I tried it and lost 3u, I was fooled by you, I'm still too naive to trust others.
愉悦 Yuyue
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SkyAI should be the best project for grinding points in bn alpha! A friend asked me to create a tutorial for grinding alpha points during a livestream, and I just happened to see some major actions from SkyAI @SKYAIpro, so let me briefly talk about it.
👉 Recent updates and actions from SkyAI - The first good news is that the official Twitter account has finally been unfrozen! - The second good news is that the official BNB Chain has referenced SkyAI's product progress update regarding MCP, indicating official support, and perhaps there is a certain degree of collaboration between SkyAI's MCP and the official MCP. - The third and most important piece of good news is that SkyAI has currently added a large pool close to 4M USD, with a slippage of 0.01%. This is very powerful—this means that using $SkyAI to grind bn alpha points will have very low wear and tear.
👉 Simple tutorial for grinding alpha points - First is the amount: Generally, based on the current volume, it is recommended to use order numbers 1024 and 2048. I prefer whole numbers, so I would choose to buy in amounts like 1100u or 2100u. -- Note that BSC tokens have double trading volume, meaning that if you buy in amounts that meet the 1024 trading volume threshold, you can directly earn 2048 points. - The second is the target. I have always chosen $SkyAI for grinding; stability is the most important factor when grinding points. Otherwise, if you get countered while grinding, it would be unfortunate. SkyAI is currently stable around 40m, which is a very good choice. - The third is the operation. After buying 1100u in 'instant' mode, I would place a 'limit' order, with the limit price set around 1103u for the selling amount. Once placed, I would leave it alone.
Tips: 1. It's best not to grind during a downward trend; otherwise, sell orders may not be filled. 2. Only BSC coins have double trading volume incentives; SkyAI is one of the better choices. The second image is a screenshot of a community member's tweet testing wear and tear.
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