I used to read The Oatmeal religiously, but somehow stopped years ago.

This is a Good Take on AI Art, as I’d expect from Matt.

As I’m getting older a lot of my social circles are becoming ever more conservative. The focus shifts from building with ambition to fiercly protecting what one has achieved. Shifting the mind on protectionism makes one consider all that can cause damage. It puts the focus on the negative, it makes those negative thoughts feel much more significant than they are and one dwells on the past, instead of envisioning of what opportunity might lie ahead.

I found Matt’s website today and had a lovely couple of hours exploring his writing.

I love most of his 15 Rules for Blogging, but this one in particular…

One idea per post. If I find myself launching into another section, cut and paste the extra into a separate draft post, and tie off the original one with the word “Anyway.” Then publish.

I regularly get excited enough to write a kinda-strem-of-conciousness thought down which turns out to be half-decent except for the end. And these often languish as drafts for ages for want of a neat way to wrap them up.

I just looked at my unfnished drafts and about two thirds of them are hard to wrap up because they contain multiple kinda-related ideas which are just a bit too hard to bring together in a conculsion I’m happy with.

Anyway.

And that suggests another risk we don’t talk about enough: every time we hand work to a wizard, we lose a chance to develop our own expertise, to build the very judgment we need to evaluate the wizard’s work.

But I come back to the inescapable point that the results are good, at least in these cases. They are what I would expect from a graduate student working for a couple hours (or more, in the case of the re-analysis of my paper), except I got them in minutes.

This is the issue with wizards: We’re getting something magical, but we’re also becoming the audience rather than the magician, or even the magician’s assistant.

The fundamental problem lies in misaligned capabilities and understanding. AI generates working code fast but cannot instill architectural thinking or testing discipline.

Users gain false competency. They produce working software without grasping underlying complexity or long-term implications.

Engineering best practices must become as accessible as AI coding tools. Security improvements and test generation should happen in natural language.

The future involves hybrid workflows. “Vibe coders” prototype solutions while engineers harden successful experiments.