Four months ago I published a claim with weak evidence behind it: that how easy a language is for an AI to write correctly depends on the language's design, not on which model you throw at it. The evidence at the time was one toy language that passed all 8 of my test problems — but took 3x longer than Ruby to get there. My working theory was that the gap was just a training-data problem. Put more of this language's code on the internet, and the model would eventually catch up on its own.
That didn't happen. There's barely more Almide code on the public internet today than there was four months ago. And Claude's current models now solve all 20 of my test problems on the first or second try — faster, and in fewer lines, than mature languages with a decade of training data behind them.
Here's what actually changed instead.
The one metric everything answers to
Almide is a language designed to be written by AI agents, and for the last 4.5 months I've barely touched its compiler's source myself. The commit log's Co-Authored-By: Claude trailers tell that story better than I can.
