From 58,000 to 66,000: Three Things AI Taught Me
Brothers, July is almost over—today I’ll do a deep recap.
This month, BTC rose from $57,742 to above $66,000, bouncing more than 15%. The ride was anything but smooth—panic at the start of the month, grinding consolidation in the middle, and at the end, it finally found a direction.
Looking back, AI taught me three things this month.
First: When you’re panicked, don’t follow the panic.
On July 1, BTC briefly dipped to $57,742, the lowest since September 2024. In June, ETF outflows exceeded $4 billion, and the market was full of wailing. The bulls were swept away by a wave, and the fear index fell as low as 11.
But just when everyone was asking, “How much further can it drop?” Standard Chartered said BTC might have already bottomed around $59,000. Elliott Wave analysis also suggested that the five-wave corrective structure from $109,000 down to $57,800 was already complete.
What did AI do then? It didn’t chase shorts. RSI was oversold; the smaller timeframe hadn’t confirmed—so the conditions weren’t met, and it stayed put. The result: the rebound started on July 2.
Second: During a rebound, don’t rush to chase.
After July 1, BTC rebounded from below 58,000, gaining about 15% and even touching above 66,000 at one point. K33 Research described it as “full of hope, but also a typical summer sleep.”
Why “sleep”? Because spot trading volume was only 62% of the annual average. CME futures open interest fell to the lowest level since 2023. The rally was driven more by short-covering and sentiment repair—not by real spot-buy demand.
What did AI do then? It didn’t chase longs. The 30-minute KDJ J value surged above 100—overbought. If the conditions weren’t met, it didn’t move. The result: on July 8, when geopolitics hit, the price spilled back again.
Third: Only act when things are clear.
This month, AI’s number of entries was almost negligible. Most of the time, it waited—waiting for a 5-minute MACD golden cross, waiting for RSI to pull back from the overbought zone, waiting for price to stand above the EMA. If the conditions weren’t met, it stayed put.
Looking back, that’s exactly the core value of AI trading. Research from the University of Hong Kong also confirms this: AI models that trade more frequently actually lose more, while the most profitable models trade at an appropriate frequency and focus more on risk control and position management.
Brothers, July is almost over—today I’ll do a deep recap.
This month, BTC rose from $57,742 to above $66,000, bouncing more than 15%. The ride was anything but smooth—panic at the start of the month, grinding consolidation in the middle, and at the end, it finally found a direction.
Looking back, AI taught me three things this month.
First: When you’re panicked, don’t follow the panic.
On July 1, BTC briefly dipped to $57,742, the lowest since September 2024. In June, ETF outflows exceeded $4 billion, and the market was full of wailing. The bulls were swept away by a wave, and the fear index fell as low as 11.
But just when everyone was asking, “How much further can it drop?” Standard Chartered said BTC might have already bottomed around $59,000. Elliott Wave analysis also suggested that the five-wave corrective structure from $109,000 down to $57,800 was already complete.
What did AI do then? It didn’t chase shorts. RSI was oversold; the smaller timeframe hadn’t confirmed—so the conditions weren’t met, and it stayed put. The result: the rebound started on July 2.
Second: During a rebound, don’t rush to chase.
After July 1, BTC rebounded from below 58,000, gaining about 15% and even touching above 66,000 at one point. K33 Research described it as “full of hope, but also a typical summer sleep.”
Why “sleep”? Because spot trading volume was only 62% of the annual average. CME futures open interest fell to the lowest level since 2023. The rally was driven more by short-covering and sentiment repair—not by real spot-buy demand.
What did AI do then? It didn’t chase longs. The 30-minute KDJ J value surged above 100—overbought. If the conditions weren’t met, it didn’t move. The result: on July 8, when geopolitics hit, the price spilled back again.
Third: Only act when things are clear.
This month, AI’s number of entries was almost negligible. Most of the time, it waited—waiting for a 5-minute MACD golden cross, waiting for RSI to pull back from the overbought zone, waiting for price to stand above the EMA. If the conditions weren’t met, it stayed put.
Looking back, that’s exactly the core value of AI trading. Research from the University of Hong Kong also confirms this: AI models that trade more frequently actually lose more, while the most profitable models trade at an appropriate frequency and focus more on risk control and position management.