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AudioPrank – Trigger remote farts and noises via WebRTC

Hacker News

AudioPrank – Trigger remote farts and noises via WebRTC

Hi HN! My son and I built AudioPrank to have some fun with real-time sound effects. It uses netlib (a free WebRTC signaling service I helped create at Poki) so that everything runs in the browser—no extra backend or sign-ups needed. How it works: 1. Open AudioPrank and start a room. 2. On another device, open the site and join the room. 3. Trigger farts, animal sounds, or creepy noises instantly from one device to the other. Backstory: Backstory: Poki built netlib as a lightweight, free-to-use WebRTC signaling layer for game developers. I personally wanted a playful way to demonstrate its possibilities. My son suggested making a prank site and this is what we came up with. Feedback or ideas are welcome, thanks for checking it out!

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Actual performance

2points
Did not reach leaderboard

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
80%80% 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: open · Missing: mac, agents, macos
63%63% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · 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.
TrustMRRLess likely to generate early MRR · Strong signals: personal, way · Missing: mobile apps, ios, entrepreneurs
47%47% 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
35%35% 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
14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: audio · 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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