Octarine: Private Markdown stored notes on macOS

Hacker News

Hey folks! Been working on this for a year now, and shipped a bunch of features over the last few months, since the app has come off the closed beta to available for all on Mac! Comparisons with Obsidian are unavoidable, but the app has few distinctions like: - A pure WYSIWYG editor that doesn't jerk when writing rich text. - Stored completely in markdown - Does not weigh in at 300mb, but rather just 7mb (Thanks Rust and Tauri) - Opinionated in some workflows, and makes things easier for day-to-day workflows. - Keyboard shortcuts for almost everything, and a super powerful Cmd + K bar. Still loads to do to catch up, and reach where it needs to go, but would be happy if you give it a try! Download - https://octarine.app/releases Changelog - https://octarine.app/changelog Windows/Linux versions are on the way, and are currently being tested and fixed for some issues. There's also a discord if you want to hop in for discussion.

Visit product View on Hacker NewsApr 17, 2024

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: mac, macos, notes · Missing: agents, agent, cursor

90%90% 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.

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

67%67% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

53%53% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

30%30% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

22%22% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

15%15% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

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

Incorrect prediction on native model

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