The Tragedy of AI Coding

My family and I enjoy the occasional meal of delicious slow-cooked meat, but every time we visit a barbecue joint, we can’t remember whether we like the beans and slaw on offer.

Some beans are sweet; others are spicy.

Some slaw is vinegar based; others creamy.

We should keep track of this somehow , we always say but then never bother.

I should make an app , I used to joke.

But that was a ridiculous idea.

Thanks to generative artificial intelligence, it became less ridiculous.

By last summer, I had been making small programs with AI for some time.

AI’s adeptness at programming was helping me, a busy person with a professional programming background but limited reason to program, work creatively with computing for the first time in ages.

I wanted to see how far I could push AI as a solo programmer.

The barbecue-sides-preference problem, I reasoned, would serve as a perfect test case: building a fully featured iPhone app—Beanslaw, I called it—with esoteric utility that nobody would have bothered commercializing.

Two days of occasional programming were sufficient to make a professional-grade version of Beanslaw—an act that would have taken weeks of full-time dedication not long ago.

The app displayed smoked-meat joints on a searchable map.

It implemented sophisticated intelligence to filter out Korean barbecue, Brazilian churrasco , and other (no less delectable!) cuisines that entail barbecue of a different, bean-and-slawless variety.