🧠 Case study: How to know what tokens will be on CEX Listing? A few days ago, I saw Nai Zi Ge sharing his past career experience and realized that he is actually a big shot in the industry. No wonder choosing memes is so unique. The usual humorous persona is just to bring fans closer together. This kind of experience and exposure in the CEX Listing Coin Listing Committee is not an opportunity that ordinary people can have. Then what shall I do? Just ask directly, after all, it's not very familiar, and Milk Brother Ming said this thing is not easy to teach. Perhaps they have already internalized it as a set of internal mental techniques, Dao Ke Dao, very Dao. What about conducting online research by oneself? Firstly, the workload is probably not small, and there may not be corresponding content online (after all, it belongs to core confidentiality). Can AI tools be used to implement and accelerate this process? After careful consideration, I have roughly come up with an AI speed communication process for quickly researching unknown fields: 1. Conceive the content of the question 2. Initiate questions to multiple AI tools 3. Collect answers and save them as a local markdown document 4. Upload multiple documents using NoteBookLM, ask questions twice, and organize knowledge points For example, regarding how to choose the specific coin to be listed in the CEX Listing section, I asked multiple AI experts (Claude, Grok, Gemini, ChatGPT) Q: For exchanges like CEX, such as Binance, OKX, Bybit, etc. If you are standing in the position of an exchange and need to consider whether to list a token, what are your most important considerations? Immerse yourself in the role of CEX and provide a comprehensive explanation of your own profit objectives as an exchange Then, save the responses from multiple AI as a MarkDown document, open Google's NoteBookLM, and upload the document as material. Next, you can initiate a new question in the middle Chat area. My idea is: 1. Have the AI read through all the documents and then compile a comprehensive answer 2. Let AI compare the similarities and differences between different documents, sort them in descending order based on the number of key factors mentioned, and output a table The above is a complete process for quickly conducting research on an unknown domain problem by calling multiple AI tools. Based on the collected and organized information, my takeaway from the analysis of the factors considered for the CEX Listing department's coin listing is: 1. Token liquidity and trading volume are very important 2. The core profit factor of CEX comes from token trading fees (common sense, but many times you may forget this) 3. Community heat and evaluation will be taken into consideration 4. Negative factors will be rejected with one vote (such as racial discrimination, politics, DEV Rug, contract risks, etc.) Overall, the listing of coins on various exchanges is considered core confidential and will not be easily leaked. However, from the perspective of the exchange, it can be found that "profitability" and "attracting new customers" are definitely important starting points, so the choice of how to list coins seems to have a clear pattern to follow. For example: Large trading volume, sufficient on chain trading addresses, relatively abundant liquidity, and the ability to attract newcomers to enter, etc Summary: The knowledge of AI may not be accurate, let alone know the exact answer, but the information provided by AI is enough to help us broaden our perspectives. Combined with your own common sense and judgment, you can basically have your own answer. After all, vague correctness is far better than precise error. P. Finally, please find attached two comparison tables compiled from the three answers, which can serve as a reference. Table 1: CEX Profit Factor Weight Analysis Table Table 2: CEX Listing Key Factor Weight Analysis Table