I have been following the pre-sale situation of @ TheoriqAI recently, and the project is currently in the allocation review stage. I am collaborating with @ KaitoAI to screen from multiple dimensions such as on chain behavior, social performance, regional distribution, and user engagement quality. This wave of subscription quotas is clearly in short supply, and many people may end up with no quota or only receive a portion. The list of successful applicants is expected to be announced after August 5th, and the deposit for unsuccessful applicants will be refunded in the original way. But personally, I think what is more worth discussing than pre-sales is the several core modules they have pushed forward in one breath this time. The first one is the AlphaSmart system. Simply put, it is a mechanism designed specifically for "finding high-quality users for early projects". It's not the kind of whitelist that anyone can be on, but rather screening people through criteria, tasks, feedback, and ratings. This is particularly suitable for project parties who want to be a serious community and accumulate real users, and it also makes those who are willing to participate seriously more valuable. The second one is the V3.0 intelligent trading system, which has a clear logic and is a combination of "all-weather defense+active arbitrage". For example, the system can identify market traps, automatically reduce positions to protect capital in case of market fluctuations, and also perform cross chain arbitrage and automatic position adjustment to optimize returns. For ordinary users, the most practical aspect of this type of feature is that it can help you maintain a steady pace even during market fluctuations, avoiding being repeatedly harvested by the market. What Theoriq wants to do is not pure instrumental AI, it is more like building a complete "smart trading+user layering" closed loop. On one hand, the Swarm module is responsible for selecting personnel, and on the other hand, the trading system is responsible for managing money. In addition, THQ's economic model binds the two together, connecting the behavior, incentives, and risk control of participants. Speaking of tokens, the result of their collaboration with Kaito on Launchpad is also very strong, with a subscription of 78 million US dollars, nearly 40 times over raised. The key is that it is unlocked and directly usable, which is actually quite difficult in the current market environment. The rhythm of their community incentives is also very interesting, from the initial ranking points, to AlphaLocker's lock up model, to the Yap to Earn writing mechanism, layer by layer, increasing the participation density on the one hand, and on the other hand, it does make the token and actual use more tightly bound, not the kind of random task cheating reward model. Overall, @ TheoriqAI is not following the superficial narrative of pan AI, but rather verifying how AI can truly serve users and amplify the value of participants through practical and usable modules. If their ecological model can run smoothly, it may really become a paradigm sample for the next stage, especially in the current trend of "users and data quality becoming increasingly important". It is recommended to take a careful look, not just to obtain credit, but to understand what it truly wants to do. The opportunity for this cycle may be hidden in projects that are "useful, dynamic, and far fetched". TheoriqAI Kaito Yappers