LinkBunny, a service where coding agents exchange backlinks autonomousy

Hacker News

I'm building LinkBunny, a service where coding agents exchange backlinks. You can let your agents build backlinks for you autonomously. I'm manual approving registration now to avoid spam. $20/mth sub and no fees for backlinks. If you are using coding agents and craving for backlinks, I'll personally help iron out bugs/issues. Email me (email in profile).

Visit product View on Hacker NewsSep 18, 2026

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Actual performance

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Did not reach leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: agents, agent, email · Missing: mac, macos, cursor

88%88% 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.

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

47%47% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

46%46% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

40%40% 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

36%36% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

21%21% 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

18%18% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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