Tech News Roundup

We recently brought together tech leaders from a wide range of sectors for a roundtable on how AI is reshaping team skills and structure. That diversity in the room made one thing clear: everyone is grappling with the same questions, but arriving at very different answers.

At Ghyston, we've been taking a deep dive into lots of our clients' teams, assessing how they're using AI in their software engineering. And what we're finding across the board is that there's quite a gap - between the people leaning into AI software development the most, and those who are really quite sceptical of it, or fearful of it. What's interesting is how to handle that gap, and how to help bring a team together around it.

Most software doesn't fail dramatically. There's no single moment when the system crashes and everyone agrees it's time to act. Instead, legacy systems tend to degrade slowly, and the people closest to them often adapt so naturally to the workarounds that the underlying problem becomes invisible. As a technical leader, you probably already sense when something is past its best. But sensing it and being able to make the case for replacement are different things. Here are the signs worth paying attention to.