Engineering

A practical method for using ChatGPT in engineering: prompting with role, context, and constraints, the tasks it suits, its accuracy limits, and protecting your data.

The best free AI tools for engineering students, grouped by job: solving math, research, writing, coding, and revision, with where each free tier runs out.

Read a legacy engineering drawing the right way: title block, first vs third angle projection, revisions, symbols, and where AI helps or misleads.

An honest review of Perplexity AI for research: its citation features, where it helps, the accuracy caveats, pricing, and how to use it in a workflow.

Wolfram Alpha vs ChatGPT: a task-by-task comparison for STEM students, when to use each, how to pair them, and honest pricing.

Are AI CAD tools worth it? An honest look at generative design, AI copilots, and text-to-CAD, with the evidence and a worth-it verdict by scenario.

MATLAB vs Python for engineers: an honest comparison of cost, ecosystem, AI and ML support, and AI-assistant reliability, with a clear pick for each path.

The seven limitations of AI in engineering that matter most, each grounded in published evidence, and the practical workaround for each.

Can you upload CAD files to ChatGPT? Which formats work, what Code Interpreter can compute, the privacy rules for proprietary drawings, and a workflow that works.

Can AI do engineering calculations? Why it gets numbers, units, and interpretation wrong, and the workflow that makes AI calculations reliable.

Which structural analysis tools add real AI, what that AI actually does, and why the solver and the licensed engineer still run the job.