withink.
A calm, distraction-free space for your daily thoughts
What it does
A private, encrypted journal built for clarity. One entry a day, saved offline, and exportable anytime as plain text—no trackers, no noise. Most journaling apps are bloated with complex templates and friction. withink. is a calm, minimalist space featuring a distraction-free Zen editor, seamless daily tracking, and reflection tools that strip away noise so you can focus entirely on your thoughts. Write daily. Think clearly. Stay consistent.
A private, encrypted journal. One entry a day, saved offline and exported anytime as plain text - no trackers, no noise.
A private, encrypted journal — one page a day, saved offline and exported anytime. Yours forever. withink. turns daily reflection into something you look forward to — not another app you check off. Flip back through any month — a quiet streak, a year at a glance, and the moods you lived, all on one calm screen. A warm, paper-like page with nothing else on it. No notifications, no feeds, no noise — just today’s entry. One click turns your whole journal into plain pages you can keep forever. No lock-in, ever. Live, working previews of the journaling experience — write a mood, lock your page, revisit a year. “ Had a great conversation with an old friend. It's nice to reconnect and share…from withink.me
Does the same job
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- JPJournalBook – Privacy centric, offline first, personal journal app2019 · journalbook.co.uk · ▲268
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Life & fun · 10d ago · louisabraham.github.io
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Hello HN! I found that picking out plausible but diverse skin tones for my digital art and game development projects was kind of difficult, and I got curious about if there was a way to define a color space that made it easy. I've built a color picker and procedural generation algorithm based on the space as well as a bunch of other fun js features and demos throughout the page that use the equations. If you find it interesting, I have lots of explanations of how I built it and what properties the space has. The methodology might be a bit shaky, but hopefully the result is as helpful for…
Life & fun · Aug 2026 · toneyalexander.github.io
I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
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