Playwright Is Dead, Long Live AI Automation Testing

Kevin Wu

Co-Founder of Slash.cool

It was a summer afternoon in a Starbuck café August 2025.

My friend Mark and I met in a coffee shop to discuss the recent development of AI, the air thick with caffeine and the rhythmic tapping of programmers' keyboards.

The sound felt both familiar and distant—I'd been away from traditional offices for over half a year, using AI programming to develop my own products and build a small startup. While, I listened to my friend Mark complaining and recent frustration: How to using AI to test AI?

Mark works in test automation at a big tech company and has always been a die-hard Playwright fan. Yet today, he was complaining about testing's breakdowns in his projects:

"Our tech boss has gone crazy," he sighed.

"He wants to do this so-called 'AI refactor.' To fix all the security issues caused by AI-written code, we have to rewrite a massive amount of Playwright tests and figure out how to test AI products—and even how to use AI to test AI."

I put down my coffee and said, "You should try AI automation testing."

I knew this wasn't just his problem, with the rise of "AI vibe coding," traditional testing frameworks are struggling to keep up. Testing AI-powered products requires a fundamentally different approach.

There are still some companies out there who do manual testing, and they build a website and they basically manually click, yes I used to do this too.

Not all companies are there yet; some people are still not testing, some are still doing manual testing, and some people are doing automation testing and have their workflow.

Playwright is dead; it's time to embrace AI automation testing.

I've heard many people discuss the limitations of Playwright in the AI era, We're all AI-focused at the moment, the world has gone AI crazy.

Does Playwright no longer fit into today's AI-led development workflow?

Let me be direct: Yes, but Playwright + AI Automation has a brighter future.

Playwright: The Last Mile of Code-Based Testing

In the history of automated testing, Playwright absolutely deserves its place.

Playwright brought a unified API for testing across Chromium, Firefox, and WebKit, making cross-browser testing easier. It made end-to-end testing smoother and more efficient than ever before—arguably the peak of "code-based testing."

It's alse cross-language. Use the Playwright API in TypeScript, JavaScript, Python, .NET, Java.

It provides a series of powerful tools like Codegen. Generate tests by recording your actions, save them into any language.

Playwright automatically waits for elements to be actionable before performing actions, providing flexible and stable testing through its built-in auto-wait mechanism.

You can also use Tracing to debug test failures. Configure test retry strategy, capture execution trace, videos, screenshots to eliminate flakes, it also has a rich set of introspection events.

But its greatest strength is also the reason it's now outdated.

At its core, Playwright is still about "controlling the browser with code." Every page.click() and every CSS selector is an instruction you have to explicitly tell the browser to execute.

Why Traditional Testing Tools Fail in Modern Teams

XPaths are not always reliable

When developers change the user interface, Playwright tests often break because they depend on specific CSS selectors and XPaths that may no longer exist. Playwright can not identify elements based on context and text — just like a human.

Requires coding skills to control the browser

Playwright's problems aren't unique—they're part of a bigger problem that affects all traditional testing tools that rely heavily on writing code. In an age that values agility, DevOps, and rapid iteration, their shortcomings are amplified.

High Maintenance Costs

Maintaining test scripts is an endless debt cycle. UI changes, broken selectors, and adjusted async logic mean constant updates. Entire teams can spend a third—or even half—of their time stuck in this "maintenance hell."

Steep Learning Curve

Creating tests in Playwright requires programming knowledge, writing stable automated tests requires deep knowledge of Playwright APIs, CSS selectors, XPath, and front-end rendering. This keeps the barrier high for non-technical team members, limiting collaboration.

It is good for developers. However, with the popularity of AI and Vibe coding, more and more people can use AI to develop their own applications. They may be product managers, designers, and others without programming experience.

Out of Sync with Modern Development

Traditional testing can't keep up with CI/CD speeds. Complex test scripts may take hours to run, and failures require even more time to debug. This lag undermines the DevOps ideal of fast feedback.

Comparing with Others: Leading the AI Testing Revolution

Slash.cool

As traditional tools falter, a quiet revolution has begun—AI automation testing.

Slash core idea: let AI understand and interact with applications like a human, instead of mechanically following code. Slash is a leading example. It's not about writing code—it's about writing tests in plain English.

Key strengths include:

• Natural Language Testing: Simply describe steps in human language—e.g., "Open the login page, enter username 'admin', click the 'Login' button." AI translates this into executable actions, dramatically lowering the barrier to entry. Now, PMs, BAs, and QAs alike can write tests.

• Self-Healing Tests: Slash uses computer vision and AI models to identify UI elements. Even if developers change an element's ID or position, it can still find and interact with it, drastically cutting maintenance costs.

• Sandbox and Cloud browser: It runs in a secure sandbox environment. It uses a real cloud browser to actually navigate, inspect, and analyze target pages in real-time. This means Slash writes accurate scripts based on actual page structure and behavior, not guesswork.

Main difference between Slash and Playwright:

Playwright focused on use code to control browser for testing, then got things done, you need know how it works and write script code.

