Who this is for
You lead a team, a product, or a change initiative. You've seen good ideas die in meetings. You've watched pilots launch and quietly disappear. You know something is stuck, but the usual advice (more alignment! better communication! try this framework!) doesn't land.
What you'll get
No methodology. No certification. Just observations from many years of building design and product teams across industries: architecture, e-commerce, automotive, SaaS, PropTech. Patterns I've seen repeat. Mistakes I've made more than once. Things that actually moved the needle when everything else failed.
Why I'm writing this
I've spent most of my career in rooms where transformation was supposed to happen. Sometimes it did. More often, it didn't. The tools were there. The talent was there. What was missing was simpler, and harder to fix: honest cultures, clear ownership, and teams small enough to actually move.
45% of workers now use AI regularly. That's up 13% from last year.
But here's the twist: confidence in using technology dropped 18%. And 43% fear automation will replace their job within two years.
People are adopting AI faster than ever while trusting it less. That gap tells you everything.
BCG puts numbers on it: 70% of AI project failures come from people and process issues, not technology. McKinsey found that middle management (the layer that actually runs most companies) resists change for perfectly rational reasons. They're busy. Their current methods work well enough. Learning something new is exhausting.
What nobody wants to say out loud: most company cultures aren't honest enough to adapt.
The European angle
This hits differently in Europe. We're 80% dependent on US tech for our digital infrastructure. We talk about sovereignty but GAIA-X quietly failed. Meanwhile, our traditional strength (the Mittelstand, the hidden champions) often treats "fail fast" as an insult rather than a method.
I'm not interested in the Silicon Valley playbook of "move fast and break things." That's not how things work here, and pretending otherwise doesn't help. But I am interested in how small, focused teams can detect opportunities, build solutions quickly, and survive long enough to matter.
It doesn't help to build 12 machines instead of 10, when you can only sell 9. More output isn't the answer. Better sensing, faster learning, and honest feedback loops are.
What this series covers
- Culture eats AI for breakfast
- The honesty problem
- Small teams win
- Agent-assisted work
- Surviving success
I'll be posting in the LinkedIn group and linking to longer versions here. Comments, disagreements, and war stories welcome.
Sources
ManpowerGroup 2026: Global Talent Barometer
BCG 2024: AI Adoption in 2024
McKinsey 2024: The Learning Organization
Gallup 2025: AI Strategy and Culture
Draghi Report 2024: European Competitiveness