The Quietest Eight Months of My Career: And What They Were Actually For


Contents

Have you ever noticed that the people doing the hardest work are often the quietest ones in the room? Or, for that matter, the quietest ones on LinkedIn?

I have been quiet for eight months. No posts, no weekly “fascinating insight” reshares, no carefully staged photos from conference stages. And before I write anything else, before I share what I found and what is coming next, I want to be honest about why. Because the reason matters. It shapes everything that follows.

Why Silence Sometimes Beats Content

There is a particular kind of noise on LinkedIn that I find quietly exhausting. The person who is simultaneously running a major project and posting three times a week about it. The consultant who has just walked out of a difficult meeting and is already writing a thread about what they learned. The speaker who shares a photo from every stage within the hour.

I am not saying those people are wrong. Some of them genuinely process by writing, and that works for them. But I know myself well enough to understand that I am not one of them. When I am in the thick of something difficult, I need all of my attention on the difficulty. Writing about it in parallel, shaping raw unfinished experience into digestible paragraphs with clean takeaways, would mean making it sound more resolved than it actually is.

And that is where a lot of leadership content goes wrong. It describes what the slide deck says should happen. Not what happens in the meeting room at 11pm on a Tuesday when three people disagree about the baseline data and the project sponsor is travelling.

So I stayed in the difficulty. And I chose not to write.

Three Years, One Mandate: When It Got Real

In June 2023, I took on an executive role running digital transformation from the inside at a company in the German construction industry. Not consulting from a distance. Not designing the strategy and handing over a PowerPoint. Actually doing it, as Head of Digital Transformation, with all the friction, politics, and unexpected turns that come with that.

The first year was largely about building the foundation. Mapping the landscape, understanding where the organisation actually was digitally versus where it thought it was, and earning the trust that would be needed for anything more ambitious. In 2024, we developed the first real AI Roadmap. Not a wish list: a structured plan that connected specific use cases to specific business problems, with priorities, owners, and realistic timelines.

Then February 2025 arrived. The EU AI Act came into force, and with it a shift in the entire conversation around artificial intelligence in European organisations. Suddenly, AI was not just a competitive topic. It was a compliance topic, a governance topic, a risk topic. And for us, it was also the starting gun for consistent use-case implementation. The roadmap moved from planning mode into execution mode.

That phase is where the last eight months of silence come from. There were two things happening in parallel that both demanded full attention. The transformation work at ALHO was moving from planning into real execution. And at the same time, two books were in their final stretch, the kind of finish-line work where every free hour either goes into manuscript review or it goes nowhere useful.

You cannot run a serious AI adoption programme, finalise two books, and simultaneously keep a posting schedule. Or rather: you can, but then you are performing productivity rather than being productive. The posting would have come at the cost of the actual work, and that trade-off was not one I was willing to make.

What the Construction Industry Teaches You About AI

The construction industry is not where most AI thought leadership focuses its attention. It is not fintech, not software, not a digital-native business with APIs everywhere and a founder who blogs about it. It is a world of thick-walled procurement processes, deeply experienced tradespeople who have built things with their hands for decades, and an entirely justified scepticism toward anything that promises to “change everything.”

Getting AI tools adopted in that environment is a categorically different problem than getting them adopted in a startup. The cognitive distance between a large language model and a site manager running a modular building project is not bridged by a webinar or a well-designed onboarding flow. It requires something slower and more patient: demonstrating, repeatedly and concretely, that a tool solves a problem the person actually has. Not a problem you have decided they should have.

What I found in those months is that the real adoption curve looks nothing like the ones in the consultant’s presentation. People do not move smoothly from “awareness” to “adoption” along a predictable slope. They move in fits and starts, driven by individual experiences and peer conversations that you can influence but not control. A single positive experience by a respected colleague can do more than three months of internal communications. A single bad experience can undo it.

I spoke about this at the Digital Transformation 2025 Congress in Leipzig in October: what really happens when AI meets organisational reality. Not the use-case showcase version. The version with the resistance curves, the unexpected bottlenecks, the moments where a senior leader nods enthusiastically in the workshop and then changes nothing about how their team actually works. Audiences, I noticed, relax when you tell them the messy version. Because they are living it. They had started to wonder if only they were finding it this hard.

Two Books That Found Their Final Form

While all of this was happening operationally, two books crossed the finish line.

Abfangen publishes in July 2026. It is about leading through organisational crises, specifically about what you do in the first days and weeks when you step into a situation that is already on fire. The central framework draws from something I know at a visceral level from thirteen years flying Tornado jets for the German Navy: in a crisis, the first job is always to fly the aircraft. You do not diagnose the engine failure before you have regained control of the machine. Organisations work the same way, and most crisis management approaches get this exactly backwards. The book is in German, written for German-speaking leaders, because that is the language I think in when the pressure is on.

Anker lichten follows in the autumn. It is about motivation, specifically about why motivation stalls inside organisations and what leaders can actually do about it. Not the motivational-speech version. The structural version, built on years of watching the same patterns repeat across very different companies. Why do good people disengage? What pulls them under? And how do you, as a leader, diagnose the actual problem before you reach for a solution that only treats the symptom? This question became sharper in the ALHO context, where AI adoption and human motivation turned out to be far more connected than any technology roadmap suggests.

Why DE and EN, and What That Means for You

A quick word about language, because it will become relevant as the weeks go on.

Some of what I publish here and on LinkedIn is in German. Some is in English. That is not inconsistency: it is deliberate. Abfangen and Anker lichten are German books, written for German-speaking executives and leaders. The ideas translate, but the specific pressures of leading in a German Mittelstand environment, the particular dynamics of Betriebsrat conversations, procurement culture, and the weight of “wir haben das immer so gemacht”, are better addressed in the language those leaders actually think in.

The English posts follow the English books, It Takes 10 to Transform and Alignomics, aimed at an international audience navigating large-scale organisational change. Different framing, different examples, but the same underlying principle: start with what is real.

If you are here primarily for the English content, the German posts will occasionally feel like background. That is fine. But I am not going to optimise the publishing schedule for reach at the expense of the actual people I am trying to reach.

What Comes Next

This series of posts, and the longer pieces here on #MY2CENTS, will cover the territory I actually covered in the last three years. What happens when AI projects start and nobody has told the middle layer that their daily work is changing. Why most AI roadmaps are built backwards. What the first-week interview looks like when you step into a failing project. What motivation anchors actually are and how to spot when one is dragging a whole team underwater.

There will also be things I am still working out. I do not plan to pretend I have everything solved. One of the things I found most useful during the months of silence was following people willing to say: “I thought this was going to work and it did not, and here is what I think went wrong.” That kind of honesty is rarer than it should be. I intend to do more of it.

The hardest workers are often the quietest ones. Now it is time to talk.

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