Window Expander – Mostly maximize your windows

Hacker News

Hi HN, I developed Window Expander for my own use and decided to put it out there for free. I'm particular about how I like my desktop windows to appear. I don't like to fully maximize them because I want to see a little bit of the beautiful mountain, desert, or forest scene behind them. I found myself manually expanding them, but that's cumbersome. I run so many apps on so many VMs and I frequently switch monitors. It was time consuming. With Window Expander, I just have to click on the tray icon, select the "Resize Windows" menu item, and it takes care of everything. It's currently available for Windows and Mac and it's free. There's no signup or paid features or anything. I also have a Linux version for private use. I haven't packaged it for public consumption yet, but if you want to see it, let me know.

Visit product View on Hacker NewsJun 26, 2025

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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, apps · Missing: agents, macos, agent

81%81% 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, io · Missing: https docs, excited, just released

59%59% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

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

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

36%36% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: apps · Missing: mobile apps, ios, personal

35%35% 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

14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: paid · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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