TBD - will follow shortly
AI is making product work easier, which is great news for good product teams and slightly alarming news for the rest of us. Specs can be drafted in minutes, research can be summarized instantly, and prioritization can now look intelligent with very little effort. The problem is that easier product work is not automatically better product work.
In this talk, Fabian Kleeberger explores what happens when AI enters product organizations that were already not very clear on strategy, problem framing, decision-making, or what success actually looks like. If those conditions stay the same, AI does not solve them. It helps them move faster, look sharper, and become harder to question.
This is not a talk against AI. It is a talk about what has to change before easier product work becomes better product work. Fabian will show how product leaders can tell whether AI is improving judgment or just improving the appearance of rigor, and what foundations need to be in place before acceleration starts creating value.
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Fabian Kleeberger
Fabian Kleeberger works where product, growth, technology, and organizational complexity stop being separate topics and start becoming each other's problems. Over the past 20 years, he has led products and product organizations through growth, complexity, and change in environments shaped by AI, data, and cross-functional transformation.
With a background in sociology, psychology, and data, Fabian brings an unusually systems-oriented lens to product leadership. He is probably the only product executive whose reference points include Niklas Luhmann, which may explain both his fascination with how organizations behave under pressure and his low tolerance for frameworks that sound elegant in theory but would clearly collapse in a real company.
Before moving into product leadership, Fabian worked in early childhood research, which might be the reason for his enduring interest in how people learn, how groups behave, and why "senior leadership" is not always as mature a category as it sounds. His work focuses on what it takes for companies to stay intelligent when growth, pressure, politics, and AI start pulling in different directions.
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