Menu

1 / 3

I Trained an LLM on 75K of My Own Messages So It Would Stop Writing Like a Chatbot

DEV Community·Nic Lydon·6 months ago
#ocXlKWwF
#training#ai#machinelearning#model#voice
Reading 0:00
15s threshold

Frontier LLMs are good at figuring out what to say. They're bad at saying it the way you would.

I've spent months using Claude and GPT-4o to draft content for a personal publishing system. The system prompt is detailed: first person, short sentences mixed with long ones, no LinkedIn buzzwords, lead with specifics. The drafts come back structurally correct every time. And they sound like a talented intern who studied my writing for an afternoon.

Here's what a prompted frontier model produces when asked to write in my voice:

By maintaining complete control over the hardware infrastructure, I eliminate the need to navigate third-party terms of service entirely.

Here's what I actually write:

The data lives on hardware I control. There's no terms of service to read because there's no service.

Same idea. One sounds like me. The other sounds like a model following instructions about how I sound.

Prompt engineering has a ceiling for voice matching.…

Continue reading — create a free account

Join HashtagPLUS to read full articles, follow hashtags, vote, and join the conversation.