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A funny rap song about stereotypical tech startups

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A funny rap song about stereotypical tech startups

Song URL: https://www.youtube.com/watch?v=JjjUj1ypVmI Quick background on the project: I'm a full time programmer and I love making rap music. I see a lot of humor in the profession/industry, and thought it would be fun to combine the two. Here is what I'm planning on for next steps. I'm always open to feedback on how to get more exposure! 1. Paid ad on a popular Twitter account(s) 2. Rent a GoPro and shoot a music video for one of the existing songs (if you have any tips on recording, please let me know - I have done some music video editing but don't know much about video cameras)

Visit productView on Hacker NewsDec 11, 2018
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Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Strong signals: songs · Missing: supports, reddit linkedin, podcasting
85%85% 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.
Hacker NewsStrong engagement from HN community · Strong signals: exist, existing, ide · Missing: https docs, excited, just released
62%62% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Product HuntUnlikely to reach the leaderboard · Strong signals: open · Missing: mac, agents, macos
47%47% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: video, way · Missing: mobile apps, ios, personal
41%41% 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
38%38% 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: paid · 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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