Web3 Blind

Hacker News

Web3 Blind

Not sure if anyone already made similar things like this made before because it's very simple to implement. I guess the hard part is finding people to actually using it, and that's why I'm posting here just to throw the idea out. If we have Blind to shit posting/show appreciation about companies we've worked before, then given all those web3 communities and NFT dramas there should also be a Web3 Blind that allow people to publicly check the vibe of a token-gated group given a token address (either ERC20 or NFT token on ethreum). You can only shit posting/show appreciation if you have at least one token of the community, but everyone is able to review the vibe board to see what's going on in the community no matter if they hold a token or not. Right now it still requires a web2 login (ofc all login info salted and hashed) because I'm reusing the data structure of the web2 version.

Visit product View on Hacker NewsMay 11, 2023

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Actual performance

2points

Did not reach leaderboard

Launch Intel predictions

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

56%56% 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.

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

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

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

33%33% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

32%32% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

29%29% 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

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: web3 · Missing: chat, crypto, cryptocurrency

3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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