WWDC Together – a platform to watch and discuss WWDC with friends

Hacker News

I'm excited to launch @wwdctogether as a free place to watch and hangout during WWDC. We can now view upcoming and previous sessions via modern playback, with a chatroom for each session. Hope this provides a similar WWDC vibe during this hard time You can join at wwdctogether.com WWDC21 is just around the corner and I'm happy to bring back this year too. I've refactored the site from the ground up to have better chat experience. There's also gathering map where we can discover each other Don't watch WWDC alone, let's watch together and discuss :]

Visit product View on Hacker NewsMay 27, 2021

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Actual performance

2points

Did not reach leaderboard

Launch Intel predictions

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AppSumoStrong fit for a featured deal · Strong signals: platform · Missing: plus, intuitive, reviews

54%54% predicted probability of success on AppSumo, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos

51%51% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

48%48% 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: excited, ide, io · Missing: https docs, just released, exist

45%45% 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 · Missing: mobile apps, ios, personal

41%41% 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

15%15% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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