Try dsu gem as featured in RubyWeekly

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As featured in RubyWeekly https://rubyweekly.com/issues/687 dsu is a ruby gem that enables anyone practicing Agile methodology to record, keep track of and manage their daily standup (DSU) activities. Give it a download and a GitHub star. Lots of fun to use :) RubyGems: https://rubygems.org/gems/dsu GitHub wiki: https://github.com/gangelo/dsu/wiki - dsu uses no network connections whatsoever. - dsu stores all of its data locally, in .json files. - dsu is a simple (but powerful) command-line tool for users who love to work within the terminal. - dsu versioning follows the semantic versioning standard (MAJOR.MINOR.PATCH).

Visit product View on Hacker NewsJan 28, 2024

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

86%86% 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 · Strong signals: io · Missing: https docs, excited, just released

50%50% 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

38%38% 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

22%22% 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

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

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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