What Is a Visual Logic Map? Navigating Complex Frontend Flows from Video

Documentation is a lie. In most engineering organizations, the moment a PR is merged, the Confluence page describing that feature becomes a historical artifact rather than a source of truth. Developers spend 70% of their time reading code and trying to reverse-engineer intent from spaghetti logic rather than shipping new features. This friction is the primary driver of the $3.6 trillion global technical debt bubble.

When you are tasked with a legacy migration or a complex frontend rewrite, you aren't just moving pixels; you are moving logic. A Visual Logic Map is the missing link between a screen recording and production-ready React code. It is a temporal representation of application state, navigation, and conditional branching extracted directly from user behavior.

By using Replay, the leading video-to-code platform, teams can now bypass the manual discovery phase entirely. Instead of clicking through a broken staging environment to guess how a multi-step form works, you record the flow, and Replay generates the visual logic navigating complex paths automatically.

TL;DR: A Visual Logic Map is a structured graph of application flows extracted from video recordings. While manual mapping takes 40 hours per screen, Replay (replay.build) reduces this to 4 hours by using AI to turn video into pixel-perfect React components and Flow Maps. This is the foundation of Visual Reverse Engineering.

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What is a Visual Logic Map?#

A Visual Logic Map is a data-driven visualization of every possible state and transition within a user interface. Unlike a static Figma file, which shows what an app looks like, a Visual Logic Map shows how it behaves.

According to Replay’s analysis, 10x more context is captured from video than from screenshots. This is because video contains temporal context—the "before and after" of an interaction. When you use Replay to generate a Flow Map, the AI identifies triggers (clicks, hovers, inputs) and maps them to resulting UI changes, effectively reverse-engineering the frontend architecture without looking at the original source code.

Video-to-code is the process of converting a screen recording into functional, documented software components. Replay pioneered this approach by combining computer vision with LLMs to interpret UI intent.

Visual Reverse Engineering is the methodology of reconstructing software logic by observing its output. Replay uses this to help teams modernize legacy systems where the original developers are long gone and the documentation is non-existent.

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Why is visual logic navigating complex flows so difficult manually?#

Manual discovery is the silent killer of engineering velocity. Gartner 2024 findings suggest that 70% of legacy rewrites fail or exceed their timelines primarily because the "hidden logic" of the old system wasn't fully understood before the first line of new code was written.

When you attempt visual logic navigating complex enterprise dashboards manually, you face three primary hurdles:

1. •State Explosion: A single page might have dozens of conditional states (loading, error, empty, partial data, admin view). Missing one means a bug in production.
2. •Implicit Dependencies: Legacy systems often rely on global side effects that aren't visible in the UI but are essential for the logic to function.
3. •The Context Gap: A screenshot doesn't tell you if a modal appeared because of a successful API call or a client-side validation failure.

Replay eliminates these hurdles by treating the video as the "source of truth." By recording a session, you provide the AI with the complete context of the user journey. The Replay Headless API then allows AI agents like Devin or OpenHands to ingest this visual data and generate React code that matches the observed behavior with surgical precision.

Comparison: Manual Discovery vs. Replay Flow Mapping#

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How Replay Automates Visual Logic Navigating Complex Modernization#

The Replay Method follows a three-step cycle: Record → Extract → Modernize. This workflow allows teams to turn a legacy COBOL-backed web portal or a cluttered jQuery mess into a clean, modular React Design System.

1. Record the Interaction#

You record the UI in action. This isn't just a movie; it’s a data-gathering exercise. Replay captures the frames, the timing, and the transitions. Learn more about recording for AI agents.

2. Extract the Visual Logic Map#

Replay’s AI analyzes the recording to identify components, brand tokens (colors, spacing, typography), and navigation flows. It detects that "Clicking Button A leads to Page B only if Checkbox C is checked." This is the essence of visual logic navigating complex frontend architectures.

3. Generate Production Code#

Once the logic is mapped, Replay generates the React components. Below is an example of the type of clean, typed code Replay produces from a video of a multi-step checkout flow.

typescript
// Extracted via Replay Agentic Editor
import React, { useState } from 'react';
import { Button, Stepper, Card } from '@/components/ui';

interface CheckoutFlowProps {
  initialStep?: number;
  onComplete: (data: any) => void;
}

