I built a goal-oriented task manager

Hacker News

Hello HN! I've been working on a task manager ( https://plocs.com ) that combines a todo list with project management. Unlike most task managers, Plocs supports task dependencies and makes working with them easy. Thanks to dependencies Plocs is better in two important ways: 1.) You can plan in a goal-oriented way. Start with your goal and then plan the steps you need to get there. 2.) You can tell very easily which tasks you can work on: the ones that don't depend on other tasks are shown in a list to the left of the screen. Would love to get your feedback! PS: If you click on "Start demo" you can try it in the browser without registering. Thanks, Christian Staudenmeyer

Visit product View on Hacker NewsNov 17, 2022

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

92%92% 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: tasks, project management · Missing: mac, agents, macos

79%79% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

54%54% 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 · Strong signals: way · Missing: mobile apps, ios, personal

47%47% 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

45%45% 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

15%15% 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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