Id

IdeaKache – Ideas Worth Holding Onto

Hacker News

IdeaKache – Ideas Worth Holding Onto

Explore 2,410 ideas from many of the world's leading thinkers. Start with Jeff Bezos or let IdeaKache pick for you by clicking "Crack open a Kache Surprise". I've spent 9 years collecting ideas from books, podcasts, X and corners of the internet. Each entry taught me something. All entries are sourced so you can refer back to the original. I've checked every one of them. Some entries are behind a simple login (which is free) to protect against agents and bots. Let me know what you think. Jeremy

Visit product View on Hacker NewsAug 27, 2026

Actual performance

4points

1comments

Did not reach leaderboard

Launch Intel predictions

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

73%73% 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: agents, agent, open · Missing: mac, macos, cursor

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

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

58%58% 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

38%38% 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

34%34% 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

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

4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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