Unblocked To-Do List for iOS and macOS

Hacker News

Inbox Zero is a system where your inbox is for things you need to do right now. Everything else gets moved to later and you clear your inbox everyday. The Gmail snooze button is really good for this. This strategy helps me to get things done but what I really need is an inbox zero to-do list app. iPhone reminders doesn't work this way; you can only move items by giving them a due date and this splits all your to-dos into ‘today’ and ‘all.’ The today view has a couple of issues: If a snoozed item is now ‘today,’ and you don't do it immediately, it becomes overdue. All the red text is super anxiety inducing and it makes me never wanna open the app ever again. Secondly, if I ever forget to set a due date on an item, it will never shows up in the today view. I'll forget to do it all together. It really feels like organizing your iPhone Reminder app becomes a chore in and of itself. So for week 11 of building one app every week I decided to build Unblocked. It's a to-do list app that only shows you the items that you're unblocked on right now. Everything else can be snoozed with one tap. It synchronizes with Apple Reminders so you have all your to-dos on both your Mac and iPhone and it syncs in real time.

Visit product View on Hacker NewsOct 15, 2024

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Actual performance

3points

Did not reach leaderboard

Launch Intel predictions

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

90%90% 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 · Strong signals: ios · Missing: supports, reddit linkedin, podcasting

84%84% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

56%56% predicted probability of success on TrustMRR, 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

48%48% 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

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

22%22% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: real time · 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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