Learning about the trigger conditions for serotonin, oxytocin, dopamine, and cortisol, which allowed for more direct optimization away from cortisol activations
This idea started when I read this article I was pointed at by a coworker in 2020: The DOCS Happiness Model. I then did some naturalist studies with that framing in mind, and managed to reduce cortisol activations that I considered “unhelpful” by a significant degree. I consider this of high value to people who have enough control over their environment to meaningfully optimize against cortisol triggers.
Using method acting and other mimicry skills to more quickly learn from experts I was already trying to learn from
This was mostly learned via self-experimentation.
This is a large part of what I call my “skill stealing” skill tree, which nowadays mainly focuses on training an IFS “voice” that possesses knowledge of the skill or skill set in question. The stronger forms of these techniques tend to eat a lot of processing cycles and make it hard to maintain other parts of a “self image” while you use them, so be wary of that pitfall.
If you do want to pursue it, remember to focus on aligning as many parts of your thought process in that field to the expert’s thought process as seems appropriate instead of just becoming able to sound like them. There are a lot of layers and details to be mastered in this process, but even lesser forms can start showing value quickly.
Applying operating system architecture knowledge to my internal thinking patterns to allow more efficient multithreading and context switching
This was mostly learned via self-experimentation.
This is performed by analyzing where there seems to be bottlenecks in my personal processing speed, and then doing some tests to see if I can nudge things towards a slightly different architecture to reduce the constraint. Which changes are needed and when seems to be pretty individual-specific, but here’s some things I did:
Practice switching between commonly-used headspaces to make such transitions more reflexive (and thus cheaper in both energy and time)
Train a “scheduler” and figure out how to let it cut off trains of thought that aren’t a priority at the moment (there are many pitfalls to doing this poorly, approach carefully)
Start grouping my IFS “skillset voices” into semi-specialized “circles” I can switch between to partition which ones are “active” at different times, which saved processing resources during active calculations and reduced signal noise during queries; picture having different predefined parties to choose from in an RPG
In general, your guiding creed should be “know your constraints and know your capabilities”.
The mimicry and OS architecture applications have borne a lot of fruit over the years, but they both can take time to yield their first fruit, even if they are a good fit for your setup. The mimicry tactics are probably useful to anyone who wants to benefit from cooperative experts, but the OS tactic doesn’t seem as widely useful.
This idea started when I read this article I was pointed at by a coworker in 2020: The DOCS Happiness Model. I then did some naturalist studies with that framing in mind, and managed to reduce cortisol activations that I considered “unhelpful” by a significant degree. I consider this of high value to people who have enough control over their environment to meaningfully optimize against cortisol triggers.
This was mostly learned via self-experimentation.
This is a large part of what I call my “skill stealing” skill tree, which nowadays mainly focuses on training an IFS “voice” that possesses knowledge of the skill or skill set in question. The stronger forms of these techniques tend to eat a lot of processing cycles and make it hard to maintain other parts of a “self image” while you use them, so be wary of that pitfall.
If you do want to pursue it, remember to focus on aligning as many parts of your thought process in that field to the expert’s thought process as seems appropriate instead of just becoming able to sound like them. There are a lot of layers and details to be mastered in this process, but even lesser forms can start showing value quickly.
This was mostly learned via self-experimentation.
This is performed by analyzing where there seems to be bottlenecks in my personal processing speed, and then doing some tests to see if I can nudge things towards a slightly different architecture to reduce the constraint. Which changes are needed and when seems to be pretty individual-specific, but here’s some things I did:
Practice switching between commonly-used headspaces to make such transitions more reflexive (and thus cheaper in both energy and time)
Train a “scheduler” and figure out how to let it cut off trains of thought that aren’t a priority at the moment (there are many pitfalls to doing this poorly, approach carefully)
Start grouping my IFS “skillset voices” into semi-specialized “circles” I can switch between to partition which ones are “active” at different times, which saved processing resources during active calculations and reduced signal noise during queries; picture having different predefined parties to choose from in an RPG
In general, your guiding creed should be “know your constraints and know your capabilities”.
The mimicry and OS architecture applications have borne a lot of fruit over the years, but they both can take time to yield their first fruit, even if they are a good fit for your setup. The mimicry tactics are probably useful to anyone who wants to benefit from cooperative experts, but the OS tactic doesn’t seem as widely useful.