Current AI coding tools don't seem to have any real impact on true development productivity/ efficiency yet.
Apparently you cannot just one-shot everything to production. who'd have thunk? :-)
LLMs did - they soaked up the entire public Python, JS, React universe during pre‑training.
So the marginal value of a “React‑only” model is thin.
I agree that bigger wins come from better retrieval, tool feedback loops, and planning on top of a powerful general model whose weights already contain some of today’s front‑end ecosystem's spine.
The fact that you're accounting for invisible elements and accidental shadows shows deep domain expertise.
This is exactly the kind of thing general-purpose tools miss because they assume clean inputs.
I don't think a direct similarity with domain specific languages is evident to me. I rather find the messaging similar to some "agents" from other domains. e.g. https://www.harvey.ai/
The idea of an "AI agent" is to anthropomorphize. You don't call workers domain-specific humans.
It sounds like a strange choice. That's why I asked. Of course it's not related to domain specific languages.
Vertical software won because GUIs were scarce. General LLMs are winning because context is abundant.
Can y'all find another word for high-quality code, please?