A forum for sharing and discovering project ideas

Hacker News

It often happens that one has a brilliant idea for a project, but not the willpower and personal alignment to bring it to life. There's plenty of lists online that evidence this (for example, [1], [2], and [3]). It also often happens that when one does venture out to find ideas to pursue that would fit well with them, one finds none. Good ideas are drowned amidst the million other discussions on social media. Some ideas take too long, some don't arouse enough interest, and others are just... outdated. Hence the flood of people building things that already exist, doing things that even they themselves know won't make a real difference in the world. I've built a solution: a forum exclusively dedicated for project ideas. Share things you want to see happen in the world, discover things you actually want to do. For now, there's just some handy filters and features, with more to come as the number of ideas grows. What do you think? PS: I'm also reachable via email: ys2256[at]cornell[dot]edu [1]: https://forum.effectivealtruism.org/posts/K5R35pgPFk3DcGyRp/... [2]: https://forum.effectivealtruism.org/posts/MsNpJBzv5YhdfNHc9/... [3]: https://forum.effectivealtruism.org/posts/9AEEqDR8zcQv2XmsB/...

Visit product View on Hacker NewsJun 23, 2024

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AppSumoStrong fit for a featured deal · Strong signals: exclusive · Missing: plus, platform, intuitive

60%60% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

58%58% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

56%56% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

55%55% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: personal · Missing: mobile apps, ios, entrepreneurs

40%40% 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, revenue

14%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, 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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