Amplified Quality Engineering

Welcome on the landing page of Amplified Quality Engineering. In case you reached this page based on a reference from the book, scroll down and find the table that guides you to the content you are looking for.

The use of GenAI is multifaceted and not without its challenges. It is therefore
essential—for individuals, teams, and organizations alike — to engage with this technology in a thoughtful and responsible way.

We start with our reflections and the central message we wish to convey.

When to Use and When Not to Use GenAI

There are times when AI—especially GenAI—can be super helpful, and other times when it’s just not appropriate. But how do you figure that out?

We use a straightforward Three Question Approach to help guide that decision.

When considering AI or GenAI to assist with a specific task — or even to fully delegate the task to an autonomous agent — evaluate the situation by asking the following three questions:

1. Does it matter if the output is correct?
   If it does not really matter if the output is completely correct — for example when you are creating software for a game for your children, or when you want to generate a nice image for a birthday message — then it’s perfectly fine to use one or another type of AI to support you.
   
2. Do you have the expertise and processes to verify if the output is correct?
   When the output must be correct, you must be able to make sure that the output indeed is correct. This needs knowledge (e.g. about business) and skills (e.g. in test design) but also the proper process and tools to actually execute these verifications.
   If you don’t have this in place, you simply should not use any form of AI.
   
3. Are you willing and able to take full responsibility for any inaccuracies?
   If you do have the expertise and processes to verify the output, you still may encounter situations where it goes wrong (remember: it is impossible to test everything!!). If this would happen, do you want to accept the consequences, and are you able to do so?
   If you are not willing or able, then again do not use any form of AI.
   If you are willing and able, then you can use AI but be very cautious. This, for example, means to always do a risk-assessment, following the guidelines such as those from the EU AI Act, and make sure you don’t take unacceptable risks (also keep in mind that some activities can never be fully delegated because human oversight is required).

Questions 1 and 2 are suitable for all involved to consider. However, question 3 should be addressed by the responsible management, as they will ultimately be held accountable for any consequences should issues arise.

Don’t Use GenAI…, Unless…

GenAI is not just as a tool to amplify development and testing, but also as a source of new risks and responsibilities. We share what we’ve learned, what we’re still learning, and what we believe is needed to use GenAI both effectively and responsibly.

Our main message is:
Don’t use GenAI…Unless, you know what you’re doing.
And you are willing and able to take full responsibility for the consequences, even if the results prove to be incorrect!!

Amplified Quality Engineering!!!

From this landing page we will guide you to all the concerning subjects related to these topics.

References from the book

In our book we guide you to this page for more information. In the table below you will find your link to the relevant content.

Chapter/Section	Description	Link to content
1.4	VOICE model	VOICE model
2.1	quality risk analysis	quality risk analysis
2.2.2	quality engineering strategy	quality engineering strategy
6.4.5	definition of quality engineering	definition of quality engineering
10.2.2	Agile Quality Improvement Framework	Agile Quality Improvement Framework
16.5	Prompt crafting template	template
23.2.2	Quality & Test Policy	Quality & Test Policy
28 – intro	Sogeti extensions to the quality characteristics	in progress
28.3	Quality characteristics	in progress
28.4.1	Definition of sustainability	in progress
28.4.1	Clean code architecture	Clean code architecture
31 – intro	Test design	Test design
31.1	Test design techniques and approaches	Test design techniques and approaches
31.1.2	Experience-based test design	Experience-based test design
35.5	Template prompting machine	template
36.1	Exploratory testing	Exploratory testing
36.5	Experience-based testing approaches	Experience-based testing approaches