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I Made yet Another Rick Roll Link Generator – Instant Rick Roll

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I Made yet Another Rick Roll Link Generator – Instant Rick Roll

Hey there -- thought I'd show this simple app off. I'm bad at rails/html/css/js but made a Rick Roll generator in just under a day with rails! It's kind of incredible how relevant the rick roll still is after ~15 years. Any generated Links Dynamically make opengraph tags to disguise themselves as whatever the user inputs. It's been pretty fun to see people making their own Rick Roll links. Everyone wants to make a million dollar SaaS app but making dumb little apps like this is something I might do more of! Also -- it's kind of messed up how easily you could phish someone, I've made a bunch of random links my friends would be interested in and the click through rate is very high.

Visit productView on Hacker NewsAug 25, 2022
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5points
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Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
89%89% 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: apps, user, open · Missing: mac, agents, macos
56%56% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
51%51% 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
44%44% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: apps · Missing: mobile apps, ios, personal
43%43% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: saas · Missing: arr, mrr, revenue
17%17% 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
2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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