Paul Graham has written a “provocative” and “controversial” piece on Great Hackers. He starts by explaining that variation in wealth isn’t a bad thing, because it points to a variation in productivity, something you only get (in large amounts) once you have complex tools to leverage:
If variation in productivity increases with technology, then the contribution of the most productive individuals will not only be disproportionately large, but will actually grow with time. When you reach the point where 90% of a group’s output is created by 1% of its members, you lose big if something (whether Viking raids, or central planning) drags their productivity down to the average.
Graham makes a number of disparate, but interesting, points. Here he slams the Java programming language in the process of making a greater point:
When you decide what infrastructure to use for a project, you’re not just making a technical decision. You’re also making a social decision, and this may be the more important of the two. For example, if your company wants to write some software, it might seem a prudent choice to write it in Java. But when you choose a language, you’re also choosing a community. The programmers you’ll be able to hire to work on a Java project won’t be as smart as the ones you could get to work on a project written in Python.
There are many disconnects between hackers and suits; here’s one huge example:
After software, the most important tool to a hacker is probably his office. Big companies think the function of office space is to express rank. But hackers use their offices for more than that: they use their office as a place to think in. And if you’re a technology company, their thoughts are your product. So making hackers work in a noisy, distracting environment is like having a paint factory where the air is full of soot.The cartoon strip Dilbert has a lot to say about cubicles, and with good reason. All the hackers I know despise them. The mere prospect of being interrupted is enough to prevent hackers from working on hard problems. If you want to get real work done in an office with cubicles, you have two options: work at home, or come in early or late or on a weekend, when no one else is there. Don’t companies realize this is a sign that something is broken? An office environment is supposed to be something you work in, not something you work despite.
Generally, it’s hard — that’s an understatement — to manage hackers. There are some tricks though:
Like a parent saying to a child, I bet you can’t clean up your whole room in ten minutes, a good manager can sometimes redefine a problem as a more interesting one. Steve Jobs seems to be particularly good at this, in part simply by having high standards. There were a lot of small, inexpensive computers before the Mac. He redefined the problem as: make one that’s beautiful. And that probably drove the developers harder than any carrot or stick could.
I know the “death of a thousand cuts” — an not from watching Hong Kong wu xia movies:
It’s pretty easy to say what kinds of problems are not interesting: those where instead of solving a few big, clear, problems, you have to solve a lot