JadeStage [I built the platform I wish existed ]

Hacker News

Tired of opaque algorithms deciding what you watch? jadeStage flips the script. Our "algorithm" is simple: videos go in a playlist, you hit shuffle. That's it. What you get: - True random discovery - no favorites, no bias - Equal visibility for all creators - Transparent by design Built for creators tired of algorithmic curation and viewers craving genuine discovery. Mission: Innovate transparency, discovery, and equity in video streaming. Try it: Hit shuffle and discover something new. Upload your own videos and get equal visibility. Built with vanilla JS, it's an MVP focused on proving less is more. We're interested in feedback on whether this model resonates and what you would like to see in the next versions. Beta: https://jadestage.com/ Demo: https://www.youtube.com/watch?v=i1GNhu1AGJE

Visit product View on Hacker NewsDec 24, 2025

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Actual performance

4points

Did not reach leaderboard

Launch Intel predictions

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

58%58% 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.

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

55%55% 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: exist, ide, io · Missing: https docs, excited, just released

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 · Strong signals: video · Missing: mobile apps, ios, personal

42%42% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: model, new · Missing: mac, agents, macos

30%30% predicted probability of success on Product Hunt, 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 · 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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