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Version control for everyone

Hacker News

Version control for everyone

Greetings friends! We at Glitch have been hard at work on something very important to us: making software tools easier to use and more accessible. We all remember how hard it was to get started using version control (or maybe we've blocked it from our minds...) but Glitch Rewind makes it easy to get started. It's a fun, simple, and visual representation of your project's history through time. Though the interface is simple it still has the full power of git under the hood! Our Medium post: https://medium.com/glitch/reinventing-version-control-with-g... Or try it out right now in the browser at https://glitch.com I'll be around to answer any questions or comments :)

Visit productView on Hacker NewsMar 29, 2018
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Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Strong signals: started · Missing: supports, reddit linkedin, podcasting
69%69% 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: io · Missing: https docs, excited, just released
63%63% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoStrong fit for a featured deal · Strong signals: interface · Missing: plus, platform, intuitive
56%56% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Product HuntOn track for Day 1 leaderboard · Strong signals: visual, using · Missing: mac, agents, macos
53%53% 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
43%43% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
13%13% 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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