Slash focuses on AI-powered automation testing tools that integrate with its device and browser cloud. You don't need to know how Playwright works internally or how to use its tools. You just describe what you want in natural language, and AI generates the test scripts, runs them, and shows you the results.

The difference is clear: one requires technical knowledge and brittle selectors, the other is natural language that anyone can understand and maintain.

When to choose Slash?

• If you don't have programming experience but need Playwright scripts for testing, Slash lets you use natural language to generate Playwright test scripts
• If you're dealing with XPath selectors that break with UI changes, Slash is AI-powered and automatically browses page elements like a human, making adjustments as needed
• You don't want to write code yourself, you want AI to handle these tasks

Selenium

Selenium has been the cornerstone of web automation for over a decade, offering a comprehensive suite of tools for browser automation.

Playwright vs Selenium: Which to choose?

Selenium is not a test automation framework, it is a browser automation tool.

You need to add at least a test runner, Supports functional and cross-browser testing to verify seamless performance across multiple browsers.

Selenium's Core Functionality

Selenium WebDriver provides direct control over browser actions through a standardized API. It supports multiple browsers and allows developers to write test scripts in their preferred programming language.

Selenium's Advantages

Broader Language Support: Selenium boasts a wider range of officially supported programming languages (Java, C#, Python, JavaScript, Ruby, Kotlin) and a larger ecosystem of community-contributed libraries.

Extensive Browser Compatibility: It provides support for a broader range of browsers, including legacy browsers like Internet Explorer, which can be crucial for projects requiring backward compatibility.

Selenium's Limitations

Despite its strengths, Selenium faces similar challenges to Playwright in the AI era:

• Requires extensive coding knowledge
• Xpath selectors that break with UI changes
• High maintenance overhead
• Harder to set up yourself than alternatives
• Steep learning curve for non-technical team members

Testim

Testim is AI-powered testing for custom web, mobile, and Salesforce apps.

Pros:

• Very easy to use across a wide range of features
• Intuitive drag-and-drop interface; minimal technical knowledge required.
• Helpful onboarding and regular enterprise check-ins
• Enables recording of many tests without technical skills
• AI smart locators (a rare feature in other solutions)
• Primarily web apps with additional support for desktop and mobile testing.

Cons:

• Pricing can be a barrier than alternatives, especially for smaller teams or startups. Playwright is free and open-source.
• Limited Customization: may not support very complex or non-standard testing requirements.

When to Choose Testim?

If your team has limited coding skills or wants to empower non-technical members to contribute to testing, and need a tool with AI-powered self-healing.

Why Smart Teams Choose AI Testing

Adopting AI automation testing isn't just switching tools—it's a strategic decision.

Organizational Efficiency

AI testing removes skill barriers, making quality assurance a shared responsibility across the team. No more QA "solo acts"—everyone contributes, boosting collaboration.

Cost Effectiveness

Lower maintenance and learning curves mean fewer human hours spent fixing brittle tests, and more time spent innovating.

Competitive Advantage

Faster release cycles and higher product quality mean you can respond to market changes quicker. In today's fast-paced environment, that's the ultimate edge.

The Future Is Here: Your AI Testing Roadmap

Playwright still plays a stable role, but we can use another approach to AI-driven automation testing that's more efficient and cost-effective.

Automation used to be considered the best solution for testing—but now that AI and low-code tools are becoming popular, that story is changing quickly.

Slash'll look at how AI is transforming test automation, how the role of programming is changing, and how tools like Playwright can maximize time savings and improve team automation testing efficiency with AI integration.

If you're ready for the shift, here's a roadmap:

1.Assess Your Current State: Calculate maintenance costs, script stability, and execution efficiency. Identify bottlenecks.

2.Start Small: Use an AI automation platform like Slash.cool to test a non-core module. Experience the ease of natural language testing and self-healing in action.

3.Plan the Migration: Gradually move core business tests to AI platforms. Shift your QA engineers' roles from "script maintainers" to "test designers" and "AI prompt engineers."

The future is already here.

FAQ

What is Playwright used for?

Playwright is primarily used for automating browser tasks, which can range from simple page navigation and content scraping to more complex operations like automated form submissions, user interactions and more.

How does AI automation testing work?

AI automation testing uses artificial intelligence to understand and interact with web applications like a human would. Instead of relying on brittle CSS selectors or XPaths, AI-powered tools can visually identify elements, understand context, and adapt to UI changes automatically.

What are the benefits of AI-powered testing over traditional Playwright?

AI-powered testing offers several advantages: natural language test creation (no coding required), self-healing capabilities that adapt to UI changes, lower maintenance costs, and accessibility for non-technical team members like product managers and designers.

Can AI automation testing used with Playwright?

While AI automation testing is revolutionizing the field, build a complete Playwright test automation framework in Python using AI. You can integrate the Playwright Model Context Protocol (MCP) Server with Cursor or other AI Editer to generate a full framework (scalable test code) entirely through an AI prompt – no manual coding required.

What makes Slash.cool different from other testing tools?

Slash.cool combines AI-powered natural language testing with real cloud browser execution. It allows anyone to write tests in plain English, automatically handles UI changes through computer vision, and runs tests in secure sandbox environments with actual browser automation.