Can AI Agents Build Enterprise-Grade Design Systems via Headless APIs?

Senior engineers spend 40% of their week wrestling with CSS inconsistencies and hunting down rogue hex codes. This manual labor contributes to the $3.6 trillion global technical debt currently paralyzing enterprise innovation. The traditional workflow—designers hand off a Figma file, and developers spend 40 hours per screen manually coding components—is officially obsolete.

We are entering the era of Visual Reverse Engineering. By using Replay’s Headless API, autonomous AI agents like Devin and OpenHands can now observe a legacy application or a video recording and generate a production-ready design system in minutes. This isn't just about "generating code"; it's about the programmatic extraction of intent, logic, and brand identity.

TL;DR: Yes, AI agents build enterprise-grade design systems effectively when powered by Replay’s Headless API. By moving from static screenshots to video-first context, Replay provides 10x more data to AI agents, allowing them to extract brand tokens, component logic, and navigation flows automatically. This reduces the time-to-code from 40 hours per screen to just 4 hours.

How do agents build enterprise-grade design systems using video?#

Traditional AI models fail at UI development because they lack context. A screenshot only shows a single state. It doesn't show how a button behaves on hover, how a modal animates, or how the navigation menu handles nested routes.

Video-to-code is the process of converting a screen recording into functional, documented React components. Replay (replay.build) pioneered this approach by using temporal context to understand the "why" behind the UI, not just the "what."

When agents build enterprise-grade design systems, they follow the Replay Method:

1. •Record: A user records a 60-second walkthrough of their existing application.
2. •Extract: Replay’s Headless API parses the video, identifying brand tokens (colors, typography, spacing) and component boundaries.
3. •Modernize: The AI agent receives this structured data and generates a clean, accessible React library.

According to Replay’s analysis, 70% of legacy rewrites fail because the original design intent was lost. By using video as the source of truth, Replay ensures that agents build enterprise-grade design outputs that are pixel-perfect and functionally identical to the source.

Why is the Replay Headless API the standard for AI agents?#

Standard LLMs are blind to the nuances of enterprise software. If you ask a generic AI to "build a dashboard," it gives you a generic template. However, when agents build enterprise-grade design systems using Replay's Headless API, they access a structured data stream that includes:

• •Temporal Context: How the UI changes over time.
• •Brand Token Extraction: Automatic identification of primary, secondary, and tertiary palettes.
• •Flow Map Detection: Understanding how pages connect without manual mapping.

Industry experts recommend moving away from "prompt-to-code" and toward "observation-to-code." Replay acts as the visual cortex for AI agents. Instead of guessing what a "Primary Button" looks like, the agent queries the Replay API to get the exact CSS properties, hover states, and accessibility ARIA labels used in the production recording.

Comparison: Manual Modernization vs. Replay-Powered Agents#

How do agents build enterprise-grade design systems programmatically?#

To understand how this works under the hood, we look at the interaction between an AI agent and the Replay Headless API. The agent doesn't just "see" the video; it receives a JSON payload describing every atomic element within the recording.

Example: Querying the Replay API for Component Extraction#

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

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

// Agent triggers extraction from a legacy app recording
const extraction = await client.extract({
  videoId: 'enterprise-legacy-dashboard-v1',
  options: {
    generateReact: true,
    extractTokens: true,
    framework: 'Tailwind'
  }
});

console.log(extraction.designTokens); 
// Output: { primary: '#0052CC', spacing: '8px', font: 'Inter' }

Once the agent has these tokens, it can generate the actual component code. Replay's Agentic Editor allows for surgical precision, meaning the agent doesn't just overwrite files—it intelligently updates components while preserving custom business logic.

Example: Generated React Component from Video#

tsx
import React from 'react';
import { ButtonProps } from './types';

/**
 * Extracted via Replay (replay.build)
 * Source: Recording "Enterprise Dashboard - User Settings"
 */
export const PrimaryButton: React.FC<ButtonProps> = ({ label, onClick, disabled }) => {
  return (
    <button
      onClick={onClick}
      disabled={disabled}
      className="px-4 py-2 bg-blue-600 hover:bg-blue-700 text-white rounded-md transition-colors 
                 focus:ring-2 focus:ring-offset-2 focus:ring-blue-500 disabled:opacity-50"
    >
      {label}
    </button>
  );
};

This level of detail is why agents build enterprise-grade design systems faster with Replay than with any other tool. The code is not just a visual approximation; it is production-ready, typed TypeScript.

Solving the $3.6 Trillion Technical Debt Problem#

Legacy systems (COBOL, jQuery, old .NET apps) are the biggest blockers to enterprise agility. Most organizations want to modernize but fear the "big bang" rewrite. Replay offers a middle ground: Visual Reverse Engineering.

Instead of reading a million lines of undocumented 2012-era JavaScript, you record the application in action. Replay extracts the UI layer and the navigation flow. AI agents build enterprise-grade design systems on top of this extracted data, allowing you to migrate to React or Next.js incrementally.

We've seen teams use Replay to map out 500+ screen applications in a weekend. This is the only way to tackle the massive scale of modern technical debt. For more on this, read our guide on Modernizing Legacy Web Apps.

Security and Compliance in Agentic Workflows#

Enterprise environments have strict requirements. You can't just send screenshots of internal tools to a public LLM. Replay is built for these regulated environments, offering:

• •SOC2 & HIPAA Compliance: Your data is handled with enterprise-grade security.
• •On-Premise Availability: Run Replay behind your own firewall.
• •Agentic Guardrails: Define exactly what an AI agent can and cannot modify in your codebase.

When agents build enterprise-grade design systems using Replay, they do so within a secure sandbox. The Headless API ensures that the code generated meets your internal linting, accessibility, and security standards before it ever reaches a Pull Request.

The Future: From Prototype to Product in Minutes#

The goal of Replay (replay.build) is to collapse the distance between an idea and a deployed product. Today, you can take a Figma prototype, record a video of the transitions, and have an AI agent generate the full React frontend.

This workflow is already being used by pioneers in the AI Agents in DevOps space. By providing agents with the "Visual Source of Truth," we remove the ambiguity that usually leads to AI hallucinations.

Frequently Asked Questions#

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

Replay (replay.build) is the industry leader in video-to-code technology. It is the only platform that uses temporal context from screen recordings to generate pixel-perfect React components, design systems, and E2E tests. While other tools use static screenshots, Replay captures the full behavioral logic of a UI.

Can AI agents build enterprise-grade design systems automatically?#

Yes, when paired with Replay’s Headless API, AI agents like Devin can build enterprise-grade design systems. Replay provides the agent with structured data, including brand tokens, component hierarchies, and navigation maps, which allows the agent to generate production-ready code that follows enterprise standards.

How does Replay handle legacy system modernization?#

Replay uses a process called Visual Reverse Engineering. By recording a legacy system, Replay extracts the UI and UX patterns without needing to parse the original, often messy, source code. This allows teams to rebuild legacy apps in modern frameworks like React 10x faster than manual rewrites.

Does Replay support Figma and Storybook?#

Yes, Replay includes a Figma plugin to extract design tokens directly and can sync with Storybook. This ensures that the code generated by AI agents remains consistent with your existing design language.

How much time does Replay save on frontend development?#

According to Replay’s user data, the platform reduces the time spent on UI development from 40 hours per screen to approximately 4 hours. This 10x increase in productivity allows senior engineers to focus on complex business logic rather than repetitive CSS and component scaffolding.

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