Me

Mental Models flash cards

Hacker News

Mental Models flash cards

I've been wanting to spend time studying mental models and then I saw a comment on HN that recommended https://www.farnamstreetblog.com/mental-models/ I decided to turn their post into "Flash Cards" so I can study a few each day. It's a PWA, so you can save it to your phone's homescreen and use it offline. Full credit for the content goes to Farnam Street. Some of it is a bit confusing out of context, so I'll probably clean it up as I go. Find the app here: https://mentalmodels.co

Visit product View on Hacker NewsDec 30, 2017

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3points

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

69%69% 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.

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

52%52% 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, intuitive

48%48% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

45%45% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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36%36% 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

22%22% 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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