Based on AA, I think the most important thing to highlight is the user structure.
Whether as a tool, a channel, or a platform, each type corresponds to user groups that may not necessarily overlap, and finding the right users can lead to greater efficiency.
For instance, in a tool-based approach, no matter how many words are said, the goal is to help users place orders more easily, and there can be many types of these tools, such as settlement tools, auxiliary prediction tools, AI agents that improve success rates, or professional explainers, all fundamentally aimed at enabling users to complete transactions quickly.
Channel-based approaches are somewhat more complex, but essentially focus on digging into user populations within a specialized field. Theoretically, live streaming predictions or gambling predictions can be classified as a type of channel; this category doesn’t require deep education for users but does necessitate that users are understandable within a vertical domain.
Platform-based approaches are even more complex, requiring a composite user base. The ultimate model is a universal game, and the examples we see now, Polymarket and Kahshi, represent this model; unfortunately, platforms are the hardest to replicate.
However, in my personal opinion, even Polymarket and Kahshi may not be the final models, as both resemble centralized exchanges that lack vertical specialization and unlicensed operations, so there is still room for evolution.
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