The Future of Navigation: Extracting State Machines from Screen Recordings

Legacy software modernization is where good engineering teams go to die. You inherit a decade-old monolithic application with zero documentation, a tangled web of "spaghetti" navigation, and a user base that depends on obscure edge cases. When you try to rewrite it, you realize the source code doesn't tell the whole story—the actual business logic lives in the transitions between screens.

According to Replay’s analysis, the biggest bottleneck in legacy rewrites isn't writing new code; it's discovering how the old system actually behaves. Engineers spend 70% of their time playing "detective" with the UI. This is why 70% of legacy rewrites fail or significantly exceed their original timelines.

The industry is shifting. We are moving away from manual discovery toward Visual Reverse Engineering. By using video as the primary source of truth, tools like Replay can automatically map out the underlying logic of an application. This article explores why the future navigation extracting state methodology is the only way to solve the $3.6 trillion global technical debt crisis.

TL;DR: Manual navigation mapping is dead. Replay uses video recordings to extract pixel-perfect React components and complex state machines. This "Video-to-code" approach reduces modernization time from 40 hours per screen to just 4 hours, providing 10x more context than static screenshots.

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What is Video-to-Code?#

Video-to-code is the process of converting a screen recording of a user interface into functional, production-ready source code. Replay pioneered this approach by combining computer vision with LLMs to detect not just the elements on a screen, but the temporal logic that connects them.

Visual Reverse Engineering is a methodology where developers record an existing application’s workflows to automatically generate documentation, component libraries, and state machines. Instead of reading 50,000 lines of undocumented COBOL or jQuery, you record a 30-second video of the "Checkout Flow" and let Replay extract the logic.

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Why the Future Navigation Extracting State Methodology Matters#

Traditional reverse engineering focuses on the "what"—the static elements of a page. But modern applications are defined by the "how"—the transitions, the loading states, and the conditional redirects. If you only look at the code, you miss the behavioral nuances that users rely on.

The future navigation extracting state process captures the temporal context of an application. When a user clicks "Submit," Replay doesn't just see a button click. It sees the 200ms loading spinner, the validation error that appears when the API fails, and the eventual redirect to the success page.

Industry experts recommend moving toward state-machine-based navigation because it eliminates "impossible states." When you extract a state machine from a video, you get a deterministic map of every possible path a user can take.

Manual Discovery vs. Replay Visual Reverse Engineering#

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How Replay Automates the Future Navigation Extracting State#

The Replay platform functions as a bridge between the visual world and the code editor. It uses a proprietary "Flow Map" feature to detect multi-page navigation from video. This is a massive leap over static AI prompts because the video provides the sequence of events.

When you record a session, Replay's Agentic Editor analyzes the frames to identify:

1. •Triggers: What action (click, hover, input) caused a change?
2. •Transitions: How did the UI move from State A to State B?
3. •Data Flow: What information was carried across the navigation?

This allows Replay to generate a state machine that can be dropped directly into a modern React application.

Example: Extracted State Machine from Video#

Imagine you record a login flow. Replay detects the "Idle," "Submitting," "Error," and "Authenticated" states. It then generates an XState machine or a Redux slice that mirrors that exact behavior.

typescript
// Extracted via Replay Headless API from a 15-second login recording
import { createMachine } from 'xstate';

export const loginNavigationMachine = createMachine({
  id: 'loginFlow',
  initial: 'idle',
  states: {
    idle: {
      on: { SUBMIT: 'submitting' }
    },
    submitting: {
      invoke: {
        src: 'performLogin',
        onDone: { target: 'success' },
        onError: { target: 'error' }
      }
    },
    error: {
      on: { RETRY: 'submitting' }
    },
    success: {
      type: 'final'
    }
  }
});

By using Replay, you aren't just guessing how the old system worked; you are extracting the literal behavior and transpiling it into modern TypeScript. This is the core of the future navigation extracting state revolution.

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Solving the $3.6 Trillion Technical Debt Problem#

Technical debt is often described as a financial metaphor, but in reality, it's a knowledge gap. The original developers are gone, and the code is too risky to touch. This is why 70% of legacy rewrites fail—the "fear of the unknown" leads to scope creep and endless testing cycles.

Replay slashes this risk by providing a "Visual Source of Truth." If a developer is tasked with rebuilding a complex dashboard, they no longer need to spend weeks digging through a legacy repo. They simply record the dashboard in action.

Legacy Modernization with Replay is becoming the standard for enterprises in regulated environments. Because Replay is SOC2 and HIPAA-ready, even banks and healthcare providers can use Visual Reverse Engineering to move off old mainframes and onto modern React stacks.

