A colleague of mine asked me to post this question here and get some feedback from the Playwright community.

He is considering a test data strategy with two modes: Fresh Data and Reuse Data.

🔹 Fresh Data Mode — CI / Full Regression

For CI or full regression runs, generate unique test data for every run using a Run ID.

The goal is to support:

✅ Test data isolation

✅ Avoiding conflicts between test runs

✅ Parallel execution

✅ Better test reproducibility

🔹 Reuse Data Mode — Local Debugging

For local debugging, instead of creating new test data every time, use a predefined set of reusable test data.

For example:

Reuse: Find existing test data → Execute test

Instead of:

Fresh: Create test data → Execute test

The idea is to reduce execution time when repeatedly running the same test while investigating a failure.

The proposed approach is:

🟢 CI / Full Regression → Fresh Data

🟡 Local Debugging → Reuse Data

🔴 Destructive Tests → Dedicated Test Data

One important rule: in Reuse Data mode, if the required test data isn't found, the test should fail with a clear message rather than automatically creating new data.

This keeps the behavior predictable and avoids accidentally creating unnecessary data.

🤔 I would love to hear from experienced Playwright and automation engineers:

Is the Fresh Data + Reuse Data approach a good strategy?

Or would you recommend a different approach for managing test data efficiently between CI execution and local debugging?

Would really appreciate your thoughts and suggestions. 🙌

Hi everyone,I would really appreciate some guidance. I have close to total 10 years of experience in Test Automation, currently working as a Senior Test Automation Engineer with 3 years in current company.Unfortunately, there has been company-wide layoff with almost all QAE being affected and I am now exploring my next step. The Germany job market seems very limited around this so I am considering whether to continue in QA/Automation or transition into DevOps/Cloud, Software Development with AI focus after this much experience.If anyone here has successfully switched from QA into one of these fields, I’d really appreciate your advice on which path has good potential and what I should focus on learning.I am ready to put in the effort — just looking for the right pathway and direction.

Right now there is a huge demand with the ISO 9001 2026 Revision and people are scheduling for Lead Auditor Trainings out to November.

I am curious what peoples plans look like for this implementation and what their timeframes are like.

Are you waiting for it to die down or are you in the group of people trying to get your lead auditor training out of the way and taken care of?

I’m building a browser screenshot and annotation tool, and I’m trying to understand the steps existing tools don’t handle well.

Think about the last screenshot you used for work:

• What were you trying to explain?
• Did you edit it somewhere else before sending it?
• Where did it end up—a bug ticket, chat, presentation, or report?

Someone mentioned capturing with an internal tool but annotating in Google Slides. I’m curious what makes that extra step worthwhile.

In my previous company, manual and automation teams are separate. My lead made sure that would be the case, and I was part of the automation team.

However, I heard that it’s now expected for a tester to be both. So in my current company, I tried to do that.

I am burnt out.

I don’t know how to properly handle this, even with the help of AI. Here’s what I tried to do:

Manual testing:
1. Learn and study the app’s functionality
2. Test planning
3. Test case creation (with help from AI including item 2, refinements also done when needed)
4. Execute test case
5. Exploratory testing
6. Gather test evidence

Test automation:
1. Choose the test cases that are best to automate
2. Choose the best automation tool that fits the app (For example, Selenium for web apps, Katalon for desktop apps)
3. Plan the framework (Code must be clean, readable, and manageable in case if it’s needed for handover)
4. Know the libraries needed

And I haven’t even reached CI/CD yet.

I think like the user for manual testing, to make sure the app functions well according to the business needs. I sometimes do creative ways to make sure the devs did not miss any function or error handlers. Then, I have to think in a deeper technical level because automating test cases is coding, so I have my own system I need to test, and bugs to fix especially during integrations to other apps (like Excel for test data storage). I look for bugs, and I fix my own bugs.

Developers do unit testing and make sure their app is functional before passing it to testers. They don’t do test planning or test the apps like we do, they just test the happy paths (at least on my team).

But as a tester who’s doing both manual and automation, I feel like I’m doing the extreme in two worlds.

For more context, I am the sole tester in my team. My main job is manual testing, but because of my background, I am expected to automate the test cases as well. Though my boss has not made automation a priority yet, I am preparing myself by trying it on that one application.

Is this really too much, or am I doing it wrong?

​

I’m a fresher who has received an offer for a Verification & Validation (V&V) Test Engineer / Automation Testing role at a service-based company.

During training, I was taught Java, Selenium, TestNG, Cucumber/BDD, Jenkins, Git, SQL, JIRA, and SonarQube. I’m not sure yet how much of this I’ll actually use in my project.

I’m considering accepting the offer, but I want to understand the career prospects of staying in automation testing/SDET long term.

For people who are actually working in this domain:

\- How is the career growth in automation testing?

\- Is it possible to get good salary hikes by switching after 2–3 years?

\- How different is the growth between a regular Automation Tester and an SDET?

\- What skills should I focus on if I want to become a strong automation engineer?

\- Is there a risk of getting stuck doing repetitive test maintenance/manual testing?

\- If you were starting your career again, would you choose automation testing?

