The First Time I Met 80s Pop Icon Kim Wilde, She Was Watching Me on Stage

The first time I met 80s pop icon Kim Wilde, she was actually watching me on stage.

It was 1997, in Deville, northern France. I was presenting my product prototype at a major partner event. To set the tone, my company had hired the West End cast of Tommy to open the show. It was loud, polished, and theatrical. Only later did I learn that one of the performers was dating Kim Wilde, best known for the pop hits Kids in America and You Keep Me Hangin’ On. She was sitting in the audience, watching what came next.

That detail should not have mattered. But it did. It added to the surrealness of the moment. “Encore une fois” by Sash! was pumping through the theater in sync with the strobe lights. A packed theater of around 300 people. One computer in the middle of the stage. And an announcer telling the audience they were about to be introduced to the future. I held my breath for a moment as I suddenly realized that was my cue.

Then I walked on stage.

The lights dropped. The music dulled. The screen behind me lit up with my desktop, projected larger than life.

It was supposed to be my Steve Jobs moment. Instead, it nearly ended my fledgling product career before it had even started.

As I tried to submit the first live form, which would show how this technology would change everything, it didn’t work. I hit Enter again.

Nothing happened. The form didn’t load.

Yes, I was bald, even back then.

Standing there, under the lights, with the silence deafening and every eye in the room fixed on that screen, all I could think was, I have blown it. I do not think I have ever been that nervous before or since.

I hit refresh, and to my eternal relief the form beautifully populated the screen. The rest of the demo performed flawlessly. At the end people clapped. Afterwards, lots of people told me how impressive it all was.

And to this day that is what stuck. Not the near catastrophe. Not the fact that I had almost bombed in front of Kim Wilde. But the validation that what we had built hit the mark. The clarity that came from putting a live prototype in front of real partners and clients and watching their reaction in real time. Not a slide or a roadmap. But a live rendering of what could be.   

That moment was not about personal exposure or nerves. It was about learning. It gave us confirmation that we were solving the right problem, in the right way. And just as importantly, it created alignment internally. Company executives saw firsthand how partners responded. Questions that had lingered for months were answered in minutes.

That kind of validation should not wait until the end of the process. It must happen at the front.

But for that to happen it requires product managers to step into uncertainty early, before everything is polished, before every edge case is resolved. The risk must be calculated. In my case, the prototype had been thought through, tested where it could be, before being presented to the audience that mattered most.

Today, product management spends much of its time managing workflow rather than shaping direction. Pipelines, backlogs, and delivery processes dominate the work. But many of the issues teams struggle to fix downstream originate upstream, long before delivery begins.

In the past, product managers were expected to engage directly with customers and partners early, before certainty existed. Prototypes were used as learning tools, not just delivery artifacts. Not because failure was desirable, but because learning mattered more than looking polished.

It is about where product managers choose to engage. Great product management happens at the front of the process. Where problems are defined and assumptions are tested. This is where direction is set. But it requires a willingness to step forward before certainty exists and to use real reactions as inputs to better decisions.

Related: How Product Management Lost Its Voice and Its Influence, and How to Get It Back

AI makes this even more important. As building becomes faster and easier, the cost of getting the problem wrong increases. AI can accelerate exploration and synthesis, but it cannot decide what matters or take responsibility for the result.

That moment in Deville was a turning point for me. Not because something almost failed, but because something real was learned. It reinforced a lesson that has stayed with me ever since. If product management wants to be central to the success of their product, it has to get closer to customers earlier, while the real problem is still being defined.