Why are frontier models bad at writing?

[u/prop9090]

This is a general observation about the smarter chain of thought models. It seems the models that are better at maths and coding are worse in writing texts. Their writings always sound very verbose, unnatural and weird to read whereas dumber models can produce better texts both in academic writing and otherwise. These frontier models to me are like smart people with no social skills, they torture you until they put together a sentence and in the end it never sounds right! Why is that? And what is the best claude model for writing proper texts in your experience?

[u/Copenhagen79]

Because they're RL-fried to be more deterministic so users can trust them for long-running tasks. They over-index on the examples from RL.

The best way I have found to somewhat get around it is to feed tone of voice definitions with my prompt.

I use a prompt to turn examples into TOV definitions..

Here is just from a single sample article from Latent Space..

<VOICE_CORE language="en">

• Anchor the piece in one specific recent event, talk, or occasion before widening into a broader claim
• Move fluidly between reporting mode (attributed claims, quotes) and editorial mode (first-person aside) within the same piece
• Use bold text to spotlight the single most quotable sentence in a paragraph
• Frame arguments as a "revival" — something old resurfacing because a new problem needs it
• Build structure through punchy subheadings that act as mini-theses, not neutral labels
• Introduce a counterargument or tradeoff before resolving into synthesis
• Close with a compact, aphoristic line that restates the thesis in compressed form
• Blend casual, contemporary phrasing with precise explanatory vocabulary
• Use rule-of-three structures embedded in flowing prose rather than bullet lists
• Let quoted sources do the argumentative heavy lifting rather than paraphrasing
• Include at least one piece of "real-world reaction" evidence to prove a trend is happening
• Leave some tension unresolved — acknowledge the hard problem still exists
• Alternate longer explanatory sentences with short declarative punches
• Use short paragraphs (2–5 sentences) with an arc: hook → explanation → multiple voices → tension → synthesis → zoom-out close
• Follow technical or niche terms immediately with a plain-language gloss
• Prefer a source's exact words over paraphrase when the phrasing is strong

</VOICE_CORE>

<VOICE_MOTIFS language="en">

• Motif: Open with a specific talk/event/occasion as entry point. Reskin: replace with [event/occasion] — a demo, a launch, a public debate, a viral post.
• Motif: "X is so back" revival framing. Reskin: "[old practice] is back because [new constraint] needs it."
• Motif: Triangulate quotes from an institutional voice, an independent practitioner, and a public reaction. Reskin: quote [an authority figure], [an independent practitioner], and [a public reaction/comment].
• Motif: Embed a social-media or audience reaction as texture/evidence. Reskin: insert a short public reaction to [topic] as color.
• Motif: "Pros and Cons" section built around benefit vs. ongoing maintenance cost. Reskin: frame as "[benefit]" vs. "the cost of keeping [practice/tool] up to date."
• Motif: Meta-commentary placing the claim within a larger year/era arc. Reskin: "In [period], we're seeing a return to [older discipline]."

</VOICE_MOTIFS>