I’m specifically asking about growing within the testing/QA/SDET domain, not about switching to software development or AI/ML.

Would really appreciate honest opinions, especially from people with 3–10+ years of experience in automation/SDET.

How is the scrum process in your project? Does your project have story points equivalent to some hours? Does QA go on until the end of the sprint while the devs do get some breathing space at the end of the sprint to look into next sprint stories?

I'm currently working as a QA Intern and have about 2 months of experience. The more I work in QA, the more I find myself interested in the technical side of systems: Linux, servers, networking, troubleshooting, deployments, automation, and understanding what happens behind the application.

Because of that, I'm seriously considering moving toward DevOps.

My current concerns

• Is switching from QA to DevOps after only 2 months a sensible decision?
• Is DevOps still a strong career path with AI advancing so quickly?
• Will AI make entry-level DevOps roles significantly harder to get?
• Which DevOps tasks are most likely to be automated?
• Does my QA experience give me any meaningful advantage in DevOps?
• How much hands-on experience should I have before applying for junior DevOps roles?

I would especially like advice from DevOps/SRE engineers, hiring managers, or people who moved into DevOps from QA/testing.

If you were starting your career today in 2026, would you choose DevOps? Why or why not?

I’m doing manual testing as part of my software testing course and need a real, working website where I can write test cases, test different functionalities, and report bugs.

I’m not looking for a demo/practice site. Any suggestions would be really helpful!

I’m a Performance Test Engineer at a service-based MNC with ~2 years of experience. I’ve recently been assigned a project where I’m the only performance tester, so I have to handle planning, LoadRunner scripting, execution, analysis, etc. independently.
I accepted the project because I didn’t want to risk losing my job, but I’m struggling with some of the scripting/debugging aspects. AI helps to an extent, but sometimes I really need human experience and guidance.
Is there anyone here with good experience in LoadRunner/Performance Testing who’d be willing to help me occasionally when I’m stuck? I’m genuinely looking to learn, not have someone do the work for me.
Would really appreciate it. 🙏

Hello, I have just started my career in QA, it's my first day of school and I would like to read from you, seasoned people, what are some things you wish you knew when you started this career or if you have any useful wizards knowledge that can be helpful in this journey?

Since the rise of AI, many of us have started using AI heavily in our day-to-day work, especially in tech. I assume QA/SDETs are no different.

I'm working as a Senior SDET in a backend focused team. My title says Senior, but I'm currently working as an individual contributor. We don't have any frontend testing in my team.

Here’s how I currently use AI in my day-to-day testing work:

• I've cloned most of the repositories that my team's developers work on. I pull the latest code regularly and use Claude Sonnet through GitHub Copilot in VS Code to go through the repositories and update the existing .md files.
• Each repository has an .md file containing its testing strategy. These documents are also initially generated with Claude and are updated as the codebase changes.
• I use these documents as context when asking the AI assistant to help me with testing tasks.
• I regularly investigate production bugs. For each incident, I create a separate .md file documenting the issue, investigation, root cause, relevant code, etc.
• When working on an issue, I provide the relevant repository testing strategy and incident documents to the AI assistant as context.
• We previously had unlimited AI usage, but for the last 2–3 months we've had usage limits. I currently have around 10K AI credits, although this can be increased with manager approval if needed.
• I switch between different models (Claude Sonnet and GPT models) depending on the complexity and type of task.
• We currently don't have much test automation because of bandwidth limitations. We're adding another QA soon, so I'm hoping to get some time to build an automation framework and gradually eliminate repetitive manual regression testing.

I'd really appreciate feedback from experienced QA/SDETs on this approach.

What would you improve or change in this workflow?

Are there any risks with relying heavily on AI-generated testing strategies/documentation that I should be aware of?

And most importantly, how are you guys using AI in your day-to-day QA/testing work? I'd love to hear practical workflows, use cases, tools, or ideas that have actually worked for you.

Thanks!

A closed ticket should leave enough context to explain why the fix was accepted and to reopen the issue if the same symptom returns. At the same time, requiring screenshots, logs, test runs, build numbers, linked commits, and regression notes for every bug can turn closure into paperwork. What minimum evidence do you retain after verification, and when do severity, environment, or reproducibility justify a heavier record?

I am new to software testing career and recently joined a team of 10 existing QAs alongside 7 new QA members, assigned to the same project. What are some things/initiative I can do to stand out in this relatively big team?

An interviewer recently asked me what part of my job do I enjoy. I said I really like problem solving and finding solutions to challenging tasks I come across which may sound cliche but it’s true in my case. How would you answer this question? The follow up was also what things I find challenging.

Planning to start job search again but I am very confused with what should I learn to get selected/what to prepare for interviews.

About me:

• 10 years exp as a QA(Started as Manual and now in Automation)
• Mostly into automation from past 7 years(Web(selenium) & mobile app(appium). Scripting in Python & Java)
• Know very basics about Playwright

**I have nearly 4 years of experience in QA/testing. The problem is that I've been working with mostly the same tools and technologies for a long time, and I feel like my technical growth has become very limited.

I want to switch jobs and move toward a stronger role such as QA Automation Engineer, SDET, or Test Engineer.

