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I used to live by this philosophy when this article came out. But now I think it's a fairly imperfect model of the world that can lead you astray easily. The

I used to live by this philosophy when this article came out. But now I think it's a fairly imperfect model of the world that can lead you astray easily. The problem with it is that it's very easy to interpret that y-axis, "something good", as static. It's pretty hard to make sense of the model at all if you don't interpret as static, because your slope will bend all over the place, out of the plane, into multiple dimensions, etc. But once you've set your goal point, your "something good" axis, the natural temptation is to optimize your slope until you're steadily progressing against it. And that's dangerous, because you might forget that the "something good" axis was arbitrary to begin with. Instead, I've become much more of a fan of John Boyd's "OODA loop" [1] model. Here, you're continually reacting to your environment, which is also continually changing around you. And the person or organization that can react faster usually has an advantage, because they can set the terms of the engagement. We can call that adaptation "learning", but the key point is that it's learning an environment that is dynamic, not static. Sometimes the environment will change in a way that invalidates all of your accumulated learning, and that's okay (and you don't really get a choice about it anyway). This also drives home the point that choosing the environment you're adapting against is a pretty critical skill, and often dominates how well you adapt to it (i.e. your learning rate). I've seen some relatively mediocre people become billionaires because they picked the right industry and the right opportunity within it to join. Similarly, there are people who are brilliant problem solvers but end up in jail because the environment they are in rewards problem-solving that will get you sent there (think Omar from The Wire, or SBF from FTX). [1] https://en.wikipedia.org/wiki/OODA_loop https://en.wikipedia.org/wiki/OODA_loop

