A TS/PGSQL/React boilerplate to save up to 20 hours

Hacker News

I designed this product primarily for myself, and then I decided to market it at a lower price than the competitors while saving the same amount of time. I want to make it as accessible as possible and community-based with modules. I imagine offering a discount/partial refund for people developing new modules, helping others, etc. I also plan to launch a series of video tutorials soon to show beginners how to get started easily.

Visit product View on Hacker NewsJul 12, 2024

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Actual performance

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Did not reach leaderboard

Launch Intel predictions

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

84%84% 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.

Product HuntOn track for Day 1 leaderboard · Strong signals: new · Missing: mac, agents, macos

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

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

47%47% 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: video · Missing: mobile apps, ios, personal

43%43% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: soon · Missing: plus, platform, intuitive

43%43% 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

16%16% 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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