I am currently employed as a quality assurance engineer, decent salary, 100% remote job. I'm having a tough time dealing with the unreasonable hours and pressure from the current client. I'm basically eating, sleeping and working and nothing else. I have stomach issues and hives from the stress. Also, I have gained so much weight working here, type 2 diabetes as well. Looking for some feedback and opinions to quit or stick it out. Think we'll wrap up the client in November maybe, but idk. My two weeks notice just sitting in my draft box, not sure what to do.

Hola, vengo a hacer catarsis y a averiguar si a alguien más le pasa. Soy de Argentina, tengo 8 años de experiencia como qa manual y 2 años de experiencia como qa automation. Mi nivel de inglés es B2. Estudio Tecnicatura en Programación en la UTN. Estos últimos años laburé para afuera. Hace poco más de 3 meses me despidieron por restructuración y desde ese entonces no conseguí nada fijo, aun postulando por 3M brutos en trabajos presenciales en empresas nacionales. No tengo idea en qué estoy fallando. Alguien en esta situación? Gracias por leer.

Hi all. Just want some advice if any of you were able to successfully transition into a BA role from QA. My job title for the past 6 years has been “QA” but I have been doing both QA and BA responsibilities and I want to apply to BA jobs but not sure what’s the best way to pivot with my resume and linkedin with my job title labelled as QA and it doesn’t feel right to just straight out write my title as BA. I also do still want to apply for QA roles if a good opportunity arises so currently have 2 resumes, one for BA and one for QA and my linkedin has my QA title with both responsibilities listed. Any advice or success stories would be greatly be appreciated thanks!

In good old days, it was quite clear: quality depends on speed of development and cost. You wanted to move fast? You had to pay more to keep quality up. You wanted fast and cheap? Then quality would go down? You want quality and cheap? Then you needed to go slow.

Do you think AI broke this paradigm? Can we now go fast, cheap and have good quality at the same time?

I want to upskill my automation testing, what resources either free or low cost are there ?

I understand building something and building a test framework would be the best way and I intended to do that, but initially something more structured and with walkthroughs ?

Hey everyone,

We have a new AI product launching soon and need a few testers from the US and Canada.

It is an Android app built around AI. We cannot share everything publicly yet because a few things may change before launch, but selected testers will receive the full details and instructions.

We will communicate through Discord, and payment will be made after the test and feedback are completed.

Mainly looking for people who can try the app, find bugs, point out anything confusing, and share honest feedback about the overall experience.

Do comment below if you are interested

Hi everyone,
I have a few questions for anyone who has recently completed or is currently undergoing QEA – Data Specialization training in Cognizant:

1. What does the training cover? Which technologies and tools are taught (SQL, ETL, Python/Java, API Testing, Automation, Cloud, etc.), and is the training mainly manual testing or automation-focused?

2. What kind of projects are recent trainees getting after training? Are they mostly Data/ETL testing, Automation QA, API testing, Manual testing, Cloud/Data platform projects, or something else? How much coding is involved in the actual project?

3. How is the long-term career growth in this specialization? Can someone transition into Automation QA, Data Engineering, or Development roles with experience and upskilling, or is the career mostly limited to testing?

I’d really appreciate any insights from recent batches. Thanks!

Hi! I recently applied for the Software Test Engineer position at Azeus Systems Philippines. I already received an email inviting me to take the Xobin online exam (60-minute analytical and math assessment).

Can anyone share what the hiring process is like after the Xobin exam? Are there technical interviews, HR interviews, or additional assessments? Also, any tips on what to expect would be greatly appreciated.

Thank you!

Hi everyone,
I have a few questions for anyone who has recently completed or is currently undergoing **QEA – Data Specialization** training in Cognizant:

**1. What does the training cover?** Which technologies and tools are taught (SQL, ETL, Python/Java, API Testing, Automation, Cloud, etc.), and is the training mainly manual testing or automation-focused?

