1.

1.0 launch of Nodewood, a Node.js SaaS starter kit

Hacker News

1.0 launch of Nodewood, a Node.js SaaS starter kit

Hey Hacker News! I've been working on Nodewood for a couple years now (and have submitted it before, in its beta version [1]), but have just released the first full-release 1.0 version today! Nodewood is intended to solve the issue that a lot of new SaaS founders face, that there's a whole host of features you have to have as table stakes -- user management, team management, subscription management, etc. -- and building those features yourself means you either have to cut corners or delay working on the actual business logic of your app. Nodewood comes with those features out of the box, allowing you to start building your actual app moments after you create your project. Plus, it comes with a CLI tool, a Docker-based development system, and a Pulumi-based [2] deploy option, not to mention a lot of other time-saving tools and utilities! As always, I'd love to hear any feedback! [1] https://news.ycombinator.com/item?id=26048937 [2] https://www.pulumi.com/

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2points
Did not reach leaderboard

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
67%67% 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: just released, hacker news, io · Missing: https docs, excited, exist
53%53% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Strong signals: plus, host · Missing: platform, intuitive, reviews
31%31% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: user, dock, new · Missing: mac, agents, macos
28%28% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal
27%27% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: saas, subscription · Missing: arr, mrr, revenue
18%18% 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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