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Comment by arpa | Hacker News Reader

While very idealistic and beautiful in a way as all manifests tend to be, we (along the author) tend to forget certain truths - the middle of the gaussian curve is fattest; all natural distributions follow that curve, and developers are no exception. Most of us, by definition, are mediocre. There's nothing that can be done about it. We should not shun, but rather embrace that. Not by deluding ourselves that if we follow some idealistic manifesto we somehow rise above our limited skills and minds. We will not. We will suck. Our tech will suck. Other peoples' tech will suck. There is no ideal that can be attained. This is not the profession of saints and Buddhas. But by knowing this, by accepting this, we can start working on raising the standard for mediocracy...

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> all natural distributions follow that curve

No, they don't. Many approximate that curve. Others do not. For examples:

"Bimodal distribution of flowering time in a natural hybrid population of daylily (Hemerocallis fulva) and nightlily (Hemerocallis citrina)" - http://link.springer.com/article/10.1007%2Fs10265-005-0241-3 .

http://psychology.wikia.com/wiki/Bimodal_distribution lists other bimodal distributions: "the time between eruptions of certain geysers, the color of galaxies, the size of worker weaver ants, the age of incidence of Hodgkin's lymphoma, the speed of inactivation of the drug isoniazid in US adults, the absolute magnitude of novae, and the circadian activity patterns of those crepuscular animals that are active both in morning and evening twilight"

A large number of natural distributions follow a power-law distribution. https://en.wikipedia.org/wiki/Power_law#Examples gives many examples.

That said, you do not need that broad claim to make your argument.

I humbly sit corrected. Thanks for the links!

>A large number of natural distributions follow a power-law distribution.

This is surprisingly debatable. People like to find power-law/scale-free distributions because it implies a neat generative story, but a lot of the "evidence" for power-law distributions is pretty weak. For example, you cannot just show that a log-log plot is linear--lots of other distributions can produce similar plots.

Clauset, Shalizi, and Newman have a very readable paper where they describe 1) how to properly test for a power-law distribution, and 2) use those tests to assess the validity of some claims from the literature (spoiler: not many have "good" statistical support). Here is the paper: http://arxiv.org/abs/0706.1062 Shalizi has a short blog post describing the main results: http://bactra.org/weblog/491.html

Agreed. The old saying is "anything looks linear when plotted on a log-log graph."

However, the OP was giving a rough approximation in the first place, in saying that all natural distributions follow a Gaussian curve. But Gaussian curves go from -∞ to +∞. Many of the real-world distributions must only have positive values, like heights and weights. Although for real-world purposes, they can usually be approximated as Gaussian.

With that roughness in mind, I think it's okay to say that the Stefan–Boltzmann law, the inverse-square laws of Newtonian gravity and electrostatics, or Kleiber's law, which are all listed in the Wikipedia link are close to a power law to be acceptable counter-examples.

(Stefan–Boltzmann assumes a perfect black body, the inverse-square laws ignore relativity, and Kleiber's law is a rule-of-thumb in the first place.)

Oh sure. When there's a plausible reason for thinking something is scale-free, I'm all for it.

For a while though, it was en vogue to find power law distributions in all sorts of weird places (email response times, numbers of friends), and that's what I was attempting to object to!

Re-read the manifesto. You'll notice that its theme is not about a person's natural abilities or smarts, but self awareness. The manifesto can basically be boiled down to "show humility in your own code". Always assume that there is potential for improvement, and be ready for when that potential becomes a need.

It's about mindfulness towards our own product. "Mediocrity", in this case, is turning a blind eye towards our own limits. All people have the ability to overcome this form of mediocrity.

Couldn't agree more with this. It's something I repeat at work almost once every week. Look I'm average, most of us at work will be average. The question is how to we design our processes to take that into account? instead of constantly pointing fingers for mistakes that happened.

It'd be kind of cool if you tried to improve your skill level, too. That is something you can do.

Of course I can and I do but the wider group will still always have a Gaussian distribution of skills more or less always. (as pointed out by parent comment)

Not usually......skill tends to have an exponential distribution, not a Gaussian distribution. Not everything falls into a Gaussian distribution.

> This is not the profession of saints and Buddhas.

It's a choice, not a lifestyle.

Full enlightenment, or being a Buddha, is the realization all of this around you is Buddha Nature. Each individual is capable of attaining enlightenment in a single moment, given choice is made in very similar moments throughout the day. When you decide to believe it, you do so in a timeframe that is non-measurable. Like many people I know in SV, I believe we're running in a simulation. This belief could be viewed as equivalent to a type of enlightenment.

On the other hand, saints are beyond this reality and are "holy" in nature. Holiness means they have been re-integrated with the supreme wisdom, or all knowledge. Some call it the fucking oneness. Aldous Huxley called it the "burning brightness of unmitigated Reality". Technically, they are enlightened, but they are outside what we HERE can consider as Buddha Nature.

I liken these two concepts to security through obscurity. We don't know the proper protocols to realize that we are all the same thing and refuse to think about the fact we'll all be reintegrated into the brightness when it comes for us.

There lies a difference between Bodhisattva and Buddha. What you described while explaining the difference between Buddhas and saints is essentially the difference between Bodhisattvas and Buddhas :)

And Bodhisattva is a lifestyle by choice.

But then again, what do i know. I barely follow the eightfold path.

But surely the purpose of the manifesto is to skew that curve to the right.

Or to at least make the author feel like he is part of the right.

One might as well try to skew global IQ stats to the right. And please, don't call me shirley.

This has been happening over the last 100 years. That's why IQ tests need periodically recalibrated.

thing is, the curve remains the same. Fat in the middle.

Of course the curve will remain centered about 100, because that's how IQ is defined.

But shifted right. This is good. Praise science.

But it stopped recently, I believe

I think you just mean "shift" the curve right, as in translate; "skew" means something very specific in the context of distribution curves.

One solution comes to mind: allow only the people who are >2 sigma above the average to design the software (i.e., be architects), and to do QA.

In my experience, this usually leads to having a team of "architects" whose job it is to sit in meetings with people actually building things and tell them how to do it. I've yet to meet anyone who can do that job well. No one is good enough to reliably prescribe solutions from afar without getting their hands dirty. There will be weirdness and corner cases and overlooked details that have to be accounted for. Going back to the architect who has been doing other things for the last six months isn't likely to yield much insight in what to do about that.

I think that in pretty much all cases, you'd be better off just taking that architect and telling him to write the code. If you don't think you have enough good people to do the amount of work you need to do with that approach, you're trying to do too much work.

   >the middle of the gaussian curve is fattest; all natural distributions follow that curve

Skill-level tends to be distributed with an exponential distribution, not a gaussian distribution.

The main problem is management wanting shiny and new and not being aware of the value of paying down technical debt.

Being mediocre is a choice. It's the choice of the lazy and unemployed.

Sir, may I please look at your horse? It seems pretty high, would you step off it, please, and face the reality?

Accepting being better than some people is accepting being worse than some other people. One thing is for certain; we all aren't just as good. Who is really ignoring reality? Is it the person who thinks he has room to improve or is it the person who thinks he can't improve and has no reason to improve?

That's not what you said.

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