Tag: artificial-intelligence

AI as Writer’s Assistant: the Local Edition

Posted on Posted in ai, Dictation, Editing, LLMs, Marketing, Mel Dunay, Midjourney, Publishing Plans, Python, Weird Science, World BuildingTagged , , , , Leave a comment

Or, By The Sorceries of Python and LM Studio Combined

(Note: this is me rewriting a Claude draft post about this development. I had Claude do the initial draft inside the same chat where most of this python coding had been done).

After I wrote about my n8n automations back in February, my computer died in April, and was replaced by something newer and pinker. I resolved to do something different this time around: without API costs, without cloud dependencies, and without the kind of platform risk that bit me with Perplexity. The goal was to run my automations locally: local models, local inference, local Python scripts. No subscription fees beyond what I was already paying for Claude Pro, no data leaving my machine, no terms of service surprises. I have studied Python, but the actual coding was mostly done by Claude Sonnet 4.6. I’m not including the code itself, because your use cases may be different and your pet chatbot is probably just as good at writing python scripts as mine.

What follows is a report from the other side of that transition. TL;DR version: you can get an AI chatbot to write and troubleshoot python scripts which talk to LM Studio and do various useful support tasks for writers. Once those python scripts are finalized, you will be that much less dependent on the chatbots living out there on other people’s servers. Your “Skynet Secretary” will be living at home with you, instead of out there online. I also include some asides on how to do something similar with just a chatbot and without the python scripts and LM Studio, for people who care more about keeping things simple than keeping them local.

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So, Raptor Write…

Posted on Posted in ai, Cool Websites, Fantasy, Jane Austen, LLMs, Set in Stone, Weird Science, WritingTagged , , , , , Leave a comment

This all started when I still had my old computer, and my openrouter credits were running low, so I bought more. Then the old computer died, I decided I didn’t want to mess around with n8n again, recreating all my old automations. On the new computer I started experimenting with python+LM Studio to handle those automations, with Claude doing most of the coding. My openrouter credits were just sitting there not doing anything, so I decided to take Raptor Write, one of the cloud-based AI writing apps, for a spin. Raptor Write is a product of the Future Fiction Academy, which is probably the largest and most ambitious center of the AI first draft movement. (Not affiliated, this is not an endorsement, count your pennies before throwing money at them, etc. Any and all disclaimers may apply.) Raptor Write has a cute mascot, and is free to use except for the “bring your own API key” part. (You do need to create a Teachable account but that is also free). I had been brainstorming a very ridiculous and gothic JAFF concept set in the early 1900s with Claude, and decided generating it in Raptor Write might be a fun way to burn off some of those open router credits.

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So, Claude CoWork

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Since my last series of AI process posts, the much hyped Claude CoWork finally came to Windows. I was curious about it, so I upgraded to a Claude Pro account. I am enjoying the increased chatbot usage that comes with a Pro account. Claude, possibly, is not. Periodically it starts gently hinting that we are DONE with a particular subtopic and need to MOVE ON. As for CoWork itself, the Windows version is very glitchy. I’ve only gotten a modest amount of useful work out of it. Specifically, I wanted to go back and make clearer POV shift indicators for some of my past novels. I put the manuscripts in a subfolder of the only folder on the computer that CoWork has access to. Then I asked CoWork to review each manuscript, and write a report which quotes the first sentence after each POV shift. Here’s a couple observations:

-Opus 4.6 glitches out less often than Sonnet 4.6 does in Cowork mode, but lives up to its reputation as a usage hog. Reviewing one 50K-ish word manuscript and writing the report on it used up most of a Pro Plan usage session. I ended up running these tasks at times when my session limits had reset, and I did not expect to need Claude for a while. Late at night, early in the morning, times like that.

-Even Opus 4.6 glitches out in CoWork when asked to write fanfic. This might be a guardrail related to Anthropic’s predominantly corporate focus for CoWork. Or maybe I’m not giving it clear enough instructions. As you can see from the past “Fanficcing with Claude” posts, I tend to be pretty general in my fanficcing instructions.

-My initial feeling is that CoWork is going to be most useful for tasks too large for a chatbot and too specific to justify building a whole automation, but we’ll see how it goes.

Due Disclosure: Me and AI and Marketing

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To me, AI is a flawed but interesting tool, brought to us by the same flawed (and often corrupt) people who brought us the rest of the modern conveniences we live with. Other people have other opinions about it, and out of respect for them, I try to be transparent about my use of AI.

I do not use AI for first draft writing or for high-level concept and character background work. I have found ai chatbots (mostly Claude.ai) helpful for tasks like:

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State of the Dictator, 2025

Posted on Posted in ai, Dictation, LLMs, Uncategorized, Weird Science, WritingTagged , , , , 4 Comments

When I was talking to another writer on Discord, I realized that I tend to be somewhat vague and off-handed when I talk about my writing process, and assume people already know what I’m talking about, so I’m going to walk through the whole process here for transparency’s sake. This process includes the use of AI software for transcription and cleanup of dictated content, but it doesn’t start or end there, so if you are interested in that part, please, bear with me until I get there.

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Thoughts About LLMs, aka “AIs”

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(Note: in this piece, I link to a lot of websites that I’ve played with at different times. This is to allow the reader to make up their own minds about these things. No endorsement is intended, except of course when I am linking to my own books. If I didn’t like them, I wouldn’t publish them.)

First off, what we see today is not truly artificial intelligence, in the sense of “artificial sapient beings capable of exercising judgment and choice.” ChatGPT, Stable Diffusion and their many cousins and descendants are Large Learning Models (LLMs), software that has been programmed to extrapolate statistical information from the dataset it is given and offer randomized responses to human commands based on the dataset and the extrapolations. The results are only as good as the initial programming, and the dataset. And in terms of output, they’re only vastly more complicated versions of the random generators available at Seventh Sanctum and similar websites for more than a decade. Here are the situations in which I personally have used LLMs:

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