Richard Johnson

A clear breakdown of what ChatGPT Plus adds for engineers, where it helps, where it does not, who should pay, and how it compares to Claude Pro and the free tier.

What the academic community on Reddit actually recommends among AI research tools, grouped by job with honest pros and cons, plus the hallucinated-citation warning to heed.

The three real reasons ChatGPT botches unit conversions: number tokenization, no dimensional tracking, and optimizing for plausible over correct, plus the fixes that work.

A repeatable method to verify an AI engineering answer: show the working, recompute independently, check units, trace citations, and know when a licensed engineer must sign off.

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.