Mr. Xiaolong's Trading Review Room ——How do I train the "Monster Coin Trading System AI Decision System"? These days, I am doing something very valuable and interesting: having the Yaocoin AI review some classic big Yaocoins and summarize their patterns, and then update and evolve them. I asked the demon coin AI to help me predict and analyze the demon coin market, while also feeding my trading experience accumulated from reviewing TUT, LAB, M, SKYAI and other major demon coins to the AI bit by bit, so that it can review and learn to recognize the lifecycle of demon coins. A truly valuable AI decision-making system is not one that tells you whether to rise or fall tomorrow, but rather one that can extract replicable patterns and commonalities by reviewing a large number of representative historical market trends of demonic coins. This training task is quite time-consuming and labor-intensive, as excellent AI decision-making systems are not born, but are trained and perfected through human-machine integration. Recently reviewing TUT, I also found a phenomenon worth recording: After the first sharp drop of demonic coins, there is often a oversold rebound. After rebounding to around 0.236 or 0.382, if unable to re-enter the main uptrend structure, it is likely to enter a sustained bearish trend or even another sharp decline later on. TUT is a typical case. After the main uptrend peaked, it plummeted from around 0.337 to around 0.11, followed by an oversold rebound, rebounding to around 0.25-0.26, which is the 0.236 area, and then the rebound ended, entering a sustained decline. Why? After the first wave of sharp decline, the previously trapped chasing funds finally saw a rebound. Finally recouping the cost "and" Run away with less loss "- these chips will be released when they rebound to a critical position. So, sometimes 0.236/0.382 is not the starting point for a reversal, but may become a position for trapped stocks to escape and for bears to seek opportunities again. And LAB gave me another answer. LAB went from a long-term sideways trend with a large volume breakthrough, to a crazy main rise, and then to a high level with repeated oscillations, finally falling below the oscillation range and experiencing a waterfall collapse. This indicates that: When demonic coins are truly dangerous, it may not necessarily be when the first big bearish candlestick appears, but rather when the high has repeatedly fluctuated and each rebound has become weaker, yet the market continues to have the illusion of "still rising". Especially in cases like LAB, if supply side risks such as token unlocking are added, the sharp decline may escalate from a technical correction to a true liquidity collapse. And SKYAI has shown me a completely different side: The rapid drop in penetration after a breakthrough does not necessarily mean reaching the top, sometimes it may actually be a wash up. After a long-term sideways breakout, SKYAI experienced a very intense downward trend, but the price regained its breakthrough zone before entering the true main uptrend. So now when I train my Monster Coin AI, I increasingly don't want it to only remember: A sharp drop=reaching the top I want it to learn to distinguish: Is the sharp drop after the breakthrough a wash up or a peak? Is the high-level pin distributed or oscillating normally? Oversold rebound, is it a reversal or a escape? Horizontal market, is it fundraising or top distribution? Breaking below support, is it a normal pullback or a lifecycle switch? This is what I really want to train. Putting these cases together, I found something increasingly clear: Demon coins do not rise in a straight line, nor do they end up falling once. It's more like a constantly looping lifecycle. Horizontal accumulation → volume breakthrough → consolidation → main uptrend → high-level distribution → sharp decline → oversold rebound → further decline → bottom suction → new cycle. Of course, this is not a 100% fixed path. What AI really needs to learn is not to memorize this path, but to learn to recognize which stage the current market is in. So, what I am doing now is essentially not just about making AI "recognize demon coins". We also need to train it: Searching for patterns from historical cases → validating patterns with data → identifying similar structures → determining the current stage → and finally forming transaction decisions. This may be what I understand: AI assisted trading is not about making decisions for you, but about turning your trading experience into a system that can continuously learn, review, and iterate. There is no standard answer for demon coins. But I believe that as long as there are enough cases for review, the pattern will become clearer and clearer. I am still continuing to train this' Monster Coin Trading System AI '. TUT, LAB, M, SKYAI... What will the next case tell us? The process of training the demon coin AI decision-making system, please watch the video below for demonstration