I build test structure, test automation and AI-driven test generation into your development. In your environment, with your team. Not as a service you rebook every quarter.
Most teams that call me don’t have a bad product. They just never decided how to test it. In practice, it looks like this:
Whatever stands out gets tested. Whatever doesn’t, doesn’t.
First the feature, then the deadline, then testing, if there’s time left.
Hours of manual clicking, and the bug still slips through.
Your team knows how to build. Nobody ever taught them how to test.
The result is always the same: at some point, your customer finds the bug before you do. A bug that only surfaces in production costs many times what you would have invested in an early test. And it costs trust.
That equals 0.45 developers who spend the whole year finding and fixing bugs instead of building your product.
Default 9%: developers spend 3.8 of 41.1 weekly hours on faulty code. Source: Stripe, The Developer Coefficient (2018). Full costs incl. 21% employer contributions.
You’re not paying too little for QA. You’re paying more every year for the same result. There’s a mechanical reason for that.
Every new feature enlarges the surface that has to be checked before each release. No feature ever shrinks it. Your testing effort grows with the age of your product, not with your revenue.
Scale QA by adding people and you get a curve that never flattens. The metric that makes this visible is Cost per secured release. Almost nobody measures it.
Automation solved test execution. The last manual bottleneck is writing and maintaining test cases. That’s exactly where the curve breaks, and exactly where I come in.
QA isn’t an extra cost line in your budget. It’s an investment that stops you from paying for the same work twice.
Automation without structure just automates the chaos. That’s why I work in a fixed order.
First we clarify what needs testing, then build a strategy that fits your team.
Before anything gets automated, we clarify what actually needs testing. I review your requirements, your existing tests and your development process, and build a test strategy that fits your team, not a textbook.
Tests that run on every commit instead of costing someone time on every release.
Tests that run on every commit instead of costing someone time on every release. I build the automation and wire it into your pipeline so a red result is a clear signal, not a reason to switch the test off.
AI writes more code than ever, but hardly anyone checks systematically whether it does what it should. I advise you on using AI in your quality assurance the right way.
This is where the difference lies, in both directions. I advise on AI in testing and put it to work: your requirements become test cases and automation code. And I test what AI builds, from generated code to AI products. A test case an AI writes in seconds is only worth something once a human has checked that it tests the right thing.
test('checkout')
expect(total).toBe(…)
The manual step in the middle disappears. And the generation runs in your environment, not mine.
Three situations that come up again and again in different forms. Client names are withheld for confidentiality.
ISTQB certified · Project experience in large enterprises and the public sector, including Deutsche Bahn, Bilfinger and Paychex
A bug your customer finds costs more than any test. It costs revenue, trust and, in the worst case, the customer. Cutting corners on quality assurance doesn’t save money. It postpones the bill. And it comes back with interest.
| If you cut corners here | If you invest here |
|---|---|
| Your customers find the bugs and tell others. | Bugs surface before the release, not at the customer. |
| Every release becomes harder to plan. | You ship faster because you can rely on your tests. |
| Your team loses time. Every project takes longer and costs more than planned. | A clear structure takes the load off your team. Your developers work with more focus and deliver on schedule. |
| The competitor who ships clean takes over your customers. | You become the one who ships clean. |
You get more than tests. Your team learns where AI already takes real work off its hands: generating test cases from requirements, writing automation code, handling routine work that used to take days. And it learns where AI makes mistakes that someone has to check. You will use that knowledge far beyond testing.
| Your alternative | What stays afterwards |
|---|---|
| Hiring another QA engineer | one more head |
| A tester from a consultancy | nothing |
| Working with me | the structure, the automation and the AI know-how |
In the worst case, after the intro call you know exactly where your quality assurance stands today. It costs you nothing.
In the best case, your pipeline eventually tests itself and your team knows how.
You describe the situation, I ask questions. By the end, you know whether I’m the right fit. Free, no obligation.
We go into your process, your tests and your pipeline in detail. This is where the problem turns into a scope.
You get a proposal with a clear scope and a clear price.
From the first call to a signed proposal: possible in under two weeks.
I discuss pricing in the call, not on the website. Not as a tactic, but because the right investment depends on scope: a QA structure for a startup with four developers is something different from a regression strategy in a large enterprise. A number without context would be a guess.
Thirty minutes, free. You tell me where things get stuck, and I’ll tell you honestly whether and how I can help. If it’s not a fit, I’ll tell you in the call.
Book an intro callOr send me an email: info@kdessel.com