A mobile app that generates mobile apps in 30 secs

Hacker News

Hi HN! Daniel from YC S21 here, launching a project called aSim ( https://asim.sh/ ), which lets people generate/simulate usable native apps (called Sims). Describe an app you want and aSim will generate it. Then, edit and refine it to better suit your needs. Sims are also shareable via links, and basic app functionality is also available through web (though mobile is much more feature complete). A couple of my favorite Sims so far: - Doom demo: https://asim.sh/@zymaric/s/18665 - Star wars idle game: https://asim.sh/@jojaspero/s/29102 - Hotdog or Not Hotdog: https://asim.sh/s/3748 - Height guesser: https://asim.sh/@dli/s/2741 - 2048: https://asim.sh/@dli/s/388 Would love feedback around the experience and additional functionality you'd like surfaced!

Visit product View on Hacker NewsDec 12, 2024

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

78%78% 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: io · Missing: https docs, excited, just released

65%65% 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 · Missing: supports, reddit linkedin, podcasting

60%60% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

58%58% 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

49%49% 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

21%21% 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

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

Correct prediction on native model

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