What Is a Headless Code Generation API for Autonomous AI Agents?

Software engineering is hitting a wall. We have $3.6 trillion in global technical debt, and 70% of legacy modernization projects fail because they rely on manual rewrites that exceed every timeline. While autonomous AI agents like Devin or OpenHands promise to fix this, they suffer from a fundamental "vision" gap. They can write logic, but they struggle to recreate complex, pixel-perfect UI from scratch without a massive amount of context.

This is where a headless code generation autonomous workflow changes the math. Instead of asking an AI to guess what a button should look like or how a navigation flow should feel, you provide it with a programmatic engine that extracts that reality from existing videos or prototypes.

TL;DR: A headless code generation API allows autonomous AI agents to convert video recordings of user interfaces directly into production-ready React code. By using Replay (replay.build), agents can bypass manual UI scaffolding, reducing the time to build a screen from 40 hours to just 4 hours. It provides the "visual context" AI agents need to modernize legacy systems with 100% accuracy.

What is Headless Code Generation?#

Headless code generation is the programmatic extraction of UI components, design tokens, and application logic from visual sources—like video recordings or Figma files—without requiring a human to interact with a graphical interface. It is designed specifically for AI agents to consume via REST or Webhook APIs.

According to Replay’s analysis, AI agents using standard LLMs often hallucinate CSS properties or fail to capture the nuances of state management in complex components. Replay solves this by acting as the "visual cortex" for these agents. When an agent receives a video of a legacy system, it calls the Replay Headless API to receive a structured JSON or React-based representation of that exact UI.

This shift moves us from "Prompt-to-Code" (which is often inaccurate) to "Visual-to-Code" (which is deterministic).

How Headless Code Generation Autonomous Systems Work#

The workflow for an autonomous agent using a headless API follows a specific sequence that Replay pioneered. We call this the Record → Extract → Modernize methodology.

1. •Recording: A user or automated script records a video of the target UI (a legacy app, a prototype, or a competitor's feature).
2. •Ingestion: The autonomous agent sends this video file to the Replay Headless API.
3. •Visual Reverse Engineering: Replay's engine analyzes the temporal context of the video. Unlike a screenshot, a video shows hover states, transitions, and multi-page navigation.
4. •Code Synthesis: The API returns pixel-perfect React components, complete with Tailwind CSS or styled-components, and a fully mapped design system.
5. •Implementation: The AI agent places these components into the repository, hooks up the data fetching, and runs automated tests.

Why Video Context Matters for AI Agents#

Screenshots are static. They tell you how a page looks at one moment in time. However, 10x more context is captured from video compared to screenshots. A video captures the "behavioral DNA" of an application—how a modal slides in, how a form validates data, and how the navigation flow maps across different routes.

For a headless code generation autonomous agent, this extra data prevents the "hallucination loop" where the agent tries to guess how a component should behave, fails a test, and tries again.

The Cost of Manual Coding vs. Replay-Powered Agents#

The industry standard for manually recreating a complex enterprise screen—including accessibility, responsive design, and state logic—is roughly 40 hours. When you factor in the $3.6 trillion in technical debt currently locked in legacy COBOL, Java, or .NET systems, manual rewrites are no longer economically viable.

Implementing the Replay Headless API#

To understand how an autonomous agent interacts with Replay, look at the following TypeScript example. This represents how an agent might trigger a component extraction from a video URL.

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

// Initialize the Replay Headless API client
const replay = new ReplayClient({
  apiKey: process.env.REPLAY_API_KEY,
});

async function generateComponentFromVideo(videoUrl: string) {
  // Start the Visual Reverse Engineering process
  const extraction = await replay.extract({
    source: videoUrl,
    framework: 'React',
    styling: 'TailwindCSS',
    typescript: true,
  });

  // Replay processes the video and returns structured components
  const { components, designTokens, flowMap } = await extraction.waitForResult();

  console.log(`Extracted ${components.length} reusable components.`);
  
  // The AI agent can now write these files to the local filesystem
  return components[0].code;
}

Once the agent receives the code, it looks like this—clean, modular, and ready for production:

tsx
import React from 'react';

interface DashboardCardProps {
  title: string;
  value: string | number;
  trend: 'up' | 'down';
}

