I am QA tester with over 5 years of experience in the IT industry. During this time, I have worked on a wide range of projects – from small, agile teams to large-scale systems for clients across different sectors. This has given me a broad perspective on software development processes and various approaches to quality assurance. Recently, I have been focusing more on test automation, which not only helps increase efficiency but also deepens my understanding of the technical aspects of the systems I work with. The more I explore automation, the more I am convinced that it’s not just about writing code. The real challenge is keeping the project consistent, readable, and scalable. That’s why I often rely on the Page Object Pattern (POP), which organizes the repository into pages, components, and tests.

Up until recently, traditional AI editors like Gemini in VS Code helped me only within a single file. That meant manually copying code fragments, writing imports, adjusting names, and making sure everything stayed stylistically consistent. Honestly, it was time-consuming and prone to errors.

Cursor.ai takes a completely different approach. It works in the context of the entire repository, understands dependencies between files, and allows me to develop projects faster, more consistently, and without tedious repetitive work. Cursor.ai is helping developers by providing AI features that assist both developers and non-developers in writing code, launching prototypes, and automating testing processes. Its AI features make it easier to write code and automate tasks, accelerating development workflows and supporting users throughout the software development process.

Why Cursor.ai Makes a Difference

1. Full Repository Context

The biggest advantage of Cursor.ai for me is that it knows the whole project, not just a single file. It understands the directory structure, classes, methods, and coding conventions – in my case, typical for POP.

For example, I wanted to extend LoginPage with 2FA support. In a standard AI editor, I would have to manually point to the files, write imports, and make sure the new method looked consistent with the rest. In Cursor, all I had to do was start writing the method – it filled in the rest for me, matching the style to existing locators.

Example in Playwright/TypeScript:

When I start writing a method, the code editor in Cursor.ai leverages natural language prompts and plain language, allowing users to describe desired functionalities and receive accurate suggestions tailored to the repository context. It predicts the entire method according to the repository context and also detects that the otp field should be included at this point. Correcting it to match the full repository context takes just three clicks – by clicking on the class and constructor, Cursor automatically adds the locator line following the POP convention and adjusts the code in the method accordingly. The whole process is fast, smooth, and very efficient.

Scenario: testing user login with 2FA.

Cursor.ai        

Cursor.ai immediately recognized that I had LoginPage and DashboardPage. It suggested the loginWith2FA method, took care of the imports, and the whole test perfectly fit my POP structure. Cursor.ai is supported by a variety of AI models, including third party models, which enhances its flexibility and adaptability to different project needs.

Gemini    

Gemini, on the other hand, generated a working test, but… without any reference to the repository’s structure. Everything was raw selectors, no classes or methods. That would mean manual rework and refactoring.

Many developers, especially those who are used to robust code editors that support multiple programming languages and integrate with other tools, may find Gemini less complete or powerful in comparison.

The difference in both time and quality was massive.

2. Magic Tab + Fast Edits in Practice

The biggest revolution I felt was during multi-file refactoring. For example, when I needed to add a logout() method across several places, I used to do it manually.

Cursor did it for me: Magic Tab suggested where the new method should go, and Fast Edits applied the changes across multiple files with a single click. These features automate repetitive changes, significantly boosting developer productivity and reducing the risk of inadvertently affecting other features during refactoring. Time savings? Huge.

Magic Tab and Fast Edits in Practice – Multi-file POP Refactoring

In POP projects, you often need to modify multiple files simultaneously, e.g., when adding a shared feature across pages.

In traditional AI editors, this is manual work in each file. Cursor, with Magic Tab and Fast Edits, handles it automatically:

• Magic Tab suggests where the new method should be used.
• Fast Edits applies changes across multiple files with one click.

Integration with existing extensions further streamlines the refactoring process and enhances compatibility with diverse development environments, making it easier for developers to work efficiently across various programming languages and frameworks.

Example: Adding a logout() method

Cursor automatically suggests:

• In dashboard.page.ts → await this.logout();
• In login.spec.ts → refactor setup/teardown to use logout()
• In components → consistent invocations

When clicking on the line, Cursor.ai highlights it, and after pressing Tab, it applies the suggested change.

