Every engineering decision is a bet about the future, but when should you actually try to optimize a design, and when should you just build for robustness instead? In this episode of The Engineering Passion Express, we trace the answer through 2,000 years of engineering history, from Roman aqueduct builders who worked by trial and repetition, to Newton's calculus turning motion and force into something predictable, to steam engines and aircraft becoming genuine optimization problems once the physics were well understood.
Then we push into today's frontier: modern semiconductors, where individual transistors are some of the most precisely optimized structures ever built, but the interaction of billions of them together creates a level of complexity we can't fully predict. That's where the real question becomes "How do you design for what you don't yet understand?"
Along the way we borrow an idea from an unlikely source, Jeff Bezos's "regret minimization framework," and apply it to engineering: instead of chasing peak performance, minimizing the cost of being wrong.
Join me as we explore:
Why optimization only works once assumptions, constraints, and variables are well understood
How steam engines and early aircraft mark two different eras of engineering certainty
Why modern semiconductor design has to move from optimization to robust design
How "regret minimization" gives you a different way to design under uncertainty
Why every leap in certainty eventually creates a new frontier of complexity we don't understand yet
The Engineering Passion Express is about growing knowledge and the passion for engineering.
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Thanks for listening, Brandon Donnelly Please connect with me on linkedin @ linkedin.com/in/brandondonnelly
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