A VIM-inspired keyboard only interface for WYSIWYG rich text editor?

Hacker News

Hello, I am working on a project that you can think as Typora + Vim keybindings. Here is a demo: https://www.youtube.com/watch?v=97lAMRrAcF4&feature=youtu.be I have previously posted on reddit/r/vim here: https://www.reddit.com/r/vim/comments/a2kjx9/work_in_progress_rich_text_editing_with/ Do you think there is an audience? Do you think that it needs to be collaborative and implement branching in itself, or it is better just as an editing interface for Markdown and let Git handle branching/merging in plain text?

Visit product View on Hacker NewsDec 5, 2018

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

83%83% 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

78%78% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

49%49% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

47%47% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

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

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

19%19% 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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