AI can spit out thousands of “optimized” airfoils in seconds, but what happens when the objective is wrong, the mission changes, or the aircraft has to be certified and insured? We talk with Patrick Hanley, founder of Hanley Aerospace and author of Aerodynamics in Plain English, about why real aerodynamics is still built on fundamentals, not AI, not vibe coding. 

Patrick shares his story from St. Kitts and Nevis, tiny islands in the Caribbean, to MIT, and how a deep love of math turned into a lifelong habit of writing software to solve aerodynamic problems  —  in his spare time. We dig into how his CFD products evolved as the market shifted from paid tools to free alternatives, and why he kept climbing toward higher-fidelity capability. He explains the practical engineering choices behind accuracy, including why grid strategy matters so much, what validation really means, and how a focused tool like Stallion 3D can carve out a global niche even while giant multiphysics platforms dominate mindshare.

We also go beyond CFD theory into the real aerospace work: Terrafugia and the flying car program, the mission logic behind eVTOL air taxis, and the overlooked constraint that shapes urban flight more than range does: noise. 

Finally, we take a hard look at AI in engineering design, from automated shape generation to liability, and why prototypes and testing still catch the failures no simulator can predict.