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“I just wish learning magick was easy, like it used to be.”
I’ve daydreamed that a few times this month, remembering days when I just practiced communication and did healing sessions around hurt knees. Things I can do easily now. Those days were good.
Except those memories are lies. Those days were just as hard as these days. Just as exhausting. Sure, if I faced those problems today, they would be easy. But that’s only because I’ve already solved them. The first time around, they were just as hard as today.
If I try to think back to a time when magick really was easy, I can’t find it. Maybe in my teens, before I really tested my results? Maybe? But if hard days are the price of getting actual results, (and they are), I’m glad to pay it.
That longing is the urge to avoid challenges, to do what used to be hard instead of what’s currently hard. It’s anti-growth. And recognizing it for what it is helps me do the hard work today.If you liked this post, consider visiting my current blog at mikesententia.com.
Tags: Learning Magick, PersonalStory
Magick sometimes seems easier when you’re just starting out because you haven’t learned to think rigorously enough yet.
The human mind has a natural tendency to remember successes and forget failures, a fallacy that most fake psychics depend on for their livelihood. So you start out, do a whole bunch of simple stuff, and some of it works. So magick is easy, right? But then when you really start taking notes in a scientific fashion, comparing samples, and testing hypotheses, you realize that the successes you have with basic techniques come with a lot of failures – because now you’re keeping track of how many there are.
It’s a lot more challenging to put together techniques that optimize your probability shifts, but doing so is eventually rewarding. You wind up with methods that are a lot more successful on a statistical basis, and the number of failures will slowly diminish as you get better at figuring out exactly what works. I’m very happy to see you and others in the blogosphere working such methods out and publishing them, whether or not I agree with the resulting models or conclusions. I’m confident that as long as we test them as scientifically as we can and trust the data the most effective ones will prevail.