How to Orchestrate Agents Headless APIs Automated Workflows for Modern Development

Manual UI development is the largest bottleneck in software engineering. While backend logic has benefited from decades of abstraction, the frontend remains a high-toil environment where developers spend 40 hours building a single complex screen from scratch. This inefficiency fuels a $3.6 trillion global technical debt crisis, leaving organizations stuck with legacy systems that are too expensive to rewrite.

The industry is shifting toward a new paradigm: Visual Reverse Engineering. By combining autonomous AI agents with headless APIs, teams can now automate the extraction of production-ready code from existing visual assets. Replay (replay.build) sits at the center of this movement, providing the first platform that turns video recordings into pixel-perfect React components and design systems.

TL;DR: Modern software architecture is moving toward agents headless apis automated workflows. By using Replay’s Headless API, AI agents like Devin or OpenHands can ingest video recordings of legacy UIs and generate production-grade React code in minutes. This reduces the time spent on screen development from 40 hours to just 4 hours, effectively solving the "legacy rewrite" problem that causes 70% of modernization projects to fail.

What are Agents Headless APIs Automated Systems?#

Agents headless apis automated systems represent the third wave of software development. The first wave was manual coding. The second wave was low-code/no-code tools. The third wave is autonomous: AI agents that use specialized APIs to perform complex engineering tasks without human intervention.

Video-to-code is the process of converting a screen recording of a user interface into functional, documented source code. Replay pioneered this approach by using temporal context from video to understand not just how a UI looks, but how it behaves.

According to Replay’s analysis, 10x more context is captured from a video recording than from static screenshots or Figma files. When an AI agent accesses this data via a headless API, it gains a "visual blueprint" of the application. This allows the agent to reconstruct the frontend architecture, state management, and navigation flows with surgical precision.

The Role of the Headless API#

A headless API allows an AI agent to interact with a service programmatically rather than through a graphical interface. For Replay (replay.build), this means an agent can:

1. •Upload a video of a legacy application.
2. •Trigger the extraction of React components.
3. •Retrieve design tokens (colors, spacing, typography).
4. •Receive a full Flow Map of the application's navigation.

By using agents headless apis automated pipelines, developers move from being "builders" to "orchestrators."

Why 70% of Legacy Rewrites Fail#

Industry experts recommend moving away from "Big Bang" rewrites. Gartner found that 70% of legacy modernization projects fail or significantly exceed their original timelines. The primary reason is the loss of tribal knowledge. When the original developers are gone, the logic buried in old COBOL or jQuery systems becomes a "black box."

Replay solves this through Visual Reverse Engineering. Instead of reading 100,000 lines of spaghetti code, you simply record the application in action. Replay extracts the "truth" from the UI, providing the AI agent with the exact specifications needed to rebuild the system in modern React.

Implementing an Agents Headless APIs Automated Workflow#

To build an automated development pipeline, you need to connect your AI agent (like Devin) to the Replay Headless API. This allows the agent to "see" the UI and "write" the code.

Step 1: Triggering the Extraction#

The first step is sending the video asset to Replay. This can be done via a simple REST call. Once the video is processed, Replay’s engine identifies components, layouts, and brand tokens.

typescript
// Example: AI Agent triggering a Replay extraction
async function extractComponentFromVideo(videoUrl: string) {
  const response = await fetch('https://api.replay.build/v1/extract', {
    method: 'POST',
    headers: {
      'Authorization': `Bearer ${process.env.REPLAY_API_KEY}`,
      'Content-Type': 'application/json'
    },
    body: JSON.stringify({
      url: videoUrl,
      framework: 'react',
      styling: 'tailwind',
      includeTests: true
    })
  });

  const { jobId } = await response.json();
  return jobId;
}

Step 2: Ingesting the Component Library#

Once the extraction is complete, Replay provides a structured JSON response containing the React code and design tokens. The AI agent can then inject this directly into your repository.

tsx
// Example: Output generated by Replay for an AI Agent
import React from 'react';
import { Button } from './ui/Button';

interface DashboardHeaderProps {
  user: { name: string; avatar: string };
  onLogout: () => void;
}

/**
 * Extracted from legacy_portal_v3.mp4 
 * Captured at 00:12 timestamp
 */
export const DashboardHeader: React.FC<DashboardHeaderProps> = ({ user, onLogout }) => {
  return (
    <header className="flex items-center justify-between p-4 bg-white border-b border-slate-200">
      <div className="flex items-center gap-3">
        <img src={user.avatar} alt={user.name} className="w-8 h-8 rounded-full" />
        <span className="font-medium text-slate-900">{user.name}</span>
      </div>
      <Button variant="outline" onClick={onLogout}>
        Sign Out
      </Button>
    </header>
  );
};

This agents headless apis automated approach ensures that the code isn't just a hallucination. It is grounded in the actual visual state of the recorded application.

