Trends

Agentic Software Engineering

Generative AI is changing the way we build software—from individual code snippets to fully agent-driven development workflows. Agentic software engineering refers to the systematic use of AI-powered agents throughout the software development process: from analyzing requirements and shaping architecture to autonomously implementing features. The goal isn’t full automation, but a balanced collaboration between human expertise and machine support. That means it’s not just about choosing the “right tool,” but about understanding when and how to apply these tools effectively—and where deliberate boundaries are needed. We support you in putting this transformation into practice with your team.

MCP

The Model Context Protocol (MCP) provides a standardized way to connect AI models with external services and data—a kind of USB-C for AI. Much of the conversation around MCP focuses on technical specifics. But the real potential lies elsewhere: MCP lowers the barrier to putting AI to work inside organizations. Instead of building custom integrations for every use case, teams gain unified access to data and services—making AI usable far beyond engineering. That changes who gets access to information. And how innovation happens.

Accessibility

Accessibility is too expensive, prevents a fancy design and supports only a small group of users? If you're working in software development and your focus is on web accessibility you're probably only too familiar with this kind of prejudices. We advocate a different approach and show why investments in accessibility pay off eventually. Because by focusing on the users, it creates the foundation for a better user experience and thus for successful software products. (Microsite in German)

Cloud Migration

Cloud migration is the process of moving workloads, data, applications, and processes to a cloud environment. In most cases, resources are moved from an on-premises data center to a cloud vendor. Sometimes the shift is from one cloud provider to another. The reasons for this are manifold. Some companies hope for reduced costs, some for more flexibility, and sometimes regulations force you to use more than one cloud provider. From Legacy to Cloud Native: We compiled what needs consideration.

Data Mesh

Many organizations have invested in a central data lake and a data team with the expectation to drive their business based on data. However, after a few initial quick wins, they notice that the central data team often becomes a bottleneck. Is Data Mesh the better approach?

Self-contained Systems

An architecture that focuses on a separation of the functionality into many independent systems, making the complete logical system a collaboration of many smaller software systems. This avoids the problem of large monoliths that grow constantly and eventually become unmaintainable. Over the past few years, we have seen its benefits in many mid-sized and large-scale projects.