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Product Hunt

Evaluate, Optimize, and Ship AI Agents

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Actual performance

391upvotes
27comments
Made the leaderboard

Traction signals

Makers1

Launch Intel predictions

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BetaListSuited for BetaList early-adopters · Missing: web3, chat, crypto
87%87% predicted probability of success on BetaList, based on ML models trained on real launch data.
Product HuntOn track for Day 1 leaderboard · Strong signals: agents, agent · Missing: mac, macos, cursor
83%83% predicted probability of success on Product Hunt, 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, personal
48%48% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: lua · Missing: https docs, excited, just released
41%41% predicted probability of success on Hacker News, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
27%27% 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, revenue
25%25% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
20%20% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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