A Windows 98 retro voting tug-O-war system

Hacker News

Hey HN, I missed the days when i was rocking around with the windows 98 and the screen so big that took two grown men to move it. The mouse i could take the ball out and launch it at someone. So i decided to feel like a kid again but spin in some voting fun at the same time and make a little tug of war voting system. Nothing much in it at all you can vote (post a msg when voting) and then there is a forum attached to the active poll. Once the polls ends after 3 days or the kill switch is met it will archive forever along with the trollbox.exe chat and then we can review what happened in the years to come. I also wanted to get the community involved so you are able to request your own poll you want to see and people upvote once a poll ends that becomes the new poll. let me know what you think nothing special but was fun!

Visit product View on Hacker NewsAug 27, 2026

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

85%85% 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 · Missing: https docs, excited, just released

53%53% 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 HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

45%45% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

42%42% 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

39%39% 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

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: chat · Missing: web3, crypto, cryptocurrency

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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