What can be done with a LiveCode, modern-day HyperCard, and a pledge

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Hello, I came here to show some cool stuff that I made with LiveCode, an HyperCard on steroids, and why I think it makes a great programming language for both beginners and seasoned developers alike. In the end, I make a pledge for the readers to help the kickstarter to make LiveCode an open source language in the terms of the GPL. There are only about 24h left and we're almost there but we need help. My little article is at: http://files.andregarzia.com/pledge.html The KS campaign is at: http://www.kickstarter.com/projects/1755283828/open-source-edition-of-livecode Thanks in advance for all the help making a wonderful tool open source and free!

Visit product View on Hacker NewsFeb 26, 2013

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

79%79% predicted probability of success on Indie Hackers, 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: open source, io · Missing: https docs, excited, just released

74%74% 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: code, open · Missing: mac, agents, macos

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

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

40%40% 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

19%19% 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

12%12% 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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