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Smart Mouth Billy Bass – another fishy LLM assistant

Hacker News

Smart Mouth Billy Bass – another fishy LLM assistant

Hello, HN people. This project was inspired by another very similar Show HN post from a few months ago called BillAI Bass. I decided to do something like it but take it in a different direction. It’s not a serious assistant and doesn't turn my lights on and off, but it has no cloud dependency and was fun to build. Hope you like it.

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Actual performance

2points
Did not reach leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos
75%75% 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: ide, io · Missing: https docs, excited, just released
60%60% 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
59%59% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive
59%59% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: month · Missing: mobile apps, ios, personal
55%55% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
13%13% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: smart · 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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