I was tricked into thinking I had “grit”

That article starts with an incorrect premise.

"America isn’t supposed to allow moats, much less reward them. Our economic system, we claim, is founded on free and fair competition."

That's called a straw man. No one has ever said America "doesn't allow moats" and that there is "free and fair competition".

The whole point of business is, within the law, to build a moat that makes it impossible for a late-starting competitor to compete with you. Patents are moats. Immense capital is a moat. Brands are moats. Regulations are moats.

When Disney pulls its movies from Netflix to start its own streaming service, it's using its moat to block a competitor.

I bet almost every dollar you spend in your life goes to companies that legally try to stop you from spending money with their competitors. From your phone to your bank to your car to your airline.

The Fed is currently propping up the price of assets through $3 Trillion of asset buying. This isn't a free economy.

>But maybe that's suboptimal in the sense that I pushed myself too hard initially, so I am fed up with that activity and don't feel like doing maintenance at all.

Yep, that's what I think. If you are oscillating for no reason you are doing it wrong. That's typically the yoyo effect people often experience when optimizing for their weight.

Humans do a really poor job at optimization in general. Quite often following a simple PID for control just make these oscillations disappear, and allow the optimization to continue instead of being stuck.

This is a simple model (quadratic), so it has its limits. Context switching shouldn't be a problem. Ideally you would have a zero cost to context switch, but if the cost is non zero, it only increase the variance but you should reach still your optimum as long as you remember that you are not just optimizing for the task at hand but for the combination.

The other limitation is when you have non-linear effects, but they are usually adverse, meaning big oscillations are more likely to result in an injury, than in an acceleration in progress. But sometimes, they can be beneficial like avoiding over-adaptation.

>Can you elaborate on this?

Which brings me to the satisficer vs maximizer point. There are often two school of thoughts when you optimize a problem that has constraints.

Once the problem become more complicated some people will assume a simplistic model and go with it, while other will try to find the best one before going with it. General-structure oriented vs detail oriented.

You can stay in the primal representation where you respect the constraints, then improve while respecting the constraints. Or you can switch to the dual where you give yourself some slack in the constraint while occurring a cost for violating the constraint that you add to the objective. You can also stay within the admissible region using some barrier method.

When you are working in the dual you are already juggling with multiple objectives.

You try to satisfy the constraints simultaneously focusing on those actively being violated, usually once all constraints are satisfied you are happy and stop maximizing even though there is still something to grab. If you want to progress further, you give yourself some additional constraints and satisfy again. Basically you are trying to land in a good-enough(TM) region of space.

The maximizer will aim for the peak. He will optimize for the sake of it. Instead of expanding the problem to a more interesting one, he will try his best to grab that extra-performance point on its limited toy problem. Once he reached the optimal point he knows that he has some slack left and only then he expands the problem to another dimension.

Sometimes he finds that deep peak inside a shallow valley, but most often he is spending a lot of energy just to make the satisficer look bad.

Measures & metrics of "grit" are, at best, not that great. It is a quality difficult to capture, and methods tend not to distinguish between projects a person chooses to undertake and those a person has no interest, believes are without value, yet is forced to undertake. I've used Duckworth's grit assessments, and not found the results to be particularly predictive of the outcomes I was trying to measure

Now, that said, "grit" is not always well understood. It's often considered a general-purpose quality. However, grit isn't necessarily about being good, or "gritty", at everything. It's much more about how you perform on something once you've chosen to do that thing. It is not about doing things that you don't believe have value to yourself.

The athlete that sleeps through class is a good example: That person didn't explicitly choose academics. Academic responsibilities were an unwanted side effect. It wasn't something the person ever really wanted.

Compare that with someone who chooses to go to college for academic reasons: Do they work hard? Stick to it? Persevere through problems? That is grit.

I schedule things. I happened to use google Calendar, but the choice is unimportant. Block out time as busy: work, commute, gym, cooking, eating, sleeping, whatever. Pick the amount of practice needed for the desired target activity. It's quite clear when you can't add something new, and it's clear from progress in things when you need to shift. Some things take less to maintain than others.

It also makes doing things you want easy, and helps build habits. "Willpower doesn't work, habits do. Motivation doesn't work, planning does." is true in my experience.

Reminds me of this (dubious) Picasso story: "It always reminds me of the story about the woman who approached Picasso in a restaurant, asked him to scribble something on a napkin, and said she would be happy to pay whatever he felt it was worth. Picasso complied and then said, “That will be $10,000.”

“But you did that in thirty seconds,” the astonished woman replied.

“No,” Picasso said. “It has taken me forty years to do that.”"

Apocryphal or not, the point of the arduous and often frustrating process hiding behind the product is relevant to any skill.