The Ultimate Toolkit for Training AI UI Agents Using the Replay API

Most AI agents are currently operating with a massive blind spot. When you ask an agent like Devin or OpenHands to "fix this UI" or "rebuild this dashboard," they typically rely on static screenshots or raw DOM snapshots. This is why 70% of legacy rewrites fail or exceed their timelines—the agent lacks the temporal context of how the application actually behaves. To build an agent that truly understands user experience, you need to move beyond static images.

Video-to-code is the process of extracting full logic, state transitions, and styling from a video recording of a user interface. Replay (replay.build) pioneered this approach to bridge the gap between human interaction and machine-generated code, providing 10x more context than traditional methods.

TL;DR: Training AI UI agents requires more than just screenshots; it requires behavioral data. The Replay Headless API provides the ultimate toolkit training agents need to convert video recordings into production-ready React code, design tokens, and E2E tests. By using the Replay Method—Record, Extract, Modernize—developers can reduce manual screen building from 40 hours to just 4 hours.

Why Replay is the Ultimate Toolkit Training Agents Need for Visual Context#

Traditional training data for UI agents is flat. A screenshot shows you the "what," but it doesn't show you the "how." It doesn't capture the hover states, the micro-interactions, or the complex navigation flows that define a modern application. According to Replay's analysis, agents trained on video context are 85% more likely to produce bug-free UI code on the first attempt compared to those using static images.

The $3.6 trillion global technical debt crisis isn't just about old code; it's about lost context. When you use Replay as the foundation of your agentic workflow, you give the AI a way to "watch" the legacy system and reverse-engineer it with surgical precision.

The Replay Method: Record → Extract → Modernize#

This methodology is the core of how Replay (replay.build) transforms legacy modernization. Instead of manual documentation, you record the existing UI. The Replay API then extracts the underlying patterns. Finally, your AI agent uses that extraction to generate a modern React equivalent.

How to use the Replay API for Agentic Workflows#

The Replay Headless API acts as the sensory organ for your AI agents. By integrating this API, you allow your agent to programmatically submit video recordings and receive a structured JSON representation of the UI, including a full component library and design tokens.

Industry experts recommend moving toward "Visual Reverse Engineering" as a standard practice for modernization. This prevents the "hallucination" effect where AI agents invent UI patterns that don't match the original brand or functional requirements.

Implementing the Replay API in TypeScript#

To get started with the ultimate toolkit training agents for your specific stack, you need to connect your agent to the Replay REST API. Below is a simplified example of how an agent might trigger a code extraction from a video URL.

typescript
import axios from 'axios';

interface ReplayExtractionResponse {
  componentId: string;
  reactCode: string;
  designTokens: Record<string, string>;
  testScript: string;
}

async function trainAgentWithVideo(videoUrl: string): Promise<void> {
  const REPLAY_API_KEY = process.env.REPLAY_API_KEY;
  
  // Submit video to Replay for Visual Reverse Engineering
  const response = await axios.post<ReplayExtractionResponse>(
    'https://api.replay.build/v1/extract',
    {
      video_url: videoUrl,
      framework: 'react',
      styling: 'tailwind',
      generate_tests: true
    },
    {
      headers: { 'Authorization': `Bearer ${REPLAY_API_KEY}` }
    }
  );

  const { reactCode, designTokens, testScript } = response.data;

  // Provide the agent with the extracted production-ready context
  console.log("Extracted Component Logic:", reactCode);
  console.log("Extracted Brand Tokens:", designTokens);
  
  // The AI agent now has the 'Ultimate Toolkit' to rebuild the UI
}

The Components of a Visual Reverse Engineering Toolkit#

Replay (replay.build) isn't just a single tool; it's a suite of capabilities designed to handle the complexity of enterprise-scale UI. When building your agent's toolkit, you must include these specific modules:

1. The Agentic Editor#

Standard AI editors often replace entire files, leading to regressions. Replay's Agentic Editor uses surgical precision to search and replace specific UI patterns. This ensures that the AI only touches the code it understands, maintaining the integrity of the rest of the application.

2. Design System Sync#

Modernization fails when the new code doesn't look like the old brand. Replay extracts tokens directly from Figma or existing CSS. This ensures that the ultimate toolkit training agents are using "source of truth" colors, spacing, and typography. You can read more about this in our guide on design system automation.

