Engineering

Which AI tool should an engineer use? A decision framework: pick by task, discipline, data sensitivity, and budget, then verify every output.

AI speeds up datasheet search and component selection by building a shortlist, but part numbers, stock, and lifecycle need confirming on a distributor.

AI tool terms of service decide who owns outputs, who is liable, and whether you are defended. The six clauses engineers should check before adopting a tool.

AI can help read a datasheet by summarizing and explaining, but is unreliable at extracting exact values from tables, ratings, and graphs, so verify every value.

Using AI with a client drawing set is safe only on a no-training business tier, backed by a data processing agreement, with client consent.

Can AI do CAD? It assists in four real ways but does not autonomously produce production-ready editable parametric models; the engineer stays in charge.

AI can explain wiring-diagram symbols and interpret small circuits, but it is unreliable at extracting exact connections from a dense schematic.

A workflow for replacing an obsolete or end-of-life electronic component: use AI to shortlist candidates, then confirm form, fit, and function on the datasheet.

AI can explain GD&T symbols and draft inspection plans, but it is unreliable at extracting exact tolerances and datums, so every value needs verifying.

AI engineering tools split into two cost worlds: general assistants at tens of dollars a month, and specialist CAD and FEA software at far more per seat.

How to run an electrical load calculation under NEC Article 220, and exactly where AI helps and where it must never be trusted for code values.