d23 4y ago
I think you’re basically making the same point he is. He even cites the environment change as an example (e.g. changing jobs).
- nostrademons 4y ago
  I think the additional point I'm making is that a 2D-graph necessarily biases your brain into ignoring the environment change, and that makes this a poor model to think about the world. Indeed, the other comment reply posted as of now still references the graph metaphor, but with S-curves instead of straight lines (which isn't really the point I was making - I'm trying to argue that your lines need to be in infinite-dimension space, regardless of their equation). You certainly can have environment change as an additional mental model you draw on when necessary - but if the quality of a model is in its ability to draw useful conclusions about the world from it, then conclusions which need to be corrected by some other model should be viewed with some suspicion.
  - unlikelytomato 4y ago
    I might agree if math analogy was being taught by a mentor as a philosophy of living. As a simple thought provoking exercise for growth of younger minds, it meets it’s goal. I think that scope is made pretty clear by his label.
Swizec 4y ago
I think you may have re-discovered the S-curve? The y-axis isn’t forever. Once you plateau, it’s time to change the definition. Then a new S-curve can begin. Over time you observe periods of quantifiable growth interspersed with discrete jumps. That said, I believe the core of y-intercept advice hides two key wisdoms: a) don’t be discouraged when you’re new, and b) don’t rest on your laurels when you’re experienced And perhaps c) if someone is both way better than you and improving faster, you’ll never catch up. This is why I never pursued competitive boxing, for example. Don’t have the talent.
- sitkack 4y ago
  If you are fan of the stack of s-curves, you will probably like this talk by Jim Keller. Jim Keller on Change https://youtu.be/gzgyksS5pX8?t=558 https://youtu.be/gzgyksS5pX8?t=558
naniwaduni 4y ago
> But once you've set your goal point, your "something good" axis, the natural temptation is to optimize your slope until you're steadily progressing against it. And that's dangerous, because you might forget that the "something good" axis was arbitrary to begin with. If you're optimizing your slope, that at least implies your slope is something you can optimize. How do you optimize your y-axis?
- nostrademons 4y ago
  That's the point - you don't. Once you're faced with something that you can't optimize because there's not even a clear definition of what "good" is, a lot of those rational tools of hill-climbing, success, continuous improvement, etc. fall out the window. And that's why it's a fun and rewarding rabbit hole to go down. Because when you're faced with an arbitrary, intractable problem, that's when you need to start developing the fuzzy, emotional side of yourself. That's when you need to start making hard choices about what you want your life to look like and what you're going to care about, and you're finally faced with a situation where there's no right answer, and you only have your feelings to go by. Then you can return to the hill-climbing and optimization as a tool to achieve those arbitrarily-chosen goals, but now you look at them only as tools.
  - rocqua 4y ago
    What if, rather than maximizing the slope, you maximize your authority over the slope. That seems closer to the original point of the article too. The general idea is that being a quick learner is universally valuable because it means you can reach a steep slope over many different dimensions. Hence allowing you to react much better.
nordsieck 4y ago
> I've become much more of a fan of John Boyd's "OODA loop" [1] model. As a side note, have you ever heard a coherent and/or useful explanation of the "orient" part? It seems like every time I hear about the OODA loop, that's the part that gets yadda-yadda-yadda'd over.
- Jtsummers 4y ago
  Synthesizing the new information (from observing) with prior information to understand the fuller picture before deciding. If you skip it, then you're, at best, just being reactive and reacting to only the present incomplete information.
  - taeric 4y ago
    This sounds hand wavy. :) My stab is specific to understanding the full picture is how you can move in it. How many movement choices do you have? Can you get back to a position? Does your moving cause others to move? Can you see places that are safe to experiment in? For prior information, look for familiar analogs. Defensive positions. Offensive outposts. Well troden paths, etc.
    - Jtsummers 4y ago
      What's hand wavy about it? It's just not concrete because the idea itself is abstract, not concrete. To orient, you have to combine information (synthesis) from your observations and your priors (what you previously observed and what you know). You can give concrete examples but then people still have to figure out the abstraction to connect one concrete example to another, and if they spend time thinking about it end up with the simple concept I described.
      - taeric 4y ago
        But that is no different than any other description I've seen. I took the question to be "what does it mean to orient to the observation?" That is, I suspect the asker wanted specific examples of what that means. I think it is fair to say that people learn in concretes, not in abstractions. Is why so few of us know what a semigroup is, after all.
cgio 4y ago
OODA looks interesting, thank you for link. I personally follow a similar model, which I am sure someone would have articulated better than I do already. Anticipate - Perceive - Act - Understand. The first two are in relation to your presence in an environment. The latter two are about your ability to be an agent in this environment. Your understanding of the world informs the things you prepare yourself to observe (e.g. the direction of your eyes when you drive, very similar to the orient in OODA I think). You perceive within the bounds of your anticipation and act according to the perception as it relates to observation (I.e. not thinking too much about it). The thinking is in the understand part where you structure the relationship of the prior and your actions and secondary post action observations. Not all the loops are completely linear, e.g. you may open a loop with an action and then close it years later in a wiser setting or when the feedback comes.
- curiousllama 4y ago
  I like your model, but I love that you put Anticipate at the front. It's a loop so doesn't really matter, but I'm entertained by the idea of "Step 1: Take a wild ass guess at what's about to happen"
HWR_14 4y ago
The problem with this concept in a competitive field is other people are likely to have a similar slope and a higher y-intercept.

d23 4y ago

I think you’re basically making the same point he is. He even cites the environment change as an example (e.g. changing jobs).

nostrademons 4y ago
I think the additional point I'm making is that a 2D-graph necessarily biases your brain into ignoring the environment change, and that makes this a poor model to think about the world. Indeed, the other comment reply posted as of now still references the graph metaphor, but with S-curves instead of straight lines (which isn't really the point I was making - I'm trying to argue that your lines need to be in infinite-dimension space, regardless of their equation). You certainly can have environment change as an additional mental model you draw on when necessary - but if the quality of a model is in its ability to draw useful conclusions about the world from it, then conclusions which need to be corrected by some other model should be viewed with some suspicion.
- unlikelytomato 4y ago
  I might agree if math analogy was being taught by a mentor as a philosophy of living. As a simple thought provoking exercise for growth of younger minds, it meets it’s goal. I think that scope is made pretty clear by his label.

