Over 5,900 companies use Playwright, including major companies like Microsoft, Adobe, and Shopify. And that number’s climbing fast. Chances are, you might be one of them, or you’re about to start using it. But knowing how to install Playwright isn’t the same as knowing how to use it well.
This guide is for teams who want to use this tool effectively. We’ll show you how high-performing teams structure Playwright projects to be fast, stable, and maintainable. You’ll learn:
Let’s get started.
Playwright is a modern tool for testing web applications. It simulates real user actions like clicking buttons, filling forms, and navigating pages, but with greater speed and precision. That makes it easier to catch bugs before they ever reach production.
Here’s how the tool has evolved throughout the years:
A lot of people think that it is just a test automation tool. However, it has all the features that help teams move faster, test more reliably, and cover more ground with less effort.
Source: npmtrends
Developed by Microsoft, Playwright brings unmatched flexibility, power, and resilience to the world of test automation. These key features set it apart from legacy tools and even its modern ones.
Mobile Web Testing: Playwright provides native mobile browser emulation for:
Note: Use it to test responsive layouts, geolocation, and touch interactions in real-world mobile scenarios.
All these features make Playwright one of the strongest choices for today’s QA workflows.
Despite having all the great features, this tool hit some serious bottlenecks. And that mostly happens with inexperienced teams. So if you’re just starting and have heard a few good things about Playwright, just make sure you’re not facing the following issues.
All this leads to distrust in the tool. However, the problem is something else. Most teams use it for a quick fix rather than a primary tool. In the next section, we’ll tell you how smart teams you use it for better efficiency so you can avoid all those mistakes.
At ThinkSys, we’ve built and maintained large-scale Playwright test suites for clients across fintech, edtech, healthcare, and ecommerce. We’ve seen firsthand what breaks and what scales. We are about to share the practices that we use on real client projects to build fast, stable, and maintainable Playwright automation.
Want to see these principles in action? Here’s how we helped Fresh Tracks Canada improve test stability and speed with Playwright in this case study
Here’s what separates teams that struggle from teams that grow.
Strong automation begins with structure. That means planning before writing tests, which includes defining folder layouts, naming conventions, and reusable components. We organize tests using the Page Object Model, giving each screen its own logical unit. It keeps test files lean and readable, and it makes changes easier to manage as the product evolves.
We’ve seen this one decision save hundreds of hours across complex applications.
Tests should be independent, and fixtures make that possible. We define setup and teardown logic using Playwright’s test fixtures. That means no more polluting global state or duplicating setup code. If we want to log in before every test or reset data after each run, fixtures handle that automatically. This keeps tests isolated and predictable, which is especially important when running them in parallel or across different environments.
Weak selectors are the fastest way to break a test suite. We avoid CSS classes like .button-blue or DOM positions like div:nth-child(2) as they’re too easy to break during UI changes. Instead, we rely on accessibility-first queries like getByRole(), getByLabelText(), or getByTestId().
These are stable, expressive, and easier to debug when things go wrong. They also align with WCAG accessibility standards, which is an added bonus.
Speed and accuracy both matter. Playwright makes it easy to run tests in parallel, and we take full advantage of that. To avoid state leakage between tests, we use isolated browser contexts so each test starts fresh. That means no shared sessions, no leftover data, and fewer weird edge-case failures.
Parallelism plus isolation gives us fast pipelines without sacrificing reliability.
Debugging shouldn’t require guesswork. We use tools like Trace Viewer and video recording to step through failures and catch issues fast. For CI, we plug Playwright into GitHub Actions or Jenkins, using Docker to ensure environments are consistent across machines.
Tests run on every commit, and failures are easy to trace and fix. This keeps quality high without slowing down the dev cycle.
Playwright on its own is already a powerful automation tool. But what’s really exciting is how Playwright is now working with AI, especially through something new called the Model Context Protocol (MCP).
The Model Context Protocol, or MCP, is a new feature introduced by Microsoft to make Playwright more AI-friendly. It allows large language models (LLMs) like GitHub Copilot or GPT-based tools to connect directly to a browser session running in Playwright.
Instead of relying on fragile CSS selectors (like .btn-primary or div:nth-child(2)), MCP gives AI access to the accessible tree of the page. This means the AI can “see” the page more like a human would. It knows which elements are buttons, inputs, toggles, etc., even if their position or class names change.
MCP also allows the AI to do more than just click around. It can send API requests, interact with databases, and simulate workflows. And since it works through the same Playwright framework, you don’t need separate tools for UI vs. API testing.
Tools like GitHub Copilot and GPT-Engineer can now generate Playwright test code from plain English prompts. For example, you could say:
“Write a test that logs in, searches for a product, and verifies it appears on the results page.”
Copilot or GPT-Engineer will write the test code. Then, thanks to MCP, that code can run directly in Playwright, using real browser sessions and real interactions. For this, no setup hacks or manual tweaks are needed.
Even more interesting is that if the test fails, some of these tools can fix and re-run the test automatically. AI builds and adjusts code purely based on goals, without a human writing every line manually.
What AI Can and Can’t Do (Yet)
AI can generate tests fast, especially for common scenarios. It’s helpful for teams that are short on time or staff. But it still needs human supervision.
Must Read: The Role of AI In Software Testing
AI doesn’t know your product the way you do. So it might miss edge cases or misunderstand complex business rules. That’s why human-in-the-loop review is still critical. You should always:
Playwright gives you speed, flexibility, and power, but it needs direction. Without structure and discipline, even the best tools fall short. By following proven practices like POM, fixtures, CI integration, parallelism, and resilient selectors, your QA team can move from flaky automation to fast, dependable coverage. With AI integration on the horizon via MCP, you’re not just automating tests — you’re future-proofing your QA.
If you're ready to build stable, reliable Playwright automation, but you're stuck, we can help.
Want help scaling Playwright in your organization? Let’s talk
Now that we’ve explored why Playwright is gaining momentum, let’s see how it stacks up against other major players like Selenium and Cypress.
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