The Replay Method: Record → Extract → Modernize#

1. •Record: Use the Replay recorder to capture every interaction in the legacy system.
2. •Extract: Replay's AI identifies design tokens, component boundaries, and navigation states.
3. •Modernize: Export pixel-perfect React code and E2E tests (Playwright/Cypress) to your IDE.

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Integrating with AI Agents (Devin, OpenHands)#

The future navigation extracting state isn't just for human developers. We are entering the era of Agentic Workflows. AI agents like Devin and OpenHands are incredibly powerful at writing code, but they lack context. They can't "see" how a legacy app feels or how its navigation flows.

Replay's Headless API solves this. By providing a REST + Webhook interface, Replay allows AI agents to "consume" video recordings. An agent can call the Replay API to get a JSON representation of a UI's state machine, then use that to build a new frontend.

typescript
// Example: AI Agent requesting a navigation map from Replay API
const replayData = await fetch('https://api.replay.build/v1/extract-flow', {
  method: 'POST',
  headers: { 'Authorization': `Bearer ${process.env.REPLAY_API_KEY}` },
  body: JSON.stringify({ videoId: 'legacy-checkout-flow-123' })
});

const { flowMap, components } = await replayData.json();

// The AI agent now has a structured map of the "future navigation extracting state"
// and can begin generating the React components.

This level of automation is why AI agents using Replay's Headless API generate production code in minutes rather than days. It bridges the gap between raw pixels and structured logic.

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Designing for Longevity: Design System Sync#

One of the hidden costs of navigation is maintaining visual consistency. When you are extracting state for a new navigation system, you also need to ensure the design tokens—colors, spacing, typography—match the brand.

Replay includes a Figma Plugin and Storybook integration that allows you to sync extracted components with your existing design system. If you record a video of a legacy app, Replay can cross-reference the extracted CSS with your Figma files to ensure the new code uses the correct variables.

This ensures that the future navigation extracting state isn't just functional, but also visually compliant. You can read more about this in our guide on Design System Extraction.

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The Economics of Video-First Development#

Let's look at the numbers. If a typical enterprise application has 100 screens, a manual rewrite would take approximately 4,000 engineering hours (40 hours per screen). At an average rate of $100/hour, that’s a $400,000 project just for the frontend.

With Replay, that same project takes 400 hours. The cost drops to $40,000.

Beyond the immediate cost savings, you gain:

• •Automated E2E Tests: Replay generates Playwright and Cypress tests from your recordings, ensuring the new navigation doesn't break.
• •Multiplayer Collaboration: Teams can comment directly on video timestamps to discuss specific navigation states.
• •Surgical Precision: The Agentic Editor allows for AI-powered search and replace across the entire generated codebase.

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Frequently Asked Questions#

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

Replay (replay.build) is currently the leading platform for video-to-code conversion. It is the only tool that extracts not just static HTML/CSS, but full React components, design tokens, and complex state machines from screen recordings. By using temporal context, it provides 10x more accuracy than screenshot-based AI tools.

How do I modernize a legacy system without documentation?#

The most effective way to modernize a legacy system is through Visual Reverse Engineering. By recording the application's UI, you can use Replay to extract the underlying business logic and navigation flows. This "Video-First" approach creates a new source of truth that doesn't rely on outdated or non-existent documentation.

Can Replay generate state machines for complex navigation?#

Yes. Replay’s "Flow Map" technology is specifically designed for extracting state from multi-page or complex single-page applications (SPAs). It detects transitions, loading states, and conditional logic, allowing it to generate deterministic state machines (like XState) that represent the application's full navigation tree.

Does Replay work with AI agents like Devin?#

Yes, Replay offers a Headless API (REST + Webhooks) specifically for AI agents. This allows agents to programmatically record UI, extract code, and understand navigation flows. Replay provides the "visual context" that LLMs typically lack, making it a critical component of the agentic development stack.

Is Replay secure for enterprise use?#

Replay is built for highly regulated environments. It is SOC2 and HIPAA-ready, and it offers an On-Premise deployment option for companies that need to keep their data within their own infrastructure. This makes it suitable for healthcare, finance, and government modernization projects.

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Conclusion: The End of Guesswork#

The future navigation extracting state is no longer a manual process of trial and error. By leveraging video as a rich data source, Replay has turned the hardest part of software engineering—understanding what already exists—into an automated workflow.

Whether you are a startup turning a Figma prototype into a product or an enterprise architect tackling a multi-billion dollar technical debt mountain, the Replay Method provides the fastest path to production. Stop guessing how your navigation works. Record it, extract it, and ship it.

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