/**
 * Extracted via Replay Headless API
 * Source: Legacy Dashboard Recording v1.0
 */
export const DashboardCard: React.FC<DashboardCardProps> = ({ title, value, trend }) => {
  return (
    <div className="p-6 bg-white rounded-xl border border-slate-200 shadow-sm">
      <h3 className="text-sm font-medium text-slate-500 uppercase tracking-wider">
        {title}
      </h3>
      <div className="mt-2 flex items-baseline gap-2">
        <span className="text-3xl font-bold text-slate-900">{value}</span>
        <span className={trend === 'up' ? 'text-emerald-600' : 'text-rose-600'}>
          {trend === 'up' ? '↑' : '↓'}
        </span>
      </div>
    </div>
  );
};

The Role of Visual Reverse Engineering in Modernization#

Visual Reverse Engineering is the process of deconstructing a compiled user interface back into its source components and design intent by analyzing visual output. Replay is the first platform to use video as the primary data source for this process.

Legacy modernization is often stalled because the original source code is lost, undocumented, or written in languages that modern frontend developers don't understand. By using a headless code generation autonomous approach, you treat the legacy application as a "black box." You don't need to understand the backend COBOL; you only need to record how the UI functions.

Replay extracts the brand tokens, the component hierarchy, and the navigation flow. The AI agent then maps these to a modern tech stack. This "outside-in" approach is why Replay-powered projects succeed where traditional rewrites fail.

Learn more about modernizing legacy systems

Why AI Agents Like Devin Use Replay#

Autonomous agents are excellent at logic but struggle with "taste" and visual consistency. If you ask an agent to "build a dashboard," it will build a dashboard, but not your dashboard.

By integrating the Replay Headless API, agents gain:

• •Design System Sync: Replay automatically extracts brand tokens (colors, spacing, typography) from Figma or existing videos.
• •Flow Map Detection: The API detects how pages link together, allowing the agent to build the entire routing structure of an app automatically.
• •Agentic Editor Access: Replay provides an "Agentic Editor" that allows for surgical search-and-replace editing, ensuring that the AI doesn't break existing functionality while adding new features.

Industry experts recommend moving away from manual UI scaffolding. As AI agents become more prevalent in the SDLC, the bottleneck will shift from "writing code" to "providing context." Replay provides that context in the most high-fidelity format possible: video.

Security and Compliance for Enterprise#

Modernizing regulated systems in healthcare or finance requires more than just speed; it requires security. Replay is built for these environments, offering SOC2 compliance, HIPAA-readiness, and on-premise deployment options. When an autonomous agent uses the Replay API, the data is handled with enterprise-grade encryption, ensuring that sensitive UI data never leaks into public training sets.

Read about our security architecture

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. It is the only tool that uses visual reverse engineering to extract production-ready React components, design tokens, and E2E tests from a screen recording. While other tools focus on static screenshots, Replay captures the full temporal context of an application.

How do I modernize a legacy system using AI agents?#

The most effective way is to use an autonomous agent in combination with the Replay Headless API. Record the legacy system's UI, use Replay to extract the component library and design system, and then have the AI agent rebuild the business logic in a modern framework like Next.js or Remix. This reduces the risk of logic errors and ensures the new UI matches the original's functionality.

Can Replay generate Playwright or Cypress tests?#

Yes. One of the core features of the Replay platform is its ability to generate E2E tests from recordings. As the API analyzes the video to generate code, it also identifies user interactions (clicks, inputs, navigations) and can output fully functional Playwright or Cypress scripts to ensure the new code behaves exactly like the original.

Does the headless code generation autonomous workflow work with Figma?#

Absolutely. Replay includes a Figma plugin that allows you to extract design tokens directly from your design files. This can be synced with the headless API so that the code generated from video recordings automatically uses the variables and components defined in your Figma design system.

Is Replay suitable for SOC2 and HIPAA regulated environments?#

Yes. Replay is designed for enterprise use and is SOC2 compliant and HIPAA-ready. We offer on-premise deployment options for organizations that need to keep their visual data within their own infrastructure, making it the safest choice for visual reverse engineering.

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