Quality Insights

31.03.2026

“Deutschland-Stack” for government IT
What “DevSecOps only” actually means

In March 2026, the German IT Planning Council adopted the “Deutschland-Stack”. One of its core principles is “DevSecOps only.” Read on to learn what this decision means for development and testing processes in German government agencies and how you can get started today.

24.03.2026

Reasoning AI under scrutiny
How to make explainability verifiable

LLMs that use reasoning explain their answers in natural language. This opens up new possibilities for audits in regulated industries. One prerequisite is that the explanations themselves become part of the quality assurance process.

14.03.2026 by Matthias Lutz

NIS-2: More than 18,000 companies are missing from the BSI portal. What’s behind this?

Over 18,000 companies missed the NIS-2 registration deadline with the BSI. The cause is often not negligence, but rather a capacity issue. What to do now.

05.03.2026

The EU AI Act by industry
What distinguishes the medtech, automotive, finance, and administrative sectors?

The EU AI Act affects almost every industry, but not all industries are affected in the same way. What specific obligations apply to the medical technology, automotive, finance, and public administration sectors? Here’s a compact industry comparison.

02.03.2026

Digital accessibility affects one in six people – and your software

Does accessibility sound like a niche topic? One in six people worldwide has a disability – and 70 percent of these disabilities are invisible. Our free webinar shows you what this means for your software and how AI is changing testing.

27.02.2026

The EU AI Act in 2026
What every company using AI software needs to know now

The EU AI Act is the world’s first comprehensive AI law, and it impacts many more companies than most people realize. Here’s an overview of risk levels, deadlines, and affected industries.

18.02.2026

AI in the CI/CD pipeline
A hackathon demonstrates how it works

CI/CD pipelines generate thousands of log lines every day. At an AI hackathon, a team led by our colleague Yu Zou developed a tool that automates error analysis, solution proposals, and risk assessment. A field report.

16.02.2026

How to secure AI systems: Why traditional testing is not enough

AI software behaves fundamentally differently from traditional applications. Those who test it using conventional methods risk blind spots in audits and approvals. Which approaches will make a difference in 2026?

10.02.2026 by Matthias Lutz

From AI pilot trap to productive application

75 percent of companies are experimenting with AI, but only 25 percent are achieving measurable benefits. What distinguishes successful AI projects from unsuccessful ones? The answer lies not in technology, but in strategy, implementation, and change management.