Quality

It’s 2025, and the last few years has seen an explosion of GenAI-driven tools in knowledge work like software engineering. Technologies like GitHub Copilot, Cursor and large language models like ChatGPT now allow developers to generate entire applications with just a few keystrokes. If you spend any time on LinkedIn or other haunts of tech influencers, AI tools are often presented like a magic wand: type a prompt, hit enter, and tada! An entire application is built, fully integrated, with no need for you as a developer to ever do pesky things like read docs or write tests. Just ask the right question, and the code appears as if by magic. Gone are the days where engineering required knowledge and experience to do a good job. We have outsourced that to the machine. ...

When developing software, there is a natural tension between “speed” and “quality”. They are often seen as opposing goals. Delivery teams are under pressure to ship new features as fast as possible, but the reliability and functionality of their systems can not be sacrificed. In fields like data engineering, this is especially apparent. The need to quickly gain new insights is real, but sacrificing on quality can result in the wrong insights, which is worse than no insights at all!. Does this relationship between speed and quality have to be a dichotomy? What if we could move fast, but also make sure we are delivering the kind of work we can be proud of as professionals? ...