New book | Amplified Quality Engineering

Amplified Quality Engineering – book launch

We have launched the latest book in the TMAP® Series – ‘Amplified Quality Engineering’.

Launch date: 23 September 2025!

In this Generative AI (GenAI) and Agentic AI era, quality becomes an integral part of everything AI generates, right?

And if that is the case, then there is no longer a need for Human Intelligence to ensure quality, right?

And if that is the case, the long-predicted end of the field ofQuality Engineering and Testing is approaching rapidly, right?

I do not have the illusion that I can predict the future, but I do believe that in the future, perhaps more than ever, there will be a need for expertise in Quality Engineering and Testing. Yes, AI
will change the way we work and live, but how do we distinguish what is correct and what is not? How do we know what is real or fake? The book Real Fake [Doorn 2021] written by my colleagues
at the Sogeti Research Institute for the Analysis of New Technology, describes how the world is now flooded with data that is indistinguishable from real. A photo of a person with six fingers
or three ears is still funny, but if your chatbot turns against your organization, or if there are errors in your AI-generated contracts, making you vulnerable to claims, it quickly becomes
a different story.

So, although AI is capable of processing and generating enormous amounts of data, in our view, Human Intelligence remains crucial in the near future to ensure that this data is reliable, unbiased and ethically responsible. Precisely because of the rise of GenAI and Agentic AI, the field of Quality Engineering and Testing will soon rise to a new level of importance. The complexity and speed at which AI systems evolve require a new approach to quality engineering. The complicated nature of GenAI learning models makes them function as black boxes. It is becoming difficult to understand why content was created in a certain way. This makes debugging and root cause analysis much harder to accomplish without the proper tools and expertise. It is not sufficient to rely solely on the output of AI; we must thoroughly test and validate the processes and algorithms behind that output. This book offers insights and practical tools to tackle this challenge.

As a leader in Quality Engineering and Testing, I believe Sogeti has a responsibility to share its expertise and vision on amplified quality engineering with and for GenAI. This book reflects our commitment to delivering top quality and to continuously improve our quality engineering and testing body of knowledge.

Many thanks to the authors of this new book in the TMAP series Rik Marselis (Principal Quality Consultant at Sogeti), Jeroen Egelmeers (Prompt Engineering Advocate & GenAI Whisperer ) and Wouter Ruigrok (Quality Consultant) and all people who have contributed.