Be

Beeminder for Effective Charities

Hacker News

Beeminder for Effective Charities

Side project that'll hopefully raise some money for charities! Behavior change research shows that putting money on the line makes it much more likely that you'll stick to your habits. It's not being used much though because most people don't want to put money on the line haha We think part of the reason is that your money is traditionally going to the startups (eg Beeminder, Forefeit). We solve it by donating it to effective charities. I built it as a pretty minimal PWA to get around app stores and allow browser use. Apple makes it a bit hard to install (open in safari > share > save) but I wouldn't have done it if I would've had to go through all the app stores.

Visit product View on Hacker NewsMar 27, 2026

Actual performance

4points

Did not reach leaderboard

Launch Intel predictions

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

77%77% 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, podcasting

71%71% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released

64%64% 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 · Missing: mobile apps, ios, personal

32%32% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

31%31% 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

20%20% 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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