遇到 Ruby 和 Star 这么好的主持人，就偷着乐吧！真的会提问很会引导，所以忍不住多说几句，变成小话痨了 凝练下其中我非常喜欢的一个问题就是，在如此内卷的预言机行业中，是否有做一家新的预言机的必要？ 视频里我类比了Google和AOL这个非常典型的竞争案例。老牌预言机们凭借先发优势，为 DeFi ，传统金融等提供了稳定可靠的“喂价”，但当前处境像AOL一样，其原有架构在面对RWA（现实世界资产）、AI Agent、预测市场等需要处理海量非标准化、企业级复杂数据的新场景时，会有很大的局限性。 APRO 从建立伊始就没有选择在原有预言机定义的赛道上硬碰硬，而是像Google一样，进行升维攻击。我们认为新一代预言机的角色更像是数据的“理解者”和“验证者”，所以无论是从产品模式、核心理念、技术重心做的都不太一样。 我想，这也是为什么 APRO 能快速在蓝海市场中发光发热的重要原因。

With hosts as good as Ruby and Star, I can’t help but feel lucky! They ask sharp questions and guide the conversation so well that I couldn’t resist saying more than usual—turned into a bit of a chatterbox. One question I especially loved was this: in such a hyper-competitive oracle industry, is there really a need to build a new oracle? In the video, I drew a parallel to the classic Google vs. AOL case. The legacy oracle providers, thanks to first-mover advantages, have long delivered stable, reliable pricing feeds for DeFi and TradFi. But like AOL, their original architectures face major limitations when confronted with new scenarios—RWA (real-world assets), AI agents, prediction markets—where you need to handle massive volumes of non-standard, enterprise-grade complex data. From day one, APRO chose not to go head-to-head within the old, narrow definition of oracles. Instead, like Google, we’ve aimed to “attack from a higher dimension.” We believe the next generation of oracles should act more as “interpreters” and “verifiers” of data. That’s why our product model, core philosophy, and technical focus are fundamentally different. I believe this is a key reason APRO has been able to shine so quickly in a blue-ocean market.