Mo
Moongarlic – understand how much money you make
Hacker NewsMoongarlic – understand how much money you make
Hi, I'm hoping to get some feedback on a tool I'm working on that helps people understand compensation packages that include equity, which are often confusing. After you enter the details of your package, it will create a graph and table breaking down your annual compensation in $$$. You can also compare your existing compensation to a new job offer. The tool is free and your data isn't saved unless you sign in. What do you think? Is something like this useful?
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Did not reach leaderboard
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Product HuntOn track for Day 1 leaderboard · Strong signals: new, using · Missing: mac, agents, macos55%55% 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 NewsMay not resonate with HN audience · Strong signals: exist, existing, io · Missing: https docs, excited, just released47%47% 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 · Missing: mobile apps, ios, personal47%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, intuitive34%34% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting32%32% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue18%18% 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, crypto0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.
Correct prediction on native model
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