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I built an interactive course that helps you learn Vim faster

Hacker News

I built an interactive course that helps you learn Vim faster

Hey show HN! This course came about as a result of wanting a more targeted way of practicing using new vim commands I wanted to pick up, rather than just trying to use them in my regular code editing sessions. When I would try to use new commands during code editing, my productivity took a hit because I was trying to do two different things at once: thinking about code vs practicing my muscle memory. So, I made a separate environment for practicing, one that had an interactive editor, progress tracking, and achievement goals to let me see which areas I should work on, like speed and efficiency (# of keystrokes). When I realized it would be useful for beginners too, I added lessons to go along with it and this course is the result! Let me know what you guys think about it :)

Visit productView on Hacker NewsJul 9, 2022
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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: new, using, code · Missing: mac, agents, macos
85%85% 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: para · Missing: supports, reddit linkedin, podcasting
77%77% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
53%53% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRFits verified-revenue profile · Strong signals: way, para · Missing: mobile apps, ios, personal
52%52% 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
44%44% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: active · Missing: arr, mrr, revenue
20%20% 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.

Correct prediction on native model

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