Training is not design. Design is the mechanism, namely a statistical method of learning distributions, and of executing those distributions computationally as an IO function.

The model is not designed to write unit tests. It is trained to do so, i.e. the distribution learned and reinforced is one such that it maps the I distribution to the O distribution that is what human beings typically do or want when writing unit tests. The design is the suite of algorithms used for this (which is ultimately global next token prediction)

I think you are conflating design (the mechanics) with their cultural or user level function.

You are basically saying "my bike isn't just rotating wheels on a frame because it takes me places". Hopefully you can see how both parts of that statement are true and why contrasting them as if the first clause is somehow false or inaccurate is incorrect.

Both these are true statements. They operate at different levels. People are constantly conflating these levels in the "is it a next token predictor" (the answer is yes) debate.