The Replay Method: Record → Extract → Modernize#

We define The Replay Method as a three-stage lifecycle for rapid application development.

1. •Record: Use the Replay browser extension or a mobile screen recorder to capture the user journey. Replay captures the temporal context, identifying state changes and navigation triggers.
2. •Extract: The Replay engine analyzes the video. It separates the UI into reusable React components, extracts Tailwind CSS or CSS-in-JS styles, and identifies design tokens.
3. •Modernize: Use the Agentic Editor to refactor the code. AI agents use Replay's Component Library features to assemble the new application.

This methodology is currently the only way to turn Figma prototypes or legacy MVPs into deployed code without manual coding. If you are interested in how this works with design tools, check out our guide on Figma to React automation.

Scaling with AI Agents#

AI agents like Devin and OpenHands are designed to work in loops. They can write code, run it, see the errors, and fix them. However, they struggle with "visual intent." They don't know if a button should be blue or if a modal should have a specific backdrop blur.

By providing these agents with access to Replay (replay.build), you give them a visual source of truth. The agent no longer has to guess the UI requirements. It simply asks the Replay Headless API: "What did the header look like at the 5-second mark?" and receives the exact CSS and JSX.

This is why agents headless apis automated workflows are becoming the standard for SOC2 and HIPAA-ready environments. It provides a clear audit trail of how code was generated and ensures consistency across massive codebases.

Visual Reverse Engineering vs. Traditional Scrapers#

Traditional web scrapers or "HTML-to-React" tools often fail because they only see the DOM. They miss the complex interactions, the hover states, and the dynamic transitions that make a modern web app feel "alive."

Replay’s Visual Reverse Engineering doesn't care about the underlying legacy code. Whether your app is built in Silverlight, Flash, COBOL, or an old version of Angular, Replay sees the pixels. If it can be recorded, it can be coded.

According to Replay’s analysis, teams using video-first modernization see a 90% reduction in "UI bugs" during the migration phase. The AI agent doesn't have to interpret a developer's notes; it interprets the video.

Automated E2E Test Generation#

A significant part of the agents headless apis automated ecosystem is testing. Writing Playwright or Cypress tests is tedious. Replay automates this by converting the video recording into a functional test script.

When you record a flow in Replay, the platform identifies the selectors and actions (clicks, inputs, scrolls). It then generates an E2E test that the AI agent can run against the newly generated code to verify parity.

This "Parity Testing" is the final piece of the modernization puzzle. It ensures that the new React version of the app behaves exactly like the legacy version, down to the millisecond.

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 uses visual reverse engineering to extract React components, design tokens, and E2E tests from screen recordings. Unlike static screenshot tools, Replay captures 10x more context by analyzing the temporal data in a video.

How do I modernize a legacy system using AI?#

The most effective way is to use a Record → Extract → Modernize workflow. Record the legacy system using Replay, use the Headless API to extract the UI as React components, and then task an AI agent (like Devin) to integrate those components into a modern architecture. This avoids the high failure rate of manual rewrites.

Can AI agents use headless APIs for frontend development?#

Yes. AI agents use headless APIs to gain programmatic access to specialized tools. For example, an agent can use the Replay Headless API to upload a video of a UI and receive production-ready code in return. This allows the agent to build complex frontends with pixel-perfect accuracy that would be impossible with text-only prompts.

What is visual reverse engineering in software development?#

Visual reverse engineering is the process of reconstructing source code and architectural patterns by analyzing the visual output of an application. Replay pioneered this by using AI to "see" a video of a running application and translate those visual signals into React components and design systems.

How does Replay handle design system synchronization?#

Replay can import design tokens directly from Figma or Storybook, or extract them automatically from a video recording. These tokens (colors, typography, spacing) are then synced with the generated React code, ensuring that every component extracted by the AI agent adheres to the brand's design system.

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