Xmas – a 2d game developed by LLM

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I was working on this game during evenings for the last 4 weeks. It costed around 38M tokens in, and 1M tokens out (~40$), using Claude mostly (sometimes I use Gemini or GPT4o). It produced more than 10K LOC in 65 files, and refactored the code multiple times, so I can't imagine typing all that code myself. There is no chance to find energy for that after a day job, family, other things. OTOH such LLM powered development is more like laid back activity, at the same time relaxing and rewarding. Bonus links: - Example commit generated today for a "I can't play the game on touch screen, santa is not moving" prompt: https://github.com/gamedevpl/www.gamedev.pl/commit/4e0730a22... - How the development env looks like: https://github.com/gamedevpl/www.gamedev.pl/blob/master/game...

Visit product View on Hacker NewsDec 22, 2024

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Actual performance

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Launch Intel predictions

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

71%71% 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: gemini · Missing: supports, reddit linkedin, podcasting

62%62% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Missing: mobile apps, ios, personal

57%57% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

52%52% 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

43%43% 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: reward · 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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