Switch between customer and development
I see my role as the bridge between developers and customers. Developers know what they want to make, customers know what their users need. And somewhere in between is the translation. AI helps me to close that gap.
Take the Gherkin language that testers know: “Given, When, Then”. Years ago, I learned it, but we never really applied it. Too complicated to get through an entire organization. So far. AI helps me set requirements and acceptance criteria in exactly that structure. Suddenly, we look at the screen together and think: this is clear. All we have to do is get the customer along.
Designs and prototypes in minutes
With tools like V0 within five minutes, I'll create a wizard of flow that I can show. Not because I'm suddenly a designer, but because AI supports thinking. Customers understand at a glance what we want to build. As a result, testing is no longer just checking whether something works, but also showing which direction is valuable. As testers, we can now discuss the best solution with our UX colleagues, instead of asking them to build designs from scratch.
All the pieces of the puzzle finally together
The biggest problem in testing? Information everywhere and nowhere. User stories here, notes there, verbal appointments along the way. As a tester, you want to bring all that together. AI not only helps to collect, but also to keep it up to date. So that you not only provide software, but also a manual, useful documents or a one-pager.
Testing with a digital sparring partner
The best part is that AI is now my test buddy is. Before I run a test, I ask: “How would you test this?” He often comes up with the same ideas that I already had, but just a second earlier. That small difference makes me look more closely.
With Playwright MCP it goes even further: I say in plain language “test this”, and AI writes the technical test and runs it in the browser. Where I needed hours myself, AI does this in minutes. Ten times faster, sometimes a hundred times.
AI-first: strategic building block
For me, AI-First is not a separate tool that I sometimes use as a side tool. It is a conscious choice to look at each project: where can AI add value? Sometimes it's my test buddy who thinks along more quickly, sometimes a design tool that delivers a prototype in minutes, sometimes a script generator that makes tests for me.
The difference lies in the approach: I don't use AI afterwards to fix something, but see it as a fixed building block in my work. This way, AI does not remain an end in itself, but an accelerator that allows us to structurally build software faster, smarter and better.
Why testers remain indispensable
Will AI be able to test everything soon? In theory, yes. But in practice, testing is not about controlling everything, but about making the right choices. Risk-based testing we call that: focusing on what matters. For that, you need creativity and pragmatism. And that is exactly what human work remains.
As I learned at Blis: go for quality, but also pragmatics. You want the button to work when you press it. But sometimes moving on is more important than fixing every misspelling. That balance, those choices — that's where the real value of a tester lies. AI can accelerate us, but we make sure that the energy ends up in the right place.
Want to know more?
Want to know more about how we test software? At Blis Digital, we combine human acuity with AI power to deliver software that is reliable, scalable, and future-proof. Read here how we do that.
.jpg)
