HingeGPT – Generate mediocre Hinge opening lines

Hacker News

Hey all! Both jammygrams and I are complete failures on Hinge. With nothing to lose, we thought it would be hilarious to let GPT message for us. Write a name and prompt you want to respond to, and let HingeGPT give you some terrible pick up lines. Keep hitting generate - a lot of the generated messages are trash, but it occassionally strikes gold. Testimonials: “I matched with a guy using a HingeGPT line. Now we're engaged. Do I tell him?” - A friend, 29 “Maybe I'm in love with GPT?” - Another friend, 23 “I'm downloading Hinge to try out these lines” - Karina, 24, currently dating Arpeet, 25 (out of earshot)

Visit product View on Hacker NewsApr 9, 2023

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Actual performance

3points

Did not reach leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: using, open · Missing: mac, agents, macos

70%70% 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: io · Missing: https docs, excited, just released

53%53% 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

45%45% 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, podcasting

44%44% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

31%31% 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

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

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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