Systems | Development | Analytics | API | Testing

Devoxx Poland 2025 felt different. Not because of revolutionary new frameworks or another "this changes everything" moment, but because of what didn't happen. The conference had an unusual dose of pragmatism, skepticism, and – dare we say it – common sense. Maybe it's because developers are asking the right questions: "Does this solve a problem?" and "What happens when this inevitably breaks?" Here's what emerged from the sessions we watched, and the people we spoke to.

The era of generative AI is upon us, and large language models (LLMs) like Claude are demonstrating incredible potential to revolutionize how businesses operate and interact with customers. However, to truly unlock this potential, AI needs secure and standardized access to the wealth of information and services locked within enterprise systems. This is where standards such as Model Context Protocol (MCP) come in, offering a powerful way to make enterprise resources AI-consumable.

Katalon officially signed a Memorandum of Understanding (MOU) with RMIT University Vietnam. This collaboration aims to bridge academic learning with real-world software development and software testing expertise, equipping students with an adaptive mindset, future-ready skills and AI tools. Leaders and representatives from RMIT Vietnam and Katalon at the MoU signing ceremony.

AI is a groundbreaking technology that is ready to modernize the way federal government agencies operate. By automating tasks and optimizing workflows, artificial intelligence (AI) promises to enhance efficiency, minimize errors, and boost productivity without adding resources. But as with any change—and especially one as transformative as AI—leaders need to take deliberate and cautious steps to ensure a smooth integration of these innovations and to gain the buy-in of government employees.

You’ve probably heard of the concept of ‘Frontend decides, backend delivers’ in app development. On the off-chance that you haven’t, it means that the frontend defines the data it needs, and the backend acts on this instruction. This makes the data-fetching process more efficient, simplifies the error handling process and frees us, the devs, from the need to constantly make backend changes. The GraphQL query language for APIs, developed by Facebook, is a vital tool in this regard.

Let’s take a moment to think about how far we’ve come. Remember when opening a bank account meant sitting at a branch, filling out stacks of paperwork? Or when transferring money meant writing a cheque and hoping it cleared in a few days? Now, you can do all of that and so much more, with just a few taps on your phone. So, what changed? And more importantly, what’s driving this massive shift in how we bank today? The answer lies in one word: AI in Banking.