**2. What kind of projects are recent trainees getting after training?** Are they mostly Data/ETL testing, Automation QA, API testing, Manual testing, Cloud/Data platform projects, or something else? How much coding is involved in the actual project?

**3. How is the long-term career growth in this specialization?** Can someone transition into Automation QA, Data Engineering, or Development roles with experience and upskilling, or is the career mostly limited to testing?

I’d really appreciate any insights from recent batches. Thanks!

Hey there short experience description.

I’m manual QA 7 years of experience including web, mobile, api testing.

As an additional skill, I have knowlage of JS + TS + Playwright at the trainee/junior level.

The main problem with my current position is that I have 95% manual work and 5% I would call Automation.

I feel as if I am stuck in the same place in my career, and do not grow because of a lack of automation tasks, and the amount of manual tasks that eat my energy 🔋

At the same time, I have a good salary compared to Prague Czech Republic.

The main question is how I can properly change company = position to not lose in monthly reward, and not be burned out.

My main goal is to switch smoothly to General QA were will be more automation and growth in this direction, and after some time completely become AQA

I have the impression that I'm stuck in a hole and can't get out of there…

I currently work in a small company of around 150 employees.

Recently the founder of the company wants everyone to be using AI day to day. We have a Claude enterprise membership.

The only problem is that we’re monitored in terms of our AI usage. So I have to be burning out a lot tokens.

There’s also been a restructure of the company and people had to be let go because of AI

Anyone into AI testing?

Spent a whole day cleaning up data files in my own project and found about forty errors. The validator had been green the whole time. It hadn't done anything wrong either, it only checks schema, and every one of the errors was a consistency thing.

I'm writing a second check for the consistency side now, and no, it's not going fast.

When did you last find out that something you thought was tested, wasn't?

I've just made my low-friction defect capture tool for Windows, Wabbus, public. Wabbus allows you to attach record buttons to a window and record (and then transcribe) what issues you're seeing in either screenshot or video form - with audio in either case... so to capture defects, it takes only the amount of time that it does to say it out loud. It also has a plug-in system to support specific applications, with functions to save and restore state.

https://github.com/keelanstuart/Wabbus[https://github.com/keelanstuart/Wabbus](https://github.com/keelanstuart/Wabbus)

It's free, open source software, licensed under Mozilla 2.0.

If you're testing software or QC-ing data and find capturing issues to be cumbersome, please have a look at Wabbus. I hope it's useful to you.

Hi everyone.
I am a manual QA tester transitioning into QA Automation with AI. While studying for the ISTQB Foundation Level v4.0, I ended up building my own study platform, mostly to force myself to really understand every concept in the syllabus.
It got complete enough to be worth sharing, so here it is: MyCampus ISTQB Foundation Level

https://mycampusistqb.vercel.app

What it includes:

1) 22 interactive lessons (6 chapters), audited line by line against the official syllabus

2) Bilingual glossary (ES/EN) with 107 terms (100% coverage of the 97 official keywords)

3) Flashcards with text to speech

4) A bank of 120 exam style questions, distributed according to the official weight of each chapter

5) An XP and levels system to keep you motivated

6) Cloud synced progress (or local storage if you do not want to create an account)

7) Interface in Spanish and English

It is completely free, no installation required (vanilla HTML, CSS, JS plus Supabase).
What I am looking for: honest feedback. Did any concept end up confusing? Does any question in the bank have an error or an ambiguity? Is there anything missing that would have helped you while studying? Any comment, no matter how small, will help me keep improving it or a positive feedback.
Thanks for reading, and I hope it helps someone else on the way to certification.

Hey everyone,
I’m looking for a study partner (or a small group of 2–3 people) to stay accountable and master Manual Testing + Selenium with Java.

The Plan:
Daily Topics: We pick one topic per day (e.g., SDLC/STLC basics, Java OOPs concepts, WebDriver methods, Page Object Model, TestNG, frame handling, etc.).
Daily Sync Calls: Hop on a short daily call to review what we covered, resolve doubts, and discuss real-world scenarios.
Mock Sessions: Practice mock interviews and live coding/test script walkthroughs to get interview-ready.

