Nicheloom visits: 58,094 all-time · 7,637 in the last 7 days

The opportunity tracker for new startups.

Today: 1,953 launches · Niche of the day: specialized calculation tools · See what launched today →

Writekin

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

Get picks like this daily. Today's launch numbers, the top launches, AI and tech news, and a daily opportunity pick, straight to your inbox.

Want to reach these readers? Sponsor an issue.

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

HN · launched Jul 28, 2026 · 6 upvotes (top 71%) · 0 views

Niche: ai writing assistants · 186 launches, 8 in the last 7 days ▼ -64% · Explore this niche →

Category and tags

  • Horizontal
  • Content generation
  • Prosumer
  • AI-native
  • Commercial product

Visit website ↗ Source listing ↗

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 : 265 launches clear the similarity bar, closest 8 shown.

Attention rank: #225 of 266 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).

Launched 272 days after the earliest competitor.

The niche, labels, vibe code rating and competitor comparison on this page are analysis by Nicheloom. If you use them, please credit nicheloom.com. How you may use our data.