Cursor AI intro demos (Open Source)

Hacker News

While Cursor is picking off and a lot of developers trying it out. I believe that a vast amount of beginners still struggle with a lot of basics and how to use the app. So I have compiled a few demos from the docs, and X tweets, and recorded a few myself so beginners can see how the cursor works. The website is open source, and my first time contributing, so if there are any mistakes or improvements to be made please let me know! thanks :)

Visit product View on Hacker NewsFeb 18, 2025

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Actual performance

5points

Did not reach leaderboard

Launch Intel predictions

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

97%97% 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: mistakes · Missing: supports, reddit linkedin, podcasting

71%71% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: open source · 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.

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

47%47% 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

18%18% 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

17%17% 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

13%13% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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