The Speed Trap
From the cockpit, speed feels like the ultimate advantage. Data streams in real time. Simulations run in milliseconds. Artificial intelligence is compressing learning cycles across motorsport and business alike. But when every competitor has access to the same acceleration, something strange happens. Speed stops being the edge. And that’s when many teams drive straight into the speed trap.
I’ve spent my life at the intersection of racing, media, and brand behavior — shaped by mentors who believed competition was a discipline, not a performance. I was raised inside the competitive cauldron of motorsport, where excuses are exposed quickly and performance is the only measure. That environment taught me to respect speed — but never mistake it for advantage.
The Diner in Daytona
In a quiet diner in Daytona after winning the GT class at the Rolex 24, the aging racer Sonny Hayes (Brad Pitt) sits with his former Formula One teammate — now F1 team owner — Ruben Cervantes (Javier Bardem) .
On the table between them sits a first-class ticket back to Formula One.
A second chance.
Ruben slides a 1990s cover of RACER magazine — a brand I created and built — across the table showing both men as young prospects. He asks Sonny what that younger version of himself would want him to do.
Sonny deflects. Jokes. Minimizes. Because that’s safer.
Ruben presses: “I’m offering you an open seat in Formula One. The only place you could say for one day — if you win — you are the absolute best in the world.”
Sonny studies the ticket and asks: “Ever seen a miracle?”
Ruben answers quietly: “Not yet.”
Later, alone, Sonny studies the ticket again. Then the magazine cover. Something shifts. Not nostalgia, but recognition of possibility.
With a wry smile Sonny silently accepts the challenge.
That scripted moment isn’t really about age, or second chances, It’s about whether someone still believes they can learn faster than the competition— even when the competition has changed.
That’s the same question artificial intelligence is now forcing on all of us.
The Age of Acceleration
We are living through the fastest acceleration cycle of our professional lives.
Artificial Intelligence now sits inside motorsport. It informs tire strategy, simulation modeling, stewarding review, driver development, sponsorship analytics, and the content ecosystem surrounding the sport. Across Formula 1, IndyCar, NASCAR, IMSA, WEC, WRC and Formula E, learning cycles have compressed dramatically.
That’s exciting. But here’s the uncomfortable part.
When everyone has acceleration, speed stops being the advantage.
And when speed equalizes, trust begins to matter more than velocity.
AI accelerates the race. But the race hasn’t changed.
We now live in a world where access to information is nearly universal. Analysis arrives instantly. Conclusions often appear before we’ve even finished forming the question.
But access to information isn’t learning.
Learning takes friction. It takes mistakes, reflection, and the humility to sit inside uncertainty long enough to develop judgment. AI can accelerate exposure and surface patterns, but it cannot internalize consequence for us.
That part remains human.
And when we stop doing that work — when we substitute instant answers for disciplined learning — the risk isn’t that machines become too intelligent.
It’s that we become less thoughtful.
In racing, that mindset doesn’t last long. Electronic timing systems don’t reward explanation. They reward performance.
Three Words
In 1979 I was racing a new Van Diemen Formula Ford under the guidance of my mentor and team manager Mike Hull. After a qualifying session debrief filled with explanation rather than performance, Mike stopped me mid-excuse.
“I thought you wanted to be a racing driver… but you’re showing real potential as an excuse maker.” Then he delivered three words that have shaped nearly everything I’ve built since: Racing is learning.
Four years earlier Mike had written something both humorous, and impactful, in my SCCA driver’s school logbook: “Nice job on the straights.”
Translation: you’re comfortable when things are easy. The real work happens in the corners — especially the fast ones where visibility is limited and exit speed determines everything that follows.
Learning fast
Racing guru Mike Hull (left) and the author, Riverside International Raceway, July, 1979.
Jeff Zwart photo
After that season I redirected my competitive instincts into something else that demanded the same commitment to learning. I left the publishing company where I worked and started what is now Pfanner Communications, Inc., and our Pfanner advantage consulting practice.
A mentor gives you the words. Life teaches you what they meant.
Mike went on to become Managing Director of Chip Ganassi Racing. Watch how he operates and you’ll see it immediately: he lives in now. No nostalgia. No ego. Just disciplined reflection and faster learning.
That behavior is advantage.
Not speed, not innovation: but Performance powered by disciplined learning.
That philosophy echoes the thinking of the late Mark Donohue, the brilliant driver-engineer who helped define the Penske era and co-authored The Unfair Advantage. Donohue understood something that still holds true today: speed matters, but intelligence determines the outcome
This is the real “unfair advantage” that has defined organizations like Team Penske and Chip Ganassi Racing for decades. In racing’s most competitive environments — Indianapolis, Daytona, Le Mans — success rarely comes from raw speed alone.
Advantage comes from teams that learn faster than everyone else while maintaining trust inside the system. Everything matters.
The deeper question isn’t whether AI weakens thinking. It’s whether we allow it to replace the hard work of learning.
Racing is learning. Business is learning. Survival is learning.
The Shift Happens series reflects the philosophy behind Pfanner advantage, the consulting practice of Pfanner Communications, Inc., where leaders work to sharpen judgment, accelerate learning, and create durable advantage when the stakes are real.
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