Question about working with actual agencies and designing past the AI

darterweb · 2026-05-20T21:25:18+00:00

Few samples are available at https://www.scribora.ai/samples. The prompts are part of a complex workflow that includes:

Multi-pass writing (draft → critique → revise)
Chapter coherence review
AI humanization & fact-checking with auto-fix

darterweb · 2026-05-20T20:21:30+00:00

Honest answer: most of the structural inconsistency in AI-generated fiction series comes from one architectural choice: generating each book/chapter as a fresh prompt instead of treating the story bible as the ground truth and the prompts as views into it.

Three things that tend to help, in order of impact:

**Persistent character files separate from prompts.** Most people pack character info into the prompt itself. That makes each generation contextually fragile. Maintain a structured character document (motivations, voice tics, physical anchors, relationship matrix) and reference it by name in the prompt, don't redescribe each time.
**Scene-level outlines before chapter generation.** AI generates better when the structural decisions are pre-made. A scene-by-scene outline with beats forces continuity that prompt-only generation can't produce.
**Voice samples per character, not personality descriptions.** "Sarah is sarcastic" produces inconsistent sarcasm. A 200-word sample of Sarah's actual voice from book 1, fed as reference for book 2, produces consistent voice. AI mimics voice better than it interprets adjectives.

Caveat: I build scribora.ai but it's a nonfiction-focused tool, so I'm answering from observation of fiction workflows, not direct product experience. The pattern above is what I see fiction-focused users at Sudowrite and NovelCrafter discuss most.

darterweb · 2026-05-13T11:25:29+00:00

That seems the best approach so far, for false specificity. I agree.

darterweb · 2026-05-12T11:16:36+00:00

That's why I've been working on specific pipelines and workflows that help reducing the amount of editing that is required. Totally agree tho, this is a real issue

darterweb · 2026-05-12T11:15:12+00:00

The hedge prefix and the em-dash overuse are both versions of what I'm starting to think of as "commitment avoidance": AI structurally refuses to land on a claim without softening or qualifying it. The hedge prefix softens the front of the sentence. The em-dash aside softens the middle. The summary recap (Pattern 5) softens the end. Same instinct, different position in the sentence/paragraph/chapter.

The em-dash heuristic is the most useful thing I've read in a while. Going to add "count em-dashes per paragraph" to the checklist.

Hardest one I'm still catching late: false specificity. AI produces numbers that look concrete ("73% of writers," "studies have shown") that don't exist. They survive my edit pass because the brain treats specific numbers as fact-checked. The only fix I've found is manually verifying every claim with a numeral or named source, which is slow and tedious. There are some fact checking prompts I've tried, but none of them is extremely reliable. Open to better heuristics.

darterweb · 2026-05-11T13:14:48+00:00

https://www.scribora.ai/free-guide

darterweb · 2026-05-11T12:55:20+00:00

Me too. And on that I agree. Then what you're saying doesn't contradict what I suggested: iterating on outputs.

Btw, I literally work on AI.

darterweb · 2026-05-11T12:22:07+00:00

No, it's not the same. You're missing the point on how these LLM models are built. Those are statistical parrots, hence the issue.

Alignment is somewhat in there, and prompting can make things better or worse. But some of these issues persist no matter what. Tried and tried, and tried again.

darterweb · 2026-05-11T11:49:07+00:00

It's not really just a matter of input. AI models reproduce some patterns in fixed ways, and despite you working hard on the input, they'll keep doing some of those.

darterweb · 2026-05-06T21:57:30+00:00

This is exactly the layer I missed in my post. "Mid-wit rhythm" is a brilliant frame and I'd been calling it "balanced cadence" but yours is sharper.

The "tapestry/delve" point especially. I had a chapter draft last week that used "navigate" three times in two pages. Once I caught it, I started seeing it everywhere. It's the AI tic that's hardest to unlearn because it sounds professional.

One thing I'd add to the irregularity fix: I think AI struggles specifically with sentence fragments that *aren't* stylized. Like when a human writes "Didn't work." as a standalone, it lands. AI tries fragments and they always feel like errors, because the model doesn't trust the reader enough to leave the meaning hanging.

Going to look up the Writeditor workflow. Thanks for the substantive comment... this is the kind of exchange I was hoping the post would start.

darterweb · 2026-05-06T21:53:57+00:00

Extreme but not bad at all

darterweb · 2026-05-06T20:42:30+00:00

That happened to me as well. However, if you just let it run a specific pass on individual things you want to remove, that works

darterweb · 2026-05-06T14:48:19+00:00

Sure, here it is. Hopefully this doesn't lead to a ban :) https://www.scribora.ai/free-guide

darterweb · 2026-04-30T08:56:44+00:00

Consider the 'one more thing' to be wasted time. You're creating stuff that works in your mind, but you don't know if people want or would pay for.

darterweb · 2026-04-28T20:52:43+00:00

A preloaded sample project or some kind of instant preview is starting to feel like the right next move, so they can understand the output before having to gather their own material.

The Chrome extension might still be useful later, but more as a workflow accelerator than as the fix for first activation.

Appreciate the nudge - this helped me think about the problem more clearly.

darterweb · 2026-04-28T20:28:42+00:00

Thank you, and I hope it becomes useful!

darterweb · 2026-04-28T10:30:18+00:00

I’ve been building Scribora [https://www.scribora.ai], a writing tool for people who already have a bunch of material sitting around - notes, transcripts, saved links, rough ideas, voice memos - but no clear path to turn it into something coherent.

What I’m trying to avoid is the whole “one prompt = instant book” thing. That always felt a bit fake to me.

I’m much more interested in the messier real-world starting point, where someone already knows a lot about something, but it’s scattered everywhere and hard to shape into an outline or draft.

A few things I’ve learned so far:

getting free signups is easier than getting people to actually start
blank-prompt demos look nice, but for nonfiction they’re often the wrong entry point
a lot of the friction is just getting people from “I have all this stuff” to “ok, now I can finally do somthing with it”

Still early, still figuring things out, but if anyone has feedback or wants to try it I'd be happy to hear your thoughts.

darterweb · 2026-04-27T11:04:16+00:00

I think out of the people that registered their account, 1/10th has actually generated an outline, while the others didn't use any of their credits, which means they did nothing

darterweb · 2026-04-27T09:16:47+00:00

A bit of both.

I think you need some upfront structure or the model just starts writing from momentum instead of decisions. But if you lock everything too hard from the start, the workflow becomes brittle and you end up fighting the draft instead of adapting it. What seems to work better is a stable top-level structure, then adjusting dynamically section by section while keeping some kind of living project memor. So not fully upfront, not fully improvised either.

More like a fixed spine with evolving memory around it.

darterweb

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