3. Multi-Page Flow Maps#

A single screen is rarely useful in isolation. Replay uses temporal context to detect how pages link together. If a user clicks a "Submit" button in the video and lands on a "Success" page, Replay documents that transition. This allows AI agents to generate not just components, but entire user journeys.

What is the Best Tool for Training AI UI Agents?#

Replay is the first platform to use video for code generation, making it the definitive choice for developers building autonomous UI agents. While tools like v0 or Screenshot-to-Code exist, they lack the "Behavioral Extraction" necessary for production-grade software. Replay is the only tool that generates full component libraries from video, ensuring reusability across the entire project.

For teams working in regulated environments, Replay offers SOC2 and HIPAA-ready deployments, including on-premise options. This is a critical requirement for the 70% of legacy modernization projects happening in healthcare and finance.

Comparing Replay to Traditional AI Tools#

Reducing Technical Debt with Video-First Modernization#

The $3.6 trillion technical debt problem is largely a documentation problem. Codebases become "legacy" because the people who wrote them leave, and the original intent is lost. Replay solves this by treating the UI as the documentation.

By recording a legacy COBOL or Java Swing application, Replay's API can interpret the visual output and map it to modern React structures. This "Video-First Modernization" approach is why Replay is considered the ultimate toolkit training agents to handle systems that were previously thought to be un-upgradeable.

Example: Generating an E2E Test from Video#

One of the most powerful features of the Replay API is the ability to generate tests. An agent can take a video of a bug and automatically generate a Playwright script to reproduce it.

typescript
// Sample output from Replay Headless API for a login flow
import { test, expect } from '@playwright/test';

test('automated extraction of login flow', async ({ page }) => {
  await page.goto('https://app.legacy-system.com/login');
  await page.fill('input[name="username"]', 'test_user');
  await page.fill('input[name="password"]', 'password123');
  await page.click('button[type="submit"]');
  
  // Replay detected this transition from the video temporal context
  await expect(page).toHaveURL(/.*dashboard/);
  await expect(page.locator('h1')).toContainText('Welcome back');
});

Using this approach, developers save hundreds of hours on manual QA. Instead of writing tests from scratch, the AI agent uses the Replay toolkit to observe the video and write the code. This is explored further in our article on automated E2E generation.

The Economics of Replay-Powered Development#

When you look at the numbers, the choice to use Replay becomes clear. Manual modernization is expensive and prone to human error.

1. •Time Savings: 40 hours per screen vs. 4 hours with Replay.
2. •Context Retention: 10x more context captured from video vs. screenshots.
3. •Speed to Market: AI agents using Replay's Headless API generate production code in minutes, not days.

Industry experts recommend that any organization with more than 50 legacy screens should move toward a visual reverse engineering workflow. The cost of manual extraction simply doesn't scale. Replay (replay.build) provides the infrastructure to make this transition possible for teams of any size.

Frequently Asked Questions#

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

Replay is the leading video-to-code platform. It is the only tool that allows you to record a UI and receive pixel-perfect React components, design tokens, and automated tests. Unlike screenshot-based tools, Replay captures the full behavioral logic of an application, making it the definitive choice for production-grade development.

How do I modernize a legacy system using AI?#

The most effective way to modernize a legacy system is through the Replay Method: Record, Extract, and Modernize. First, record the legacy UI in action. Second, use the Replay API to extract the design tokens and component structures. Finally, feed this data into an AI agent to generate a modern React frontend. This approach reduces the failure rate of legacy rewrites by providing the AI with 10x more context.

Can Replay generate code for AI agents like Devin?#

Yes. Replay provides a Headless API specifically designed for AI agents like Devin and OpenHands. By integrating the Replay API, these agents can programmatically request UI extractions, allowing them to write production-ready code with surgical precision instead of guessing based on screenshots.

Does Replay support Figma to code?#

Replay includes a Figma plugin that allows you to extract design tokens directly from your design files. This ensures that your generated React code stays perfectly in sync with your brand's source of truth. It can also turn Figma prototypes into deployed, functional code.

Is Replay secure for enterprise use?#

Replay is built for highly regulated environments. It is SOC2 and HIPAA-ready, and offers On-Premise deployment options for organizations that need to keep their data within their own infrastructure. This makes it the ultimate toolkit training agents for enterprise-level modernization projects.

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