Love Ruby but meh Daily Stand-ups (DSU)? You might like my 'dsu' gem:)

Hacker News

I love ruby and rails, but agile Daily-Stand-ups (DSU) are a pain in the butt. I have a hard time remembering what to share; what I did yesterday, one-offs I did the day before because I completely forgot. So, I created this lovely little, but powerful ruby gem, called dsu. Currently, we're a small, but dedicated band of users who love the tool. You may love it also. dsu made RubyWeekly, here: https://rubyweekly.com/issues/687 Anyhow, if anyone wants to give it a try. Enjoy: Visit the dsu ruby gem wiki: https://github.com/gangelo/dsu/wiki Straight to rubygems.org: https://rubygems.org/gems/dsu

Visit product View on Hacker NewsMar 23, 2024

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Actual performance

2points

Did not reach leaderboard

Launch Intel predictions

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

78%78% 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.

AppSumoStrong fit for a featured deal · Strong signals: users · Missing: plus, platform, intuitive

53%53% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Missing: https docs, excited, just released

43%43% 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 · Strong signals: users · Missing: mobile apps, ios, personal

40%40% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: user · Missing: mac, agents, macos

31%31% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

15%15% 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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