Lots of bad reasoning in this article.

So long as your feedback loop isn't slow enough to be taking you out of flow, it's fast enough. Having it be a few seconds vs a few hundred milliseconds mostly doesn't matter for a human, and will matter even less for an LLM.

On macros and DSLs, yes they're cool and even useful sometimes, but most of the software industry is working quite happily without them. And LLMs aren't going to change that because they are best when there's a lot of relevant patterns in their training data. That ends up being a far more important factor in their effectiveness than whether the language itself is token-efficient. It's much easier for an LLM to reason through how to do XYZ in Python where it already knows all the semantics and syntax than it is for it to do it in your DSL it's never seen before. To be clear, it can probably do both but will make mistakes an order of magnitude more in the DSL, and that's what will matter most for the LLM iteration time.