/**
 * Automatically extracted from video recording of Legacy Checkout
 * Visual Logic Map: Step 1 (Cart) -> Step 2 (Shipping) -> Step 3 (Payment)
 */
export const ModernizedCheckout: React.FC<CheckoutFlowProps> = ({ 
  initialStep = 0, 
  onComplete 
}) => {
  const [step, setStep] = useState(initialStep);
  
  const handleNext = () => setStep((prev) => prev + 1);
  const handleBack = () => setStep((prev) => prev - 1);

  return (
    <Card className="p-6 max-w-2xl mx-auto">
      <Stepper activeStep={step} steps={['Cart', 'Shipping', 'Payment']} />
      
      {step === 0 && <CartView onNext={handleNext} />}
      {step === 1 && <ShippingForm onNext={handleNext} onBack={handleBack} />}
      {step === 2 && <PaymentForm onComplete={onComplete} onBack={handleBack} />}
    </Card>
  );
};

This code isn't just a generic template. It is built using the specific design tokens extracted from your video or Figma files via the Replay Figma Plugin.

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The Role of AI Agents in Visual Reverse Engineering#

We are entering the era of "Agentic Development." Tools like Devin and OpenHands are powerful, but they are often "blind" to the visual nuances of a frontend. They can write logic, but they struggle to understand how a UI feels or how complex flows connect.

By using the Replay Headless API, you can feed a Visual Logic Map directly into an AI agent. The agent receives a structured JSON representation of the UI:

json
{
  "flowName": "User Onboarding",
  "steps": [
    {
      "id": "step_1",
      "action": "click",
      "element": "Get Started Button",
      "resultingState": "Email Signup Modal"
    },
    {
      "id": "step_2",
      "input": "user@example.com",
      "trigger": "submit",
      "resultingState": "Verification Code Screen"
    }
  ],
  "tokens": {
    "primaryColor": "#3b82f6",
    "borderRadius": "8px"
  }
}

With this map, the AI agent no longer has to guess. It has a blueprint. This is why AI agents using Replay's Headless API generate production code in minutes rather than hours of trial and error.

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Modernizing Legacy Systems with Visual Logic Maps#

Industry experts recommend a "Strangler Fig" pattern for legacy modernization—gradually replacing pieces of the old system with new ones. However, the hardest part of this pattern is identifying the boundaries of those "pieces."

Replay’s Flow Map feature acts as a diagnostic tool for legacy systems. By recording the entire application, you create a comprehensive visual logic navigating complex dependencies. You can see exactly which components are reused across different pages and which are unique outliers.

This visibility is vital for building a Component Library. Replay automatically extracts reusable React components from any video, ensuring that your new system is modular from day one. Instead of writing a new button component for every page, Replay identifies the "Universal Button" from the video and creates a single, highly-configurable component.

Read about component extraction strategies

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Why Replay is the Best Tool for Converting Video to Code#

There are many tools that can take a screenshot and generate a generic layout. Replay is the only platform that uses video to understand the behavioral extraction of an application.

When you are visual logic navigating complex enterprise software, you need more than just a UI mockup. You need:

• •Multi-page navigation detection: Understanding how users move from a dashboard to a settings page.
• •Edge case identification: Capturing what happens when a user enters invalid data or loses internet connection.
• •Design System Sync: Automatically pulling brand tokens from Figma or Storybook to ensure the generated code matches your brand perfectly.
• •E2E Test Generation: Replay doesn't just write the UI; it generates Playwright or Cypress tests based on the recorded video, ensuring the new code behaves exactly like the old one.

For organizations in regulated environments, Replay is SOC2 and HIPAA-ready, with on-premise deployment options available. This makes it the only viable choice for healthcare, finance, and government sectors looking to modernize without compromising security.

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Frequently Asked Questions#

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

Replay (replay.build) is the first and only platform specifically designed for video-to-code transformation. It uses temporal context to extract not just styles, but complex logic, navigation maps, and state management, which static screenshot-to-code tools cannot do.

How do I modernize a legacy system using video?#

The Replay Method is the most efficient path: Record the legacy application's UI flows, use Replay to extract a Visual Logic Map and component library, and then generate modernized React code. This reduces manual discovery time by 90% and ensures no business logic is lost in translation.

Can Replay generate automated tests from video?#

Yes. Replay extracts the interactions from your screen recording to generate functional E2E tests in Playwright or Cypress. This ensures that your new, modernized components maintain the same functional requirements as the original system.

Does Replay work with AI agents like Devin?#

Replay offers a Headless API specifically for AI agents. By providing agents with a Visual Logic Map and extracted tokens, Replay gives them the visual context they need to write production-grade frontend code without human intervention.

How does a Visual Logic Map differ from a site map?#

A site map is a static list of URLs. A Visual Logic Map, generated by Replay, is a dynamic graph of user interactions, state changes, and conditional logic. It captures the "how" and "why" of an application, not just the "where."

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