Engineering

The three different limits on AI tools explained: usage caps, API rate limits, and the context window, why they exist, and how to stop hitting them.

Why AI models get engineering unit conversions wrong, which conversions invite which mistakes, and a five-step workflow to keep the error out of your work.

A repeatable protocol for testing whether an AI tool is accurate enough for engineering calculations, paired with what independent published benchmarks actually found.

A step-by-step cable sizing workflow with an AI assistant in the loop: gather inputs, check corrected ampacity, voltage drop, and short-circuit withstand, then confirm every number against the NEC or IEC table.

A side-by-side price comparison of the main AI tools engineers choose between: free, individual (around $20/mo), power ($100 to $200/mo), team per-seat, and quote-based enterprise tiers.

Which AI tools and tiers do not train on your inputs by default: the business and API tiers of OpenAI, Anthropic, Google, and Microsoft, versus the consumer tiers that train unless you opt out.

What structural engineers say about AI tools, synthesized honestly: used for drafting and scripting, kept off the analysis and load path, with a reality check on the tools.

Stop letting a chat AI produce your engineering numbers: it predicts tokens, not computes. Use AI to set up and explain, a computational engine to solve, and verify.

When an engineer should deliberately not use AI: stamped work, life-safety calculations, confidential data, unverifiable output, novel problems, and code work.

Compare candidate parts’ datasheets fast without picking wrong: let AI tabulate and normalize, then confirm every deciding value on the primary datasheet.

AI CAD software is priced four ways: AI bundled in the subscription, at a higher tier, by usage or credits, or by enterprise quote. Verified 2026 prices.