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https://warpcast.com/~/channel/founders-club
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julie.base.eth ↑
@julieinweb3
Talent Protocol aggregates data from GitHub, onchain activity, and other platforms to create your Builder Score. Given that you've recently launched Builder Score V2 in February, what key improvements have you made? Looking forward, will you focus more on building new features or expanding data sources? By the way, the current design appears quite robust against manipulation, as scores are grounded in verified identities and genuine proofs of work. Could you also share your insights on how the system maintains its resilience against attempts to game the scores? @macedo 关于 Talent Protocol 的声誉系统，我觉得你们把 Builder Score 的设计做得非常扎实，用 GitHub、链上活动等等真实数据作为依据，感觉很难有人能够“刷分”或“投机取巧”。我也注意到你们在今年 2 月发布了 Builder Score V2，想问一下，这次的升级主要在哪些方面做了优化和提升呢？ 接下来你们的产品侧重点是什么？是会更专注于开发新的功能...
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Myza
@joybrishti
Builder Score V2 likely improved accuracy, identity checks, and UX. It’s hard to game thanks to real data. Looking forward to new features and more data sources. Curious what @macedo thinks!
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julie.base.eth ↑
@julieinweb3
https://app.tako.so/cast?id=0x2f8ed32b1831acdf4c7ec27b31d735f896364d10 he answered a similar question here
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