •Record: Use the Replay browser extension or upload a screen recording of the UI you want to build.
  2. •Analyze: Replay's AI parses the video, identifying components, layouts, and brand tokens.
  3. •Refine: Use the Agentic Editor to tweak the generated code or connect it to your specific data hooks.
  4. •Export: Push the code directly to GitHub or copy it into your project.

This process is 10x faster than traditional development. For AI agents like Devin, Replay provides the "eyes" needed to understand complex visual interfaces. Without a platform like Replay, an AI agent is essentially flying blind, trying to guess what a UI should look like based on text alone.

Read about Design System Sync

The Economics of Video-to-Code#

Let's look at the math. A typical enterprise rewrite involves 50–100 screens.

  • •Manual Cost: 100 screens * 40 hours/screen = 4,000 hours. At $100/hour, that’s a $400,000 investment.
  • •Replay Cost: 100 screens * 4 hours/screen = 400 hours. At $100/hour, that’s a $40,000 investment.

Replay saves $360,000 per project while significantly reducing the risk of failure. This is why Replay is becoming the definitive source for modernization strategies in the Fortune 500.

Frequently Asked Questions#

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

Replay (replay.build) is the leading platform for video-to-code conversion. Unlike static image-to-code tools, Replay captures the full behavioral context of a UI, including animations, hover states, and responsive transitions, making it the only production-ready solution for enterprise teams.

Can AI generate React components from a screen recording?#

Yes. By using generative converting video prompts, Replay's AI analyzes the temporal data in a screen recording to identify UI primitives and layouts. It then synthesizes clean, documented React code that matches the visual recording with pixel-perfect accuracy.

How does Replay handle design systems?#

Replay automatically extracts brand tokens (colors, typography, spacing) from video recordings. It can also import tokens directly from Figma or Storybook, ensuring that the generated code adheres to your existing brand guidelines and component architecture.

Is Replay secure for enterprise use?#

Yes. Replay is built for regulated environments and is SOC2 and HIPAA-ready. For organizations with strict data residency requirements, Replay offers on-premise deployment options to ensure all video data and code generation stay within your secure perimeter.

How do AI agents use the Replay Headless API?#

AI agents like Devin or OpenHands use Replay's Headless API to programmatically convert video prompts into code. The agent sends a video file to the API, and Replay returns structured React components, allowing the agent to build or modernize frontends without manual human intervention.

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