Nicheloom

Market intelligence for builders — see what's gaining traction before it's crowded.

Writekin

fine-tune a local LLM on your own writing, on your Mac

Details

External ID
49088436
Source
HN
Company
—
Product
Writekin
Website domain
github.com
Launched
July 28, 2026
Cohort
—
Upvotes
6
Upvotes percentile
0.2873357228195938
Tags
—
Fetched at
Sept. 7, 2026, 9:26 p.m.
Updated at
Sept. 7, 2026, 9:26 p.m.

Description

Hey Hacker News!I built Writekin over the past week because I was tired of AI writing that didn't sound like me, even though I had just used AI to clean it up, rather than wholesale write it.The usual fixes I found online for this were:- Some sort of SKILL.md, or- A system prompt full of rules to strip the generic AI tells (e.g. no em-dashes, none of the stock phrases, varying the sentence length, etc).While those cleaned up the surface a bit, Pangram still came back as ~100% AI written, which was frustrating, as again it was mainly taking my sloppy copy and tweaking it.So when building Writekin I took a different route: Writekin fine-tunes a local model on your own writing. It reads what you've already written (Apple Mail, iMessage, local documents, chat exports), curates it into a training corpus, and runs a QLoRA fine-tuning on-device via Apple's MLX. A Compose screen then drafts and rewrites in that voice.Everything runs on your Mac. Ingestion, training, and generation are all local. The only network calls are:(1) When you download the model weights from Hugging Face and(2) The Sparkle update check.Training on your own Mail/Messages only felt okay to ship if the end user could verify that, so the source is public — so you can read exactly what it does!Quick gut check: It's v0.9 and the output is uneven. Honestly, sometimes it nails your voice, and sometimes it's just completely off. This is more a "this is possible and kind of works" than a finished product.Would genuinely love feedback!Source: https://github.com/scouttyg/writekin

Enrichment

Theme
ai voice dictation and transcription tools
Vertical
Horizontal
Function
Content generation
Audience
Prosumer
AI stance
AI feature
Project type
Commercial product
Normalized one-liner
fine-tune local llm on your writing
Manually corrected
False

Could you build this?

Yes A Mac wrapper executing local LoRA or QLoRA fine-tuning scripts via MLX or PyTorch and serving the result via llama.cpp is standard and easily scaffolded.

Discussion

3 comments analyzed.

Concerns raised: High hardware requirements for inference on lower-spec servers, Model size and RAM requirements unclear for different deployment scenarios

Feature requests: Support for model export/transfer to cheaper cloud servers for inference, Clarification on inference requirements vs training requirements

Competitors

Other products that read as similar to this one — 135 launches clear the similarity bar, closest 8 shown.

Attention rank: #109 of 136 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 263 days after the earliest competitor.

Other launches for this product

Same idea, different domain

Nobody's really built a content generation tool for Government yet.