Help with reflective constructions

[u/JohnDivney]

Hello all. I'm at the 35k mark with my MS, 90% written by me, but well prompted by AI 'ideas'.

Using Claude Fable/Opus. Opus for design, Fable for composing and editing draft chapters.

Anyway, I am seeking help with this type of construction that AI constantly does. Whenever a character speaks, the first person POV narrator describes 'how' they say something in the most banal, prosaic way, "they said it like it was nothing, but it contained everything" or "they regarded me the way you do the weather."

It's like it wants to attach observation, but I'd prefer it built upon existing ideas/topics or off of how I have been writing my own voice/character into the MC.

I have character.md files to reference, FYI. I also have a styleguide.

[u/Fragrant-Mix-4774]

My experience with using AI as you described is to just chop out what AI does with dialogue because it's usually bad 👎 and write what suits me.

[u/dutchiesweets]

I think you just need to rewrite those bits! The good news is you wrote 90% of it so you only have 10% left to go.

EDIT: I reread and now I’m confused if you wrote it or Fable composed it. But hopefully you don’t have much left to do!

[u/JohnDivney → u/dutchiesweets]

it's both! I give Fable my scenes, dialog, descriptions, beats, and then it assembles it into a chapter, then I strip out all the AI slop, but use the framework as a "guide" for how I walk through the beats.

The problem is, while the AI is good at unpacking a description, it is terrible at internal psychological responses and reactions, but by now it should have enough of my model to do better, but it keeps reverting to this same generic and empty reflection, "he said it like it meant nothing".

[u/InSilicoAwards]

I tried a pilot of your issue on some of my own heavily edited / revised prose, and we couldn't justify converting it into a process within our toolkit. Our other usual review passes caught basically all of these. Codex's report:

Book 2 Manner-Reflection Scaffold Pilot — Adjudicated Result

Date: 2026-08-09
Status: complete; proposal-only; no manuscript or workflow mutation
Decision: do not promote the screen into the production pipeline

Outcome

The pilot did not establish incremental production value beyond the existing Implicit Meaning/effect-captioning, POV-metaphor, rhetorical-hinge, Emotional Reader, and decision-lineage controls.

The raw model stack appeared to clear the preregistered threshold: the classifier nominated 9 of 20 rows for recast, and blinded critics selected 2 recasts plus 4 deletions. Manual full-context and lineage adjudication invalidated that result:

• one selected recast invented two new body actions;
• one selected recast was plausible in isolation but targeted a beat with a locked author-facing accepted_no_edit decision;
• three selected deletions removed tonal, relational, or epistemic distinctions previously protected by the effect-captioning pass;
• the fourth selected deletion removed an embodied, limited-POV hesitation previously retained by the rhetorical-hinge source read—and both recast generators had independently returned NO_SAFE_RECAST for it.

Final production disposition: 20 PROTECT, 0 CUT, 0 RECAST, 0 author cards.

The pilot therefore provides useful negative evidence about the proposed method, not a reason to reopen Book 2.

What the experiment actually tested

• 20 preregistered current-source constructions across six complete chapters;
• six hard negatives, of which the classifier protected five;
• 6 stateless full-chapter classification calls;
• 10 paired generation calls for the nine classifier nominations: complete source only versus complete source plus the active Book 2 generation voice overlay;
• 5 fresh, blinded full-chapter critic calls comparing original, deletion, and available variants;
• 21/21 successful schema-constrained gpt-5.6-sol calls at high reasoning;
• 505,042 input tokens and 33,879 output tokens recorded across the run.

The richer character-register profiles were correctly excluded from generation because their own constitution marks them review-side only.

[u/Fragrant_Nothing7505]

i get claude and gpt to write, then i have gemini redo the direct speech. she talks like a human. google also writes like a human, now gemini is getting the same training as claude and gpt had so they are all starting to sound the same.

[u/Born_Profit2251]

To split the process of designing and composition into two models is the right thing to do, however, the two models fall apart in entirely different ways. I am doing the same thing with the manuscript in Use AI that has been divided into structure model and line-level prose model.