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The modern F1 pit crew: AI engineers who race the deadline, not the car

From SiliconAngle

By Ryan Stevens

October 5, 2026

The modern F1 pit crew: AI engineers who race the deadline, not the car

The modern F1 pit crew: AI engineers who race the deadline, not the car

AI providers increasingly embed forward-deployed engineers inside customer operations, and few settings test that model harder than Formula One. Races arrive every two weeks, budgets are capped and margins are measured in milliseconds.

That model is now on track with the Aston Martin Aramco Formula One Team, including new physical AI engineering service places cloud engineers alongside the team’s own. The value lies less in motorsport know-how than in lessons from running infrastructure for top AI labs, according to Richard Ahlfeld (pictured, left), senior vice president of physical AI at CoreWeave Inc.

“CoreWeave, over the last years, has helped most of the world’s leading AI companies set up infrastructure and run their models,” Ahlfeld said. “You can’t really do that without learning a thing or two about what is really needed to run AI.”

Ahlfeld and Eric Ernst (right), commercial technology ambassador of the Aston Martin Aramco Formula One Team, spoke with theCUBE’s John Furrier and Dave Vellante at Fully Connected, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed the F1 team’s technology partners, whose stack runs from processors to the AI cloud. (* Disclosure below.)

Forward-deployed engineers race the F1 clock

Each car produces a million data points per second, and the team has to turn that flood into setup decisions between final practice and qualifying, according to Ernst. Outside engineers help because the calendar never pauses.

“We really need people that can be outside of the car development phase and come in with the fresh knowledge of what’s happening in this industry that is moving extremely quickly,” Ernst said. “You can build as many processes as you want, call it agile, whatever you want. You cannot stop that process. You got to hit a deadline.”

One early project tackled team radio. With dozens of open channels across the grid, teams have long relied on rooms full of people listening in, Ahlfeld explained. Then AI stepped in.

“The AI model listens to 40 people at the same time, puts a summary and immediately already knows [what to do] from a prompt,” Ahlfeld said. “If somebody is pitting, I need to do XYZ within the next 30 seconds.”

CoreWeave also taught the model driver lingo, so “oversteering” and “overheating” don’t blur together over engine noise, Ernst added. The work now anchors CoreWeave’s physical AI field engineering playbook, which spans more than 100 projects that start from a customer’s deadlines and work backward. For forward-deployed engineers, part of the job is knowing when AI isn’t the answer, since some steps can be handled by a simple rule.

“Not everything needs to be over-engineered,” Ernst said. “Look at the process first, and then say, ‘Where do we bring the tech in?'”

Here’s the complete video interview, part of SiliconANGLE’s and theCUBE’s coverage of Fully Connected:

(* Disclosure: TheCUBE is a paid media partner for the Fully Connected 2026 event. Neither CoreWeave, the sponsor of theCUBE’s event coverage, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE

View original article on siliconangle.com

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