UC
UChicago admissions asked me to find Waldo. I did.
Hacker NewsUChicago admissions asked me to find Waldo. I did.
Share cardActual performance
149points
57comments
Made the leaderboard
Launch Intel predictions
Analyze your own launch →Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released63%63% 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, podcasting58%58% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
BetaListSuited for BetaList early-adopters · Missing: web3, chat, crypto51%51% predicted probability of success on BetaList, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal44%44% 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.
Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos26%26% predicted probability of success on Product Hunt, 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.
Correct prediction on native model
Similar products
WT
WTFDYUM: Why the f*** did you unfollow me?62%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
WTFDYUM: Why the f*** did you unfollow me?
Hacker News7Di
Did you ever stuck between two dresses?53%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Did you ever stuck between two dresses?
Hacker News1To Did List49%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Track what you did, and not your almost dids'
Indie HackersGP
GPTs killed my project, or did they?46%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
GPTs killed my project, or did they?
Hacker News1Di
Did you know you can multiply matrices without multiplication?51%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Did you know you can multiply matrices without multiplication?
Hacker News6Wh
What our Intern did in a day62%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
What our Intern did in a day
Hacker News3Ho
How Much did it Cost?62%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
How Much did it Cost?
Hacker News3I
I did a platform like Upwork but for Romania66%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
I did a platform like Upwork but for Romania
Hacker News6Lo
Loglast – Track the last time you did X47%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Loglast – Track the last time you did X
Hacker News2Di
Did – A few bash aliases to log what you worked on61%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Did – A few bash aliases to log what you worked on
Hacker News2