Systems | Development | Analytics | API | Testing

The meeting started with a question I wasn't expecting. "Dragan, if AI can write tests now, what exactly will your team be doing next year?" Q1 2025, six months before I founded Quantum Quality Engineering. The executive wasn't hostile, just genuinely curious. Behind that curiosity lurked a more complex question: Do we still need QA leaders in an AI-driven world?

Ably AI Transport is now in early access. It gives your AI the continuity, awareness, and multi-device reliability users actually expect. Drop it in, keep your existing stack, and start shipping Gen-2 AI right away.

By Erez Schnaider, Technical Product Marketing Manager, ClearML Slurm has powered HPC environments for years. It is battle tested, widely adopted, and deeply embedded in research and engineering workflows. Over 60% of the TOP500 supercomputers use it to manage their large infrastructure, orchestrate workloads and schedule jobs, as it is powerful and versatile with over 20 years of engineering behind it.

In today’s world of software development, API-first has become more than a trend it is a best practice that allows teams to build scalable, modular and best of all future-ready applications. In an API-first approach, the Application Programming Interface (APIs) are not an afterthought, they are envisioned, documented and agreed upon before the development of an project in begins.

You don’t wake up caring about badges. You care about data that’s actually extractable, pipelines that don’t fall over, and teams that aren’t stuck copy-pasting CSVs. Still, it’s good when the market validates that. In the Europe Grid Report for Data Extraction | Winter 2026, Keboola is a Leader on the Mid-Market Europe Regional Grid for Data Extraction.

ETL tools automate the process of extracting data from source systems like Salesforce, transforming it into analysis-ready formats, and loading it into data warehouses, BI platforms, or other business applications. This automation eliminates the manual export/import cycles that drain resources and introduce inconsistencies.

Modern enterprise data strategies require seamless integration across cloud warehouses, legacy systems, and operational applications. Organizations report that 89% now operate multi-cloud environments, creating architectural complexity that traditional point solutions cannot address.

Apache Kafka powers real-time data at companies processing substantial event volumes daily. The new KRaft architecture makes getting started easier than ever. The platform handles massive data flows for more than 80% of Fortune 100 companies (Apache Kafka), according to the Apache Software Foundation. Event streaming represents a fundamental shift in data processing. Traditional databases save snapshots. Event streaming captures data in motion. It's the difference between a photo and live video.

Every test team has asked the same question at some point: “Should we automate this, or just test it manually?” The answer is rarely black and white. That’s why a Manual vs. Automation Decision Matrix exists to bring clarity to the chaos. It helps teams understand the lifecycle of a test case, its complexity, how often it runs, and the value it adds to product stability. With a decision matrix, you can make more informed, ROI-driven decisions.

Finance teams are smart, but not infallible. Even the most talented and dedicated finance professionals, like the ones on your team, are bound to make a mistake from time to time. But some mistakes are more costly than others. Have you ever been in the middle of a presentation and realized that you were talking about the wrong data? Or have you had an executive ask for data that you simply couldn’t find? With the right tools and automation, you can avoid these embarrassing moments.