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Issues with the 'Tone' settings not carrying through an entire generated section.

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(@diego_h)
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Joined: 4 months ago
Posts: 142
Topic starter   [#22405]

I’m testing Sudowrite for a project and noticed something inconsistent with the Tone settings. I set a specific tone (like “Professional”) for a section, but the generated text seems to drift back to a more neutral or default voice partway through.

Has anyone else run into this? I’m trying to understand if it’s a limitation in how the AI handles longer requests, or if there’s a specific way to lock the tone for an entire chapter or scene.


Still learning.


   
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(@avab)
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Joined: 2 weeks ago
Posts: 72
 

I see a lot of praise for features like this, but you're hitting the exact limitation. It's not a "longer request" issue, it's a fundamental one: these settings are just prompts added to the start of your query. The AI's attention drifts, and it forgets the initial instruction.

The promised "lock" on tone doesn't really exist for extended generation. You have to keep reminding it. Try re-specifying the tone every 200-300 words, or better yet, don't rely on a single, long generation for cohesive work.


Question everything


   
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(@heidir33)
Trusted Member
Joined: 2 weeks ago
Posts: 65
 

I completely agree about the attention drift being a fundamental issue. It reminds me of something I've seen in email automation platforms - where a segmentation rule set at the start of a workflow can get overridden by later actions if you're not careful.

You mentioned re-specifying the tone every 200-300 words. I'm curious, from your experience, does breaking the work into smaller chunks and then stitching it together later actually maintain the cohesive feel, or does it end up creating noticeable seams between sections? I worry the transitions would feel jarring.



   
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(@emilyk22)
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Joined: 2 weeks ago
Posts: 134
 

Yes, I've experienced that exact drift with Sudowrite's tone settings. You've identified the core problem: it's not a true lock. The "Professional" setting acts more like a strong initial nudge rather than a sustained command.

I've found the drift is worse when the generated section introduces new characters or shifts to descriptive action, as if the model prioritizes those content cues over the background tone instruction. It's less about the raw word count and more about contextual shifts within your request.

Breaking into smaller chunks is the only reliable method I use, but it requires you to manually re-apply the tone for each new generation. There's no native feature for persistence across a full chapter yet.


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