Hardware Podcasts

S7E28 Justin Rittenhouse | What Engineering School Doesn’t Teach You About Industry

Being an Engineer · 3 Jul 2026 · 49m · Episode 28

AI in practice: one real use of AI described

What this episode covers

Justin Rittenhouse, a mechanical engineer and author of 'Secret Keys to a STEM Degree,' discusses the gap between academic training and industry reality. He highlights that while school emphasizes complex math, industry requires project management, trade-offs, and proficiency in Excel. Rittenhouse advises new engineers to focus on career alignment, ask questions without fear, and manage stress through sleep and time management. He also explores the practical applications of AI in manufacturing optimization and the importance of leadership and marketing skills for engineers.

AI in practice

Where this conversation describes AI being used to build or deliver a product. Part of the AI in practice tracker.

Manufacturing

AI analyzes sensor data from machines to identify optimal settings for throughput based on environmental factors like humidity and temperature, allowing operators to optimize production without manual trial-and-error.

“you can collect data with many different sensors on a machine and not on the machine, like maybe humidity increases your throughput, maybe it doesn't, but also temperature sensors and stuff like that, and then you can have AI kind of look through that data and be like, "Hey, when we had this setting, this setting, at this humidity, we produced way more, but at this humidity in these settings we actually had higher output.”

Justin Rittenhouse · Hear it at 30:51

Most relevant to

early-stage companies

Topics

Mentioned

Companies
Denso, Glass Master Controls, J Letten Meyer, Worfle, Pipeline Design & Engineering
Products
Secret Keys to a STEM Degree
Tools
Excel, Matlab, Python, Google Spreadsheets

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