Personal Focus Management

Hacker News

I found, after age 40-ish, that my ability to maintain focus on a single goal over long periods had diminished substantially. So, I made a small tool to help me manage focus. The link ( https://github.com/lelanthran/frame/blob/master/docs/FrameIn... ) is to a slideshow of how the tool works. Because how it works is different enough to all the other personal time/issue/task tracker tools that I had used, I recommend reading the slideshow (5-10m reading) before trying it. I've been using it for a while now; so far it works very well for me . I hope it works very well for you, too.

Visit product View on Hacker NewsMay 15, 2023

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5points

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Launch Intel predictions

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TrustMRRFits verified-revenue profile · Strong signals: personal · Missing: mobile apps, ios, entrepreneurs

62%62% predicted probability of success on TrustMRR, 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: single, using · Missing: mac, agents, macos

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

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

53%53% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

37%37% 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

30%30% 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

12%12% 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.

Correct prediction on native model

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