Christoph Gulden invited me onto his Thought Leaders Talk. Christoph reviews investment decisions for a living, I guide companies through technology waves. What came out of it is an argument about the 90 percent of AI pilots that never reach production, and what that means for the next investment decision. At one point Christoph contradicts me openly, and he is right to. The dialogue below is the one we worked out together. The original appeared in German on LinkedIn; this is my English version.
Most AI projects do not fail on the technology. They fail earlier, on a thinking error: the hunt for one giant use case, the lighthouse project.
This is the launch of my new podcast Prompt & Proper, which I host together with Steffen Ochsenreither from Swiss Post. Every two weeks, in German, hands-on and without the marketing speak. Episode 1 takes apart what we call the “giant use-case fallacy”: why the management signal “we are doing AI now” so often ends in nothing, and what a good first use case actually needs. The episode is in German, and this post captures the core of the conversation.
Everybody is suddenly saying “agentic platform.” Almost nobody can define one. That is exactly what we set out to fix.
I invited Kaspar von Grünberg onto the channel. He has spent years shaping platforms, put the internal developer platform, the IDP, on the map with Humanitec, and built PlatformCon into the largest platform engineering community. He is now building Canyon, a control plane for enterprise AI, and his book Thinking in Platforms is on the way. By the end of this conversation you will know what an agentic platform actually is, why it matters, what it takes to build one, and how to start.
Most innovation does not die at the patent office. It dies long before that, in the way an organization makes decisions, executes, and turns ideas into outcomes.
I was invited onto The Hard Things About IP, hosted by Dimitris Giannoccaro and produced by IamIP, for Episode 7. We stepped beyond patents and legal frameworks to the question that sits before every filing: how do organizations actually turn ideas into real results? We talked about AI transformation, organizational design, why so many AI initiatives get stuck in pilot mode, how feedback loops drive decision-making, and why accountability needs to live where the work happens.
I joined Lisa Stähli on the Hello 50:50 World podcast, the show with the mission to make tech more humane, for a conversation about what actually happens when software teams add AI to the way they work. We talked about how AI is reshaping software engineering, DevOps and agile ways of working, where the real bottlenecks sit, the human cost of moving faster, and why the organisation you build around the technology is what decides whether AI helps or hurts.
I joined the adorsys Tapas & Pretzels podcast for a conversation with co-hosts Tim and David, fellow Chief AI Officer, about the question every leader is now asking: how do you move AI from isolated experiments to a company-wide capability? We talked about token economics, what the Chief AI Officer role actually demands, why capability beats tools, the trust gap that governance exists to close, and why most companies are speeding up broken processes instead of rethinking them.
I joined Emily Erker on her show Lady Sunshine Live for a German-language conversation about building future-ready organisations through what I call a cybernetic enterprise: the integration of people, processes, technology, and AI in continuous feedback loops. The full video is embedded below; what follows is my English summary of the key ideas we covered.
Header photo: Romano Roth (left) and Raphael Reischuk. Source: Zühlke (zVg), via inside-it.ch.
Effective 1 May 2026, the Zühlke Group has introduced two new roles at group level: a Group Chief Technology Officer (CTO) and a Group Chief AI Officer (CAIO). I have taken on the Group CAIO role; my long-time colleague Raphael Reischuk has been appointed Group CTO. Both of us were already partners in the group.
Although AI has moved fast, many organisations haven’t. Most leaders we speak to aren’t short on ideas, proofs of concept, or vendor demos. The challenge is turning AI into something repeatable, a capability you can trust, scale, and steer without creating new risks or bottlenecks.
Discover the people, processes and technology you’ll need to mitigate setbacks on your transformation journey, and unlock AI-augmented ROI that compounds as it scales.
Most companies that work in an agile way today while simultaneously trying to implement AI will not survive the next decade, in my opinion. The reason: their operating system is too old. The future is not agile. The future is not AI either. The future is cybernetic.
Does AI really solve the problems we have? What does it mean for innovation and intellectual property? Will AI replace patent analysts? In this webinar with IamIP, I cut through the fog of AI hype and share a practical framework for understanding where AI genuinely adds value, and where it falls short.