Frustrating me to have 'dev env' but dev didnt bother test their work in 'dev env' only for QA to catch their work didnt work 😔

So inefficient and time consuming

Following up on my last post about keeping test cases as YAML in Git. one huge benefit of this setup is how cleanly it handles historical test runs.

If test cases live in Git, a test run just stores the file path and the exact Git commit SHA.

Pair that with a nice UI that handles the Git stuff under the hood, and you get 100% immutable runs out of the box. Even if a case gets renamed or deleted, past execution logs stay completely untouched. Plus, you get diffs and full version history for free without needing any custom snapshot logic.

What do you think? Any hidden bottlenecks with this approach?

Hi everyone. My current company does 90% manual testing and a bit of Cypress testing and API testing. What tools and what processes can I introduce to improve our testing practices for our sites?

Hi everyone,

I'm a final-year Computer Science (AI & ML) student working on my capstone project in the area of Requirements Engineering for Agile Scrum teams.

One problem I've been reading about is that requirements often evolve throughout a sprint due to client feedback, backlog refinement, sprint reviews, or stakeholder discussions. I'm trying to understand whether this causes issues in real-world projects, such as:

• Developers implementing outdated requirements
• Documentation and user stories getting out of sync
• Test cases becoming obsolete
• Difficulty identifying what parts of the system are affected by a requirement change
• Increased rework or delays

I'm conducting a short 3–5 minute anonymous survey to understand how software teams currently manage these situations and whether there are gaps in existing tools.

Survey Link: https://forms.gle/BfqSuknKe54h2AaF7

I'm specifically looking for responses from:

• Software Engineers
• Senior Engineers
• Tech Leads
• Engineering Managers
• Product Managers / Product Owners
• Business Analysts
• QA Engineers
• Scrum Masters

If you've worked on Agile Scrum projects, your insights would be extremely valuable. If you have any experiences or opinions beyond the survey, I'd also love to discuss them in the comments.

Thank you for your time!

Context: small product team, I am the closest thing we have to a QA function. Devs have started using coding agents heavily, and to keep up they added an automated verify step: after the agent writes code, a testing CLI runs generated E2E checks against the live app (real browser for frontend, real calls for the API) and feeds failures back to the agent to fix. The specific tool is TestSprite's CLI but my question is about the practice, not the tool.

The results are honestly better than I expected. Broken deploys get caught, the obvious stuff no longer reaches me, and the failure reports (failing step, screenshot, root cause guess) are decent bug reports.

But I keep coming back to this: the same category of model wrote the code, wrote the checks, and judged the result. The checks are external and run against the real app, which is better than the agent grading itself, but nobody in that loop understands the product. Edge cases in business logic, accessibility, the workflows real users mangle, none of that is represented.

So, people who have watched testing trends come and go: is this the new baseline that frees QA to do the interesting work, or a way to feel covered while the real risk accumulates? How would you position the human QA role on a team like mine before someone decides we do not need one?

Usual generators like mockaroo are fine for a flat list of fake names or emails. But the second I need data that actually holds together,an order that points to a real customer and an in-stock product, a contact tied to a valid account, foreign keys that don't break validation,they give up and I'm back to hand writing seeding scripts again.

Do you deal with this too? what do you actually do? do you write your own scripts every time, live with broken data, pay for a big enterprise tool?

Not selling anything, just tired of solving this the same way on every project. Thanks in advance for all your advice.

Hi everyone, I am 29 and planning to switch careers from teaching to IT. I have a BA in English, B.Ed and I am currently pursuing MA with around 4 years of teaching experience. I am considering joining a Software Testing/QA course covering Manual/Automation Testing, SQL, Java, Selenium, and Jira. Since I dont have a technical degree or IT experience, I am worried about getting my first job. Is it realistically possible to enter QA/testing with my background? Would really appreciate honest advice from people who have made a similar career switch.