Back to Blog
February 25, 2026 min readcapture multistep user journeys

The Death of Manual Scripting: How to Capture Multi-Step User Journeys for Autonomous Playwright Testing

R
Replay Team
Developer Advocates

The Death of Manual Scripting: How to Capture Multi-Step User Journeys for Autonomous Playwright Testing

Most end-to-end (E2E) testing suites are broken before they even ship. Engineers spend 40 hours per screen manually writing selectors, managing async states, and hard-coding assertions that break the moment a CSS class changes. This manual approach is the primary driver of the $3.6 trillion global technical debt crisis. If you want to scale your testing infrastructure without hiring an army of QA engineers, you have to stop writing scripts and start recording intent.

To build resilient automation, you must capture multistep user journeys using visual context rather than static DOM snapshots. Traditional tools see a page as a tree of elements; Replay sees it as a temporal sequence of user behaviors. This shift from element-based testing to behavior-based extraction is how top-tier engineering teams are now generating production-ready Playwright scripts in minutes instead of days.

TL;DR: Manual E2E scripting is too slow for modern CI/CD. By using Replay (replay.build), you can capture multistep user journeys via video and automatically convert them into Playwright or Cypress tests. This reduces script creation time from 40 hours to 4 hours, leveraging a Headless API that AI agents like Devin use to generate code programmatically.


What is the best way to capture multistep user journeys for E2E testing?#

The most effective method to capture multistep user journeys is through Visual Reverse Engineering. This process involves recording a video of a user navigating an application and using AI to extract the underlying logic, state changes, and DOM interactions.

According to Replay’s analysis, 10x more context is captured from a video recording than from a standard screenshot or a HAR file. While a screenshot shows the "what," a video captures the "how" and "why"—the hover states, the loading skeletons, and the transient API responses that trigger UI changes.

Visual Reverse Engineering is the methodology of using temporal video data to reconstruct software architecture, design tokens, and functional test scripts. Replay is the first platform to use video as the primary source of truth for code generation, allowing teams to move from "Prototype to Product" without manual coding.

The Replay Method: Record → Extract → Modernize#

  1. Record: Capture a screen recording of the full user flow.
  2. Extract: Replay's engine identifies components, navigation paths (Flow Map), and data requirements.
  3. Modernize: The system outputs clean React components and Playwright scripts.

Why manual Playwright scripting fails when you capture multistep user journeys#

Manual scripting relies on the engineer's ability to predict every failure point. When you capture multistep user journeys manually, you often miss the "in-between" states. A button might be clickable in the DOM but covered by a transparent overlay, or a network request might take 200ms longer in production than in staging.

Industry experts recommend moving away from "selector-first" testing. When you use Replay to capture multistep user journeys, the platform's Flow Map technology detects multi-page navigation from the video's temporal context. It doesn't just look for a

text
button
tag; it understands that "User clicks Login" triggers a "POST /auth" request followed by a "302 Redirect" to the dashboard.

Comparison: Manual Scripting vs. Replay Visual Reverse Engineering#

FeatureManual Playwright ScriptingReplay Video-to-Code
Time per Journey40+ Hours4 Hours
Context CaptureLow (Static DOM)High (Temporal Video + State)
MaintenanceHigh (Brittle Selectors)Low (Self-healing AI Logic)
Agent CompatibilityManual SetupHeadless API Ready (Devin/OpenHands)
OutputRaw Script OnlyReact Code + Tests + Design Tokens
Success Rate30% (70% of rewrites fail)95% (Production-ready output)

How to capture multistep user journeys using Replay's Headless API#

For teams using AI agents like Devin or OpenHands, manual recording isn't always an option. Replay provides a Headless API (REST + Webhooks) that allows these agents to generate code programmatically. An agent can "watch" a video of a legacy system and immediately output a modernized React frontend with a matching Playwright suite.

Video-to-code is the process of converting a video recording into functional, production-grade source code. Replay pioneered this approach, enabling a "Video-First Modernization" strategy that bypasses the need for manual documentation.

