Octarine – a fast, lightweight, opinionated Markdown notes app

Hacker News

Hey HN! I’ve been building [Octarine]( https://octarine.app/ ) for a little over 2 years. It started because I wanted a note-taking app that was: - Lightweight (< 30MB, fast to launch, no Electron bloat). - Opinionated (good defaults, clean UI, not a plugin bazaar). - Yours (all plain Markdown, nothing proprietary). --- - Command bar (Cmd/Ctrl+K) to navigate and run commands quickly. - WYSIWYG editor (rich text without live preview jumping). - Git sync built-in — backups to GitHub/GitLab, no plugins. - Natural language dates (“yesterday”, “last week”). - Multiple workspaces, templates, tags, graph view. - Backup anywhere — iCloud, Dropbox, Syncthing. - Tabs & Panes — split and rearrange notes/graphs like a code editor. *Pro Features* - BYOK for over 9 AI providers including OpenAI, Anthropic, Perplexity, Gemini and more! - Ask Octarine — chat with your notes (RAG, embeddings done on-device). - Writing Assistant — Sidebar assistant to help rewrite, improve or create. - Focus Mode — distraction-free, sentence spotlight. - Customisation — 30+ fresh themes, different paper types. - Locked Notes — Disallow a note from editing. - Folder Customisations — Add icons/colors to folders, have them manage their own unique sorting. *FAQ* - Free plan gets updates forever; some features are Pro. - Pro is a one-time license (no yearly “updates tax”). - Over 130+ releases shipped. - iOS app is in development. - Overlaps with Obsidian, but follows different methodologies about having less but baked in features, over an extensible plugin system (each work for different users) --- Try it: [octarine.app]( http://octarine.app ) Changelog: [octarine.app/changelog]( https://octarine.app/changelog ) Documentation: [docs.octarine.app]( https://docs.octarine.app ) I’d love your feedback - what works, what feels off, what’s missing? Always open to ideas (and criticism).

Visit product View on Hacker NewsAug 29, 2025

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Product HuntOn track for Day 1 leaderboard · Strong signals: user, perplexity, openai · Missing: mac, agents, macos

95%95% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersFits the IH revenue-focused audience · Strong signals: started, ios, including · Missing: supports, reddit linkedin, podcasting

81%81% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: ide, io, including · Missing: https docs, excited, just released

59%59% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Strong signals: ios, users, way · Missing: mobile apps, personal, entrepreneurs

45%45% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive

31%31% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: arr · Missing: mrr, revenue, profit

23%23% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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