BlockNote – a “Notion-style” block-based text editor

Hacker News

Hi HN! BlockNote (demo @ https://blocknote-main.vercel.app ) is my shot at creating an extensible, block-based editor (similar to Notion, Coda, etc.). Featuring different block types, animations (try changing block types, indenting, etc), menus, placeholders, collaboration and more you expect from a good editor. I'm on a journey to build a decentralized, live-programmeable and collaborative block-based editor [1] that syncs over Matrix [2], and unfortunately found that there's still not a great Open Source text editor component on par with something Notion's editor, which is why I got started with this. BlockNote builds on top of Prosemirror [3] and TipTap [4] (two great libraries to build text editors for the web / work with ContentEditable and its quirks), but these libraries are pretty bare-bones ("headless"). While there's still some ground to cover, I hope BlockNote makes it easier to get a better out-of-the-box UX and am looking forward to your feedback! [1] Follow along at https://www.typecell.org [2] See this HackerNews discussion on Matrix-CRDT: https://news.ycombinator.com/item?id=29978659 [3] https://prosemirror.net/ [4] https://tiptap.dev/

Visit product View on Hacker NewsSep 8, 2022

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

76%76% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Product HuntOn track for Day 1 leaderboard · Strong signals: new, open · Missing: mac, agents, macos

72%72% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

58%58% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Missing: mobile apps, ios, personal

55%55% 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

39%39% 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

22%22% 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.

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