20-06-2026
~3 mins read

Helping knowledge move 

Usually, I do write a blog post first and then I bring a teaser on LinkedIn afterwards. This time, things happened the other way around (or the story goes in circles).
After sharing some thoughts recently, I kept coming back to a question I've been asked (and have asked myself) many times over the years: What is it that you actually want to achieve in your work?

At first glance, this is a question that seems quite simple. My focus areas have changed quite a bit over the years depending on my roles, and so have the environments I worked in. I've been involved in technical communication, product ownership, localization, terminology work, knowledge management, documentation, and more recently AI. One might think, all those things don't necessarily look closely related. But there is a pattern.

I've always cared about making expertise accessible, helping people learn from each other, and building structures that continue to work long after the initial problem has been solved. I enjoy connecting people, ideas, and perspectives. I love understanding how things work and figuring out what really matters. And it still amazes me to see how something that used to depend on a handful of experts has now become part of the way people work and learn together.

The parts nobody sees

Maybe that's why some of my favorite moments happen behind the scenes.
I enjoy conversations with developers and subject matter experts. Exploring ideas, asking one more question, untangling complexity, and helping someone explain something they've understood for years but never had to put into words. I like finding approaches that fit the people involved. Sometimes that results in a document, a template, a workflow, a content model, or simply a shared understanding that wasn't there before.

Questions that keep coming back

Over time, I noticed that I keep asking similar questions, regardless of the topic at hand.
How can we make this easier? How can we make it sustainable? What would help people contribute with confidence? How do we make sure valuable knowledge survives growth, change, and the occasional "Wait, who knows how this works?"

Those questions have followed me from technical communication to knowledge management, product ownership, and beyond. That is why organizational learning fascinates me so much. Most organizations do not lack subject matter expertise. The challenge is making sure people can learn from it, build on it, and continue to benefit from it long after the original expert has moved on to something else.

It gives me a sense of satisfaction to see people recognize connections, uncover hidden expertise, or come to realize that what they’ve known for years is valuable to others as well.

A word for the pattern

Somehow, isn't there a word that serves as the common thread running through all of this? How about “empowerment” or “enabling”?
I like the concept behind it, because I keep asking myself the same questions: understanding what is important and relevant, evaluating different approaches, and helping people build on the expertise that already exists in their environment.

Why AI feels familiar

What does not surprise me, is how naturally AI fits into that picture.
For years, I've cared about context, shared understanding, and making implicit knowledge explicit. Those things matter just as much when working with AI. The better we capture, structure, and connect what we know, the more useful AI becomes. That realization didn't feel like a new chapter. If anything, it felt oddly familiar.

I certainly didn't plan for enabling or empowerment to become a recurring theme throughout my career. It simply emerged over time. And maybe that's why the idea resonates with me so much.

I think I "accidentally" built my career around helping knowledge move.