The biggest misconception in the current market is treating 'AI-added' as the endgame. The vast majority of public chains' support for AI is essentially 'mounted': core computations occur in off-chain black boxes, data interactions rely on complex oracles and cross-chain bridges, and trust mechanisms are forced to be fragmented. This patchwork structure may pass muster during demos, but once faced with the large-scale commercial use of AI agents that require continuous high-frequency interactions and have long-term state memory, its performance bottlenecks and security risks are fatal.

​This is precisely the core perspective I have when examining @Vanar . Vanar's value lies not in how many AI slogans it has shouted today, but in whether it is prepared at the underlying architecture level for the future of 'AI-first' applications. When mainstream entertainment and gaming giants access Web3, they bring not just vast numbers of users, but also deep, real-time demands for AI personalized services. A truly AI-native application environment must provide extremely high concurrency processing capabilities, nearly zero interaction costs, and smooth compliance interfaces, allowing each inference, decision, and state update of the AI to occur naturally on-chain, rather than being forcibly split.

​Vanar's commitment to building frictionless, enterprise-level infrastructure is, in fact, paving the way for AI to transition from 'add-on' to 'embedded'. Under this architecture, $VANRY is no longer merely a simple payment tool, but a core resource credential that sustains the continuous operation of this highly integrated computing environment. Understanding the essential difference between AI-added and AI-first also reveals the true long-term potential of Vanar's pragmatic infrastructure approach. #vanar