Simplistic game for iOS written in OpenGL ES 2.0

Hacker News

Hi folks, I thought I'd share my game I've been writing for the last several months. It's my first one written in OpenGL ES 2.0 so it's very basic, but I still like the outcome. It's paid so I added some promo codes at the bottom. The URL for the game is http://www.til3s.com and the game itself can be found on the App Store at http://appstore.com/til3stilesin3d. Let me know what you think! PTRFN7TTX4NJ LK3XY7AAXLWL ALLTXT3ETRK3 MTMR3NPRA7YM X9TL9NXWJR4K RMKAMFPHEAE3 NT7NJA3PFL7J F3PF7N9J9366 9H4MR6MJEFAP

Visit product View on Hacker NewsMay 29, 2014

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Actual performance

2points

2comments

Did not reach leaderboard

Launch Intel predictions

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

70%70% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRFits verified-revenue profile · Strong signals: ios, apps, month · Missing: mobile apps, personal, entrepreneurs

63%63% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

54%54% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

52%52% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

34%34% 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

19%19% 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

3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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