I remade a image remixing community from 2010 (in public beta)

Hacker News

Hi all! Over the past 4 years I've been remaking the site Christopher Poole made back in 2010. It basically allows users to upload, or draw using the in-built image editor, and have your posts be remixed on-the-fly, by anyone. as the title says, it's still early in life, but I'm working on it every day. always looking for feedback! Technical Notes: It's written with Laravel, using FrankenPHP as it's backend. PHP goes REALLY fast with Caddy/go as the engine.

Visit product View on Hacker NewsMar 26, 2024

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

73%73% 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.

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

57%57% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive

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

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

42%42% 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 · Strong signals: users, way · Missing: mobile apps, ios, personal

42%42% 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

25%25% 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

0%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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