MIT ran a striking experiment: give undergraduate teams four weeks, unlimited access to modern AI tools, and the task of designing, building, and testing a real subscale jet engine that produces 50–100 pounds of thrust on Jet-A fuel.

The results were revealing. AI proved useful for retrieving and summarizing technical knowledge, exploring design alternatives, teaching software tools, and accelerating early analysis. However, it struggled with detailed CAD reliability, physical intuition, and — most critically — the manufacturing and vendor realities that became the true rate-limiting step. Hallucinations and sycophancy further eroded confidence when teams needed precision.