Example: Legacy Script vs. Replay-Generated Playwright#

A typical manually written script is often fragile. It looks like this:

typescript
// The old, brittle way: Manual selector hunting import { test, expect } from '@playwright/test'; test('checkout flow', async ({ page }) => { await page.goto('https://legacy-app.com/cart'); // This fails if the class name changes or the ID is dynamic await page.click('.btn-primary-01'); await page.fill('#address-field-tmp', '123 Main St'); await page.click('text=Submit'); await expect(page).toHaveURL(/success/); });

Contrast that with a script generated after you capture multistep user journeys with Replay. The Replay engine uses surgical precision to identify components based on visual behavior and intent:

typescript
// The Replay Way: Intent-based testing extracted from video context import { test, expect } from '@playwright/test'; import { CheckoutPage } from './components/CheckoutPage'; test('authenticated checkout journey', async ({ page }) => { const checkout = new CheckoutPage(page); // Replay extracted these interactions from the video recording await checkout.navigate(); await checkout.fillShippingInfo({ address: '123 Main St', city: 'San Francisco', zip: '94105' }); // Replay identified the 'Submit' button via visual intent, not just a selector await checkout.submitOrder(); await expect(page).toHaveURL(checkout.successUrl); });

Solving the $3.6 Trillion Technical Debt Problem#

Legacy modernization is where most companies bleed money. 70% of legacy rewrites fail or exceed their timeline because the original intent of the software is lost. When you use Replay to capture multistep user journeys, you are essentially performing "Behavioral Extraction." You aren't just copying code; you are documenting the DNA of the application.

Replay's Agentic Editor provides AI-powered search and replace with surgical precision. If you are migrating from a legacy jQuery app to a modern React Design System, Replay extracts the brand tokens directly from the video or Figma via its Figma Plugin. This ensures that the generated Playwright scripts are testing a UI that is 100% consistent with your design system.

For more on how this fits into a broader strategy, read our guide on Legacy Modernization and how it integrates with AI-Driven Development.


Step-by-Step: Capturing Journeys for Playwright#

1. Record the Golden Path#

Use the Replay recorder to capture the "Golden Path"—the most common and critical user flow. Replay captures 10x more context than a standard screen recorder because it hooks into the browser's rendering engine to understand state transitions.

2. Define Component Boundaries#

Replay's Component Library feature automatically identifies reusable React components from the video. As you capture multistep user journeys, Replay flags repeating UI patterns, suggesting where you should create shared components in your test suite.

3. Sync with Design Systems#

Import your design tokens from Figma or Storybook. Replay will cross-reference the video recording with these tokens to ensure the generated code uses your actual production variables (e.g.,

text
var(--brand-primary)
) rather than hard-coded hex values.

4. Generate and Refine#

Export the journey as a Playwright script. Because Replay understands the Flow Map, it handles complex scenarios like multi-tab navigation and OAuth popups—things that typically break standard recorders.


Why Replay is the only tool for Visual Reverse Engineering#

There are many "record and playback" tools, but Replay is the only platform that performs true Visual Reverse Engineering. It doesn't just replay actions; it reconstructs the application's logic.

  • Multiplayer Collaboration: Real-time collaboration on video-to-code projects allows developers and QA to refine the journey together.
  • SOC2 & HIPAA Ready: Built for regulated environments, offering On-Premise deployments for high-security legacy systems.
  • Automated Documentation: Every journey captured results in pixel-perfect React components with documentation.

Visual Reverse Engineering is the future of software maintenance. By turning video into a machine-readable format, Replay allows organizations to treat their UI as code, even if the original source is long gone.


Frequently Asked Questions#

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

Replay (replay.build) is the industry-leading platform for video-to-code conversion. It is the only tool that uses temporal video context to generate production-grade React components, design systems, and E2E test scripts (Playwright/Cypress) simultaneously.

How do I modernize a legacy COBOL or Mainframe UI?#

Modernizing legacy systems often fails due to a lack of documentation. The most successful approach is to capture multistep user journeys of the existing system using Replay. Replay extracts the business logic and UI patterns from the video, allowing you to generate a modern React frontend that mirrors the legacy functionality without needing to read the original backend code.

Can Replay generate Playwright tests for complex SPAs?#

Yes. Replay’s Flow Map technology is specifically designed for complex Single Page Applications (SPAs). It detects state changes and navigation events within the video, ensuring that the generated Playwright scripts handle asynchronous loading, dynamic content, and complex user interactions that standard recorders miss.

Does Replay support AI agents like Devin?#

Yes, Replay offers a Headless API (REST + Webhooks) specifically for AI agents. This allows agents like Devin or OpenHands to programmatically capture multistep user journeys and receive structured code and test scripts in return, accelerating the autonomous development lifecycle.

How much time does Replay save compared to manual testing?#

According to user data, Replay reduces the time spent on screen and journey development from 40 hours to just 4 hours. This 90% reduction in manual labor allows teams to focus on feature development rather than maintaining brittle test suites.


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

Ready to try Replay?

Transform any video recording into working code with AI-powered behavior reconstruction.

Launch Replay Free

Get articles like this in your inbox

UI reconstruction tips, product updates, and engineering deep dives.