ActiveDock:Improved dock for MacOS

Hacker News

Are you satisfied with the features Apple Dock provides? Me not.... I created ActiveDock because the Mac Dock does not have the ability to switch between windows, change the appearance, and conveniently group elements, and does not allow you to hide unused items. Main Features - Window Previews Panel - allows you to view and switch between windows, as well as resize and move your windows - Themes - Groups and Folder Views - for convenient grouping of items - Start button to quickly launch applications and open folders - and much more I want to simplify the application and plan to rewrite 70-80% of the code in order to simplify the application and make it more intuitive. Let me know what do you think. I will be grateful for your feedback and advice.

Visit product View on Hacker NewsJul 17, 2018

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Actual performance

2points

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

88%88% 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: created · Missing: supports, reddit linkedin, podcasting

75%75% 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

49%49% 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

35%35% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: intuitive, reviews · Missing: plus, platform, host

34%34% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: active · Missing: arr, mrr, revenue

13%13% 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.

Correct prediction on native model

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