[jmull]

It doesn't look like you addressed issues raised in the article. E.g., see the "my experiences interviewing candidates" section where we can see this isn't just a problem of the author's (just one example in one section of an article that covers various things).

I always wonder what the purpose of posting these generic, superficial defenses of a certain form of LLM-based coding is?

[Narciss]

That was a different matter altogether. I agree though that I didn't touch on that.

My experience is different in that case, but it certainly depends on the type of technical challenge, the programming language, etc.

Candidates that perform better or worse exist with and without agentic coding tools. I've had positive and negative experience on both fronts, so I'd attribute the OP's experience to the N=1 problem, and perhaps to the model's jagged intelligence.

I work mostly in Typescript, and it's well known that models are particulary well versed in it. I know that other programming languages are less supported because the training data for them is lower, in which case models could be worse with them across the board (or some SOTA models could be better than others)