Domain‑specific dev tools beat general ones because the latter never saw "domain" data.
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 idea sounds interesting enough. But, with SOOO much AI slop going all around in-the name of AI coding, I'm really weary of anyone who claims to generate "production-ready" code.
Can y'all find another word for high-quality code, please?
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[ 3.7 ms ] story [ 26.1 ms ] threadThe 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.
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.
Can y'all find another word for high-quality code, please?
Vertical software won because GUIs were scarce. General LLMs are winning because context is abundant.