The real hot take is probably this: Scalping > Swinging doesn’t mean price is fractal. It isn’t. Different timeframes = different participants with different goals. Different markets = different players entirely. Scalping works as a learning tool not because lower timeframes reflect the higher ones but because they compress feedback. You still need to know what you’re extracting. This isn’t just “head and shoulders but faster.”

Hot take Contrary to popular belief, you shouldn’t start with swing trading but scalping. Everyone starts swing trading because it feels more ‘strategic.’ But early on, you don’t need strategy; you need feedback. Scalping accelerates iterations. You don’t learn markets by holding a thesis on where Bitcoin will be in 3 months. You learn by making 50 decisions in a week and seeing what works. Scalpers can always scale up to longer timeframes. Swing traders rarely adapt down.

A system should be as simple as possible to use, but as complex as necessary to retain value. If a unit of complexity doesn’t drive a disproportionately valuable insight, output, or decision, cut it. Every added layer, rule, or feature must pay rent in the form of marginal utility. You optimize for net information efficiency.

If there are two meta-skills that unlock the door to learning just about anything, they’re these: • first principles thinking break down and reconstruct complex ideas • cognitive bias literacy ensures that this reconstruction isn’t distorted by faulty reasoning First principles thinking allows you to break down complex topics to their most fundamental elements. It helps strip away the bias that comes from personal experience. Most of us operate on assumptions built over time, and while experience is useful, it can also create mental inertia. First principles thinking forces you to pause and observe what something actually is, not just what you assume it to be. But there’s a catch: this process only works if your reasoning stays clean. Even if you’re skilled at breaking things down logically, biases can quietly sneak in and distort your understanding. So if you want your first-principles approach to actually work, you need to actively train yourself to spot and correct these distortions. When you put these two abilities together you can pick up a new domain, dissect it properly, and avoid most of the traps that lead others astray. Especially when you layer in feedback-integrated iteration, which lets you pressure-test your models. Once you’ve mapped it out you can reintroduce your experience, but this time with intention.

daily reminder BTC pumped 7x since the ECB called the “artificially induced last gasp before the crypto-asset embarks on a road to irrelevance” at the pico-shmico bottom gm

Copying strategies without knowing how they’re built is renting. You might see results, but you're leaning on borrowed logic. The moment the strategy stops working, you’re cooked. Understanding their first principles is owning. Self-reliance starts by reversing what works and tracing it back to first principles. When you own the engine, you can modify, rebuild, or invent new strategies on demand. Understanding the generative logic behind success gives you something that survives context collapse. That’s the difference between renting a strategy and owning the engine. Strategies expire. Principles don’t.

I wonder how much Aptos team paid for this tweet, quite desperate

You can go a long way with just basic trend-following principles. No need for prediction, macro analysis, or narrative weaving; you simply assume strength continues, and ride the inertia. It’s a low-assumption, high-payoff approach. The dumbest version of trend-following often outperforms the smartest attempts at timing. You just assume what’s pumping keeps pumping, until it doesn’t, and size accordingly. You don’t buy the bottom, you don’t sell the top but you capture the meat of the move. It won’t earn you social brownie points, but it’s effective.

current dynamic in one chart: world computer time

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