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Unu – canvas based pattern matching versus game

Hacker News

Unu – canvas based pattern matching versus game

A few years ago, I finished up a little game that I thought was really fun. It is a little versus game where each player needs to make a shape. I planed on submitting it to the various mobile app stores but I started a new job and life got in the way. As a fallback, I thought I would just throw the game on the web so that I could at least still share it but the game engine I used didn't support the web. I just gave Claude the source code for my game and it happily spit out a clone of my game in roughly 20 minutes. The future is wild. You can try the vibe code port here: https://benwiser.com/unu/ I wrote a quick brain dump on my blog here: https://benwiser.com/blog/Vibe-Coding-the-Port---I-gave-up-w...

Visit productView on Hacker NewsJan 26, 2026
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Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Strong signals: started · Missing: supports, reddit linkedin, podcasting
71%71% 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: claude, new, coding · Missing: mac, agents, macos
64%64% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal
44%44% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: game engine, io · Missing: https docs, excited, just released
41%41% 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
38%38% 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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