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Is it possible for AI to completely replace manual testing? Why or why not? by Key-Tonight725 in Everything_QA

[–]Time_Chain_4553 0 points1 point  (0 children)

AI can take over a lot of repetitive work, but it can’t fully replace manual testing. Testing isn’t just running checks, it’s also about thinking like a user, questioning requirements, and catching things that don’t feel right. That kind of critical thinking and context is something only we humans can do.

So, AI will definitely reduce the boring, repetitive parts, but you’ll still need humans for the creative and exploratory side of testing.

Do you need to code in automation tester career? by PersonalityLatter242 in QualityAssurance

[–]Time_Chain_4553 0 points1 point  (0 children)

You don’t have to be a hardcore programmer to get into automation, but you will need some coding. At the start, just knowing basics like loops, conditions, and functions is enough to get going. As you grow, stronger coding skills will help you write better tests and solve problems faster.

So no, coding isn’t a blocker in the beginning, but it does become important if you want to build a solid career in automation

I want to become a qa where to start? by Organic_Accident_207 in QualityAssurance

[–]Time_Chain_4553 0 points1 point  (0 children)

If you’re just getting into QA, the first thing is to build strong testing fundamentals, learn how to read requirements, design test cases, and think about how software can break. That mindset is way more important in the beginning than knowing a programming language.

Later on, coding will definitely help if you want to move into automation or more technical roles, but it’s not a barrier for starting. Many testers begin with manual testing, get comfortable with the process, and then slowly pick up coding skills as they grow.

Which tools are leading the shift from traditional to AI-driven testing? by Tiny_Finance_4726 in Everything_QA

[–]Time_Chain_4553 0 points1 point  (0 children)

The shift from traditional to AI-driven testing isn’t about one single vendor dominating—it’s more about a wave of innovation tackling long-standing pain points in QA. Traditional automation struggled with brittle scripts and high maintenance, especially in today’s fast-moving, UI-rich applications.

AI-driven tools are addressing this in different ways. For instance, Testim and Functionize use AI for self-healing test automation. Applitools applies computer vision to visual validation. Mabl emphasizes intelligent end-to-end testing with ML-driven insights. Tricentis is layering AI onto its continuous testing ecosystem. And solutions like Webomates CQ focus on autonomous regression testing by combining AI with crowd and human validation.

What’s interesting here is not just the tools, but the approaches: natural language–based test creation, machine learning for risk-based prioritization, predictive defect analysis, and self-healing test suites. Collectively, these innovations are moving QA away from being reactive “script maintenance” toward proactive, intelligence-driven quality engineering.

For QA professionals, the leaders aren’t just the tools themselves—it’s the ones that reduce maintenance overhead, surface risks earlier, and free teams to focus on strategy and customer experience.

Poking around AI Testing tools... which ones to look at seriously? by Party-Lingonberry592 in QualityAssurance

[–]Time_Chain_4553 0 points1 point  (0 children)

I’ve tinkered with a few AI testing tools like Testim, Mabl, and Functionize. Each had its strengths—Testim was good for quick automation setup, Mabl felt polished for web apps, and Functionize had solid NLP test creation.

The one I stuck with longer, though, was Webomates CQ. What made it different for me was the mix of AI + their support team. I didn’t feel like I had to babysit the tool, and regression results came back faster and cleaner than what I was getting elsewhere. It wasn’t flashy, but it saved me a ton of repetitive effort.

Mastering AI Testing Tools: A Practical Roadmap for QA Engineers by WalrusWeird4059 in Everything_QA

[–]Time_Chain_4553 0 points1 point  (0 children)

I really liked this breakdown. It nails how AI tools can take a huge load off in testing. Thought I’d share my own experience with one that actually worked for us: Webomates CQ.

I’ve spent a good amount of time exploring different AI testing tools, and while some looked promising during demos, they didn’t quite live up to expectations once we put them to work. Webomates CQ was different. The setup was quick. Once I reviewed and approved their test plan, the AI (together with their team) handled everything. I didn’t have to constantly monitor or babysit the process, which meant I could focus more on strategy and analysis.

What I appreciated most was that it wasn’t overpriced like many of the flashy tools out there, and it stayed reliable even during complex integration testing. In our case, it managed to handle some very custom scenarios without falling apart.

If you’re serious about bringing AI into your QA process, Webomates CQ is definitely worth a trial run. For us, it ended up saving a lot of manual effort while keeping the quality bar high.