Additionally, if we want to apply the change across multiple files, we can write a command for that. Cursor.ai will then scan the entire repository, make the necessary changes where needed, and simply ask us for confirmation. Cursor.ai can also assist in generating commit messages for these code changes, streamlining version control workflows by providing quick, descriptive summaries of modifications.

3. Running and Diagnosing Tests in Cursor.ai

Beyond generating code, Cursor also supports running tests and diagnosing issues.

Traditionally, QA would have to:

• switch to the terminal,
• manually run npx playwright test,
• read error logs,
• return to the editor, find the cause, and fix the code.

With Cursor.ai, the process is integrated and streamlines software testing by providing AI assistance for rapid issue resolution.

• Run tests directly in the editor – you can execute the entire suite or just a single scenario. Note that large codebases can sometimes lead to performance issues during test runs, but Cursor.ai helps mitigate these slowdowns.
• Analyze test results – errors are displayed in context (e.g., which locator was not found). Cursor.ai also helps identify false positives in automated test results, reducing debugging time and improving accuracy.
• Suggested fixes – Cursor not only shows the stack trace but proposes possible solutions, e.g., “Element #otp not found, did you mean this.otpField?”

Privacy mode controls data sharing with remote servers and external services, protecting proprietary projects and sensitive data. However, enabling privacy mode involves trade-offs, such as limiting access to some powerful features that rely on external AI models. When using advanced AI features or third-party integrations, consider the cost implications, as external services may introduce additional operational expenses.

Example

Test Failed: login.spec.ts → user can log in with 2FA

LocatorNotFoundError: Unable to find element #otp

Cursor automatically diagnoses:

Suggestion:

Should you use this.otpField instead of #otp?

Update loginWith2FA in login.page.ts?

You can accept the change and re-run the test with a single click.

In practice, this closes the QA loop in one place:

1. Write the test (Cursor generates code according to the repo).
2. Run it instantly in the editor.
3. If something fails – Cursor immediately diagnoses and suggests fixes.

This feedback not only helps teams implement process improvements but also builds knowledge for future testing scenarios, making AI-assisted workflows more efficient and accurate.

Testing Best Practices

Testing is at the heart of successful software development, acting as the safeguard that ensures every release meets the company’s quality standards and user expectations. In today’s fast-paced development cycles, relying solely on manual testing can quickly become overwhelming and inefficient. That’s where automated testing and test automation come into play, allowing teams to streamline repetitive tasks, catch issues early, and focus their manual effort where it matters most.

A comprehensive approach to testing combines both manual and automated methods. Manual testing is invaluable for exploratory scenarios and user interface checks, but automated testing shines when it comes to running large suites of regression tests or verifying core features after every code change. By implementing test automation, teams can run tests more frequently, reduce the risk of human error, and ensure that new code doesn’t break existing functionality.

Regression testing is a key practice in maintaining software quality over time. Every time new features are added or changes are made, regression tests help confirm that previously tested parts of the system still work as expected. Automating these tests not only saves time but also increases confidence in the stability of the product.

Quality control is another essential aspect of the testing process. By setting clear quality requirements and using automated tools to enforce them, teams can catch defects early and prevent costly issues from reaching production. This proactive approach to quality assurance helps companies deliver reliable, high-performing software while keeping development costs and manual effort under control.

In summary, adopting best practices in testing—especially by integrating automated testing and regression testing into your workflow—boosts efficiency, supports quality control, and helps teams consistently deliver software that meets the highest standards.

My Summary

After a few weeks of working with it, I can confidently say that Cursor.ai has changed the way I approach test automation.

• Thanks to full repository context, I don’t waste time on small details.
• Magic Tab lets me write consistent code in just seconds.
• Fast Edits makes refactoring easier, which used to be tedious and error-prone.

In practice, I’m saving hours of work, the project looks more professional, and it’s easier to maintain. Adopting Cursor.ai aligns with modern software development practices, helping the company streamline not only test automation but also other processes that impact overall efficiency. For me, Cursor.ai is a real step forward in test automation – and honestly, it’s hard to imagine going back to the old way of working.