Swizec 4y ago

I think you may have re-discovered the S-curve? The y-axis isn’t forever. Once you plateau, it’s time to change the definition. Then a new S-curve can begin. Over time you observe periods of quantifiable growth interspersed with discrete jumps. That said, I believe the core of y-intercept advice hides two key wisdoms: a) don’t be discouraged when you’re new, and b) don’t rest on your laurels when you’re experienced And perhaps c) if someone is both way better than you and improving faster, you’ll never catch up. This is why I never pursued competitive boxing, for example. Don’t have the talent.

sitkack 4y ago
If you are fan of the stack of s-curves, you will probably like this talk by Jim Keller. Jim Keller on Change https://youtu.be/gzgyksS5pX8?t=558 https://youtu.be/gzgyksS5pX8?t=558

naniwaduni 4y ago

> But once you've set your goal point, your "something good" axis, the natural temptation is to optimize your slope until you're steadily progressing against it. And that's dangerous, because you might forget that the "something good" axis was arbitrary to begin with. If you're optimizing your slope, that at least implies your slope is something you can optimize. How do you optimize your y-axis?

nostrademons 4y ago
That's the point - you don't. Once you're faced with something that you can't optimize because there's not even a clear definition of what "good" is, a lot of those rational tools of hill-climbing, success, continuous improvement, etc. fall out the window. And that's why it's a fun and rewarding rabbit hole to go down. Because when you're faced with an arbitrary, intractable problem, that's when you need to start developing the fuzzy, emotional side of yourself. That's when you need to start making hard choices about what you want your life to look like and what you're going to care about, and you're finally faced with a situation where there's no right answer, and you only have your feelings to go by. Then you can return to the hill-climbing and optimization as a tool to achieve those arbitrarily-chosen goals, but now you look at them only as tools.
- rocqua 4y ago
  What if, rather than maximizing the slope, you maximize your authority over the slope. That seems closer to the original point of the article too. The general idea is that being a quick learner is universally valuable because it means you can reach a steep slope over many different dimensions. Hence allowing you to react much better.

nordsieck 4y ago

> I've become much more of a fan of John Boyd's "OODA loop" [1] model. As a side note, have you ever heard a coherent and/or useful explanation of the "orient" part? It seems like every time I hear about the OODA loop, that's the part that gets yadda-yadda-yadda'd over.

Jtsummers 4y ago
Synthesizing the new information (from observing) with prior information to understand the fuller picture before deciding. If you skip it, then you're, at best, just being reactive and reacting to only the present incomplete information.
- taeric 4y ago
  This sounds hand wavy. :) My stab is specific to understanding the full picture is how you can move in it. How many movement choices do you have? Can you get back to a position? Does your moving cause others to move? Can you see places that are safe to experiment in? For prior information, look for familiar analogs. Defensive positions. Offensive outposts. Well troden paths, etc.
  - Jtsummers 4y ago
    What's hand wavy about it? It's just not concrete because the idea itself is abstract, not concrete. To orient, you have to combine information (synthesis) from your observations and your priors (what you previously observed and what you know). You can give concrete examples but then people still have to figure out the abstraction to connect one concrete example to another, and if they spend time thinking about it end up with the simple concept I described.
    - taeric 4y ago
      But that is no different than any other description I've seen. I took the question to be "what does it mean to orient to the observation?" That is, I suspect the asker wanted specific examples of what that means. I think it is fair to say that people learn in concretes, not in abstractions. Is why so few of us know what a semigroup is, after all.

cgio 4y ago

OODA looks interesting, thank you for link. I personally follow a similar model, which I am sure someone would have articulated better than I do already. Anticipate - Perceive - Act - Understand. The first two are in relation to your presence in an environment. The latter two are about your ability to be an agent in this environment. Your understanding of the world informs the things you prepare yourself to observe (e.g. the direction of your eyes when you drive, very similar to the orient in OODA I think). You perceive within the bounds of your anticipation and act according to the perception as it relates to observation (I.e. not thinking too much about it). The thinking is in the understand part where you structure the relationship of the prior and your actions and secondary post action observations. Not all the loops are completely linear, e.g. you may open a loop with an action and then close it years later in a wiser setting or when the feedback comes.

curiousllama 4y ago
I like your model, but I love that you put Anticipate at the front. It's a loop so doesn't really matter, but I'm entertained by the idea of "Step 1: Take a wild ass guess at what's about to happen"

HWR_14 4y ago

The problem with this concept in a competitive field is other people are likely to have a similar slope and a higher y-intercept.