In 2025 we saw a lot of debate around testing, QA’ing, quality engineering, automating and now QA AI engineering. For me at least it’s really hard to tell what people are actually doing and what their main goal is.
I do not want to get into that debate about differences but felt it may be useful if people shared a quick view of their role and what a real week looks like, not a hypothetical one, a real one.
Despite some back and forth between viewing myself as QE because I do pretty much all of the activities listed under all those titles I’d probably still regard myself primarily as a software tester because I do more of the activities that I feel best suited to testing.
My role leans heavily towards testing as a learning, discovery, exploration and investigative activity around product risks and opportunities. Whilst it is a holistic view, I’ll test requirements and business value goals alongside end user data analytics, for the most part I test the product itself using test sessions. Usually focused on risks, say accessibility or maybe a risk at the api layer or more general feature level risks.
There is no average week but here’s a rough view.
60% on my primary activity of session based testing - I’m lead solo tester on 8 products.
20% on automation, tools and CI activities.
10% on more general quality activities, planning, process, continuous improvement
10% study and learning
*0% on test case creation or manual script execution
For example I suspect those in a QE category have a very different breakdown and that’s what I’m interested in and whilst I want to increase my primary activity they may have a different primary they want to shift more to.
When I’m looking at leveraging AI in my mind I want to increase that 60%, that seems a very different goal to a lot of the articles and tool reviews I am seeing.
This is not about judging as others will clearly find different models valuable in their context but it may be useful to share to help understand why some of the discussions can have very different stances.