To
Together in Gratitude – Share Your Thanks
Hacker NewsTogether in Gratitude – Share Your Thanks
Hey HN, We've launched an open Thanksgiving gratitude board called Together in Gratitude. No sign-up required—just click "New Post" on the top right to share your thanks. You can be anonymous or use a fun name. Let's spread some love and joy this Thanksgiving! https://www.bravoboard.xyz/board/ff83ed2a079d4615b9c0bfa58e1... P.S. Please don't flag this as spam; it's just a heartfelt project. Thanks!
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Product HuntOn track for Day 1 leaderboard · Strong signals: new, open · Missing: mac, agents, macos73%73% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting70%70% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Missing: https docs, excited, just released48%48% 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 · Missing: plus, platform, intuitive44%44% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal32%32% 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, revenue14%14% 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, crypto1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.
Correct prediction on native model
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