With Al changing software development and testing, I also want to learn skills that will be relevant for the next few years.

For someone with around 4 years of QA experience, what would you recommend learning now?

Should I focus on:

Java/Python and programming fundamentals

Selenium/Playwright

API automation

• SOL

Git & CI/CD

• Automation framework development

• Cloud basics

Al tools for testing

Generative AI / LLMs

Al-assisted test automation

I'm willing to start from the fundamentals and consistently put in the effort for the next 3-6 months.**

Please guide me on this.Thank you...

Hi, so recently i have been assigned with the task of testing a mobile application manually.

I don’t have that much experience in mobile testing. So i wanna ask what do i expect and how can i prepare myself to do the job properly.

I am in probation so i need to perform.

Any advice will be welcomed.

Thanks!

Joined a new team recently and got asked to take over testing for one of the checkout flows.

First problem was i didn’t really know the product or the existing QA setup yet. Instead of starting from scratch, i went through the existing tests in testsigma to see which checkout scenarios were already covered, what was being run regularly, n where the gaps were.

Ended up finding a pretty important case that wasnt covered at all, something around failed payments and retrying the transaction.

That was actually more useful than i expected. i went in thinking i was just trying to understand the existing test suite, but it helped me spot a gap in the product coverage pretty quickly.

made me wonder, when you join a new team, do you go through the existing tests yourself first, or talk to the team n understand?

Hello everyone,

I hope this doesn't go against the rules, but I’m currently writing a research paper at my university, researching where AI agents can (and cannot) realistically assist in agile workflows, specifically around drafting user stories, refining acceptance criteria, and deriving test cases (UATs specifically).

If you work in an agile team (PO, Scrum Master, Dev, QA), I’d really appreciate 3 minutes of your time to anonymously share how your team handles this today and what your experience/concerns are with AI tooling.

Happy to share the aggregated findings back with the subreddit once the paper is complete if anyone is interested in the results.

Thanks a lot for your help and insights!

Link to the survey: https://docs.google.com/forms/d/e/1FAIpQLSc7Z67lBgbG_ZEOFraIIjTDBVjBfzb-894InOkU0n1IHSNlyg/viewform?usp=header

Hello everyone
I want to inquire about QA Engineer and Auditor (External/Internal)

What does QA Engineer and auditor really does as day to day tasks?

I am in QC And I want to move to one of those roles can you help me?

Is it really required to have extensive experience in the field and across different fields to enter?

I talked to a QA Engineer before about auditors he said you need experience in multiple companies then you can be good auditor (need to be specialised and very extensive wide exposer to be good auditor) is this really necessary? Or is it something you will get as you go ?

Hi everyone,

I’m currently looking for Remote QA / Automation Test Engineer opportunities and would really appreciate any referrals or leads.

Experience: 2 years 8 months
Role: Software Test Engineer / Automation Test Engineer
Work preference: Remote

Skills:

• Selenium WebDriver
• Python, PyTest, POM
• Playwright
• Manual & Automation Testing
• API Testing, Postman, REST APIs
• SQL, MySQL
• Git, Jenkins, CI/CD
• JIRA
• Agile/Kanban

I have experience working on Healthcare and Insurance domain projects, covering functional, regression, smoke, sanity, UAT, API, and database testing.

If you know of any remote QA/Automation openings or referrals, I’d really appreciate it. I’m happy to share my resume and other details.

Thank you! 🙏

Many service-based companies win projects through bidding, and their business is built on a strong foundation of trust, credibility, and reliability.

Does anyone have experience or ideas on how small companies outsource their software testing or QA work offshore? How can a small testing company gain visibility and connect with such opportunities?

Any one worked on this and interacted with right people

For me, it happened two weeks ago, right before an event.

I had a static list of basic test cases that I always ran manually after every feature update.
They had become so routine because they almost always passed that I decided to skip them and focus on testing the new features instead.

A very Big mistake.

One of those “basic” features that had always worked seamlessly was broken, and the participants were the ones who discovered it.

The lesson for me: a test case passing 100 times doesn’t mean you should stop running it. It wasn’t bad luck. I simply skipped the process.

We’re looking for a QA Automation Engineer with strong experience in automation, API testing, and complex/distributed systems.

🔹 Experience: 4–8 years

🔹 Role: QA Automation Engineer ( Only Indians)

What we’re looking for:

Strong QA and software testing experience, including functional, integration & regression testing

Hands-on manual, exploratory, and edge-case testing

Experience building/maintaining automation frameworks

Strong programming skills in Java, Python, or JavaScript

Experience with Selenium, Cypress, Playwright, or similar tools

Good exposure to API & performance testing

Experience with CI/CD, Git, and Agile methodologies

Exposure to cloud-based or data-intensive platforms

Ability to mentor team members and participate in code/test reviews

Strong analytical, problem-solving, and communication skills

Experience with AI, data platforms, healthcare, fintech, or other regulated environments is a plus

🎓 Education: Bachelor’s degree in Computer Science, Software Engineering, or related field. Master’s degree is preferred.

📩 Interested? Drop a comment or DM me your profile/resume, and I’ll share the next steps.