A while ago I was stuck on a problem. I had been turning it over on my own for the better part of a morning, and I was not getting anywhere.

Then I walked to the coffee machine. A colleague asked what I was working on, I explained it in two sentences, and before my cup was even full he said something that pointed me straight at the answer. No meeting, no ticket, no scheduled call. Just two people standing next to a machine that makes mediocre coffee, tea for me.

That is the kind of moment I have been missing, and I think a lot of teams are missing it too.

If you have read my blogs before, you probably know about my passion for sports, and for Michael Jordan in particular. But there is a second passion I rarely write about, and that is music. Not just any music, but the kind that truly makes an impact, at least on me. And the more I think about it, the more I suspect these two passions are not so far apart after all.

It was two o’clock in the morning before I noticed the time.

Earlier that evening I had been building an application. I had written all the work in a backlog.md, a neat list of stories, and I let the AI pick them up one by one. It would finish a story, ask me to verify everything, and then close with a simple question: shall I pick up the next task?

And every single time, that question was the trigger. It would be a shame to stop now. Just this one more, and then I’ll go to bed.

In the previous part, I discussed how AI impacts learning and team effectiveness, highlighting the tension between speed and deeper understanding. While AI offers clear advantages, it also introduces new risks for long-term team health.

In this final part, I focus on how teams can consciously integrate AI while preserving collaboration, psychological safety, and strong team dynamics.

In part one, I explored how AI is subtly changing team dynamics through isolation and echo chamber effects. While AI makes individual developers more productive, it can also reduce the natural collaboration that strengthens teams.

In this part, we take a closer look at what this means for learning, knowledge transfer, and the balance between speed and depth in software development.

This blog kicks off a three-part series based on my article “AI’s Impact on Team Dynamics,” originally published in a special edition of JavaPro magazine for JCON Europe 2026, titled Java in the Age of AI. You can find the full magazine here.

In this first part, I explore how AI is already reshaping the way we collaborate as teams and the less visible effects that come with it.

In the lead-up to today’s Dutch parliamentary elections, we continually witness how political parties defend their own positions, often at the expense of constructive collaboration. This dynamic is surprisingly familiar to anyone who has worked in a large organization. The parallels between election campaigns and organizational silos are striking, and both can be damaging to the broader mission.

Just as political parties prioritize their own agendas over national unity, departments within organizations often pursue isolated goals, leading to fragmentation, inefficiency, and missed opportunities. In both cases, the absence of a shared vision undermines progress. The way forward lies in working together toward a shared goal, aligning diverse perspectives around a common purpose to create meaningful impact.

After 25 years in software engineering, I’ve witnessed many projects, from great success stories to those that never quite lived up to their promise. In our profession, success is not just about technology. Sure, we love our frameworks, CI/CD pipelines, and microservices. But the real power of a high-performing team lies in something much deeper: team dynamics.

In this blog I want to dive into the why, how and what of team dynamics and why it’s such a crucial element in the success of your project or organization.

You’re coding late at night. The lights are low. Your favorite playlist is playing, maybe something only you would call “focus music.” Your IDE is set to a theme that feels just right. You’re not rushing. You’re not distracted. You’re in the zone.

This is vibe coding.

In my previous blog post Prompt Engineering: Tool or Threat to Software Engineering?, I discussed what Prompt Engineering is and how it can be used to help us as software engineers. In this follow-up blog I will dive into Claude 3, the latest AI from Anthropic, and how it can impact us as software engineers.