Current, primary-sourced statistics on AI in engineering: adoption among engineers and developers, the split productivity evidence, trust and the almost-right problem, and investment, each attributed and dated.
AI in Engineering: Statistics Worth Knowing in 2026 Read More »
The real, category-by-category problems with AI CAD software: why text-to-CAD outputs non-editable meshes, why generative design needs heavy cleanup, file-format and IP risks, and honest workarounds.
Problems With AI CAD Software: The Real Failure Modes Read More »
How a small engineering firm should choose AI tools under real constraints: start with one business-tier general assistant, control client-data risk without an IT department, and keep the licensed-engineer boundary clear.
AI Tools for Small Engineering Firms: A Practical Buyer’s Guide Read More »
Why AI tools fabricate material properties, code clauses, and citations in engineering work, whether newer models are better, and a verification workflow to catch plausible-but-wrong output.
AI Hallucination in Engineering: Why It Happens and How to Catch It Read More »
Which AI tiers train on your data and which do not, what OpenAI, Anthropic, Microsoft, and Google actually say as of 2026, plus the NDA, export-control, and trade-secret risks specific to engineering.
AI Tool Data Security for Engineering: Protecting Your IP Read More »
A step-by-step gravity load take-down workflow and exactly where AI helps: tributary areas, ASCE 7 load combinations, and why a chatbot is a method assistant, not the analysis engine.
Structural Load Take-Down With AI: The Workflow, Step by Step Read More »
How to use AI to write engineering technical specifications: scaffolding and shall statements it does well, the standard numbers and tolerances it must never invent, and the ISO 29148 discipline that keeps a spec trustworthy.
AI Technical Specification Writing: Draft Faster Without Faking the Engineering Read More »
A six-step tolerance stack-up workflow and where AI genuinely helps: worst-case and RSS methods, the formulas, and why a chatbot is a method assistant, not the analysis engine.
Tolerance Stack-Up Workflow With AI: Where It Helps and Where It Must Not Read More »
A reference guide to material properties databases, from free lookups like MatWeb to design-allowable sources like MMPDS and mill certificates, plus where AI helps and where it must not.
Where to Find Material Properties Data You Can Actually Trust Read More »
An honest guide to using AI for cable sizing and voltage drop: what a language model speeds up, where it fails, and why the adopted code table and a qualified engineer own the final number.
AI for Cable Sizing and Voltage Drop: What It Can and Cannot Do Read More »
How to use AI to shortlist and justify a material choice, the tools that are genuine machine learning versus curated databases, and why to never trust an AI-quoted property value.
AI Material Selection in Engineering: What Works and What to Never Trust Read More »
