Let’s talk about @wardenprotocol. In the current AI Agent race where competitors are rising rapidly, Warden didn’t go for a niche vertical but instead chose a 'big and comprehensive' approach. So, how are they planning to do this? Simply put, Warden’s ambition spans across a four-layer architecture: App-Studio-Hub-Chain. From acquiring users on the consumer side, to developer tools, distribution and monetization, all the way down to foundational infrastructure—covering the entire industry chain in one go. This strategy is quite rare in the AI Agent space. Most projects either focus solely on the application layer, like @virtuals_io, or specialize in the performance of the underlying chain, like @GoKiteAI, or attempt to tackle data analysis, like @UnifaiNetwork... The biggest advantage of focusing on a niche vertical is that it’s easier to get stuck. For example, after the last wave of AI Agent hype cooled down, Virtuals was easily hit by the backlash of short-term trends. This might be the underlying logic behind Warden’s choice of a full-stack approach: 1) Strong anti-cycle capability: If the application layer doesn’t work out, the developer tools can still serve builders. If on-chain transaction volume drops, the Studio layer can still accumulate technical expertise. This multi-point support architecture is more resilient than single-point breakthroughs. 2) Data closed-loop and synergy: User behavior data from the App layer can feed back into optimizing Studio tools, while distribution data from the Hub can guide performance tuning at the Chain layer. Once this vertical integration is fully operational, it becomes very difficult for competitors to replicate. Of course, the full-stack approach isn’t a cure-all—it comes with obvious challenges. Aside from stretching the battle lines too thin, team focus, funding, and community attention can also get diluted. It’s easy for the ecosystem to suffer from the 'weakest link' effect. But on the flip side, if one product in the chain stands out, it can drive synchronized growth across other modules. So, it’s clear that Warden is currently focusing on the BetFlix product. Although the prediction market space is already highly competitive, with @Polymarket and @Kalshi taking up most of the traffic, prediction markets are undoubtedly one of the biggest application scenarios for AI Agents to showcase their value. Think about it: prediction markets powered by AI Agents can solve multiple pain points of traditional prediction markets, such as information asymmetry and high-frequency trading experiences. Agents can fetch real-time on-chain and off-chain data, analyze social media sentiment, and then automatically execute trading strategies. If Warden can further integrate deeply with the x402 protocol to enable native payment capabilities for AI Agents, the story of breaking through in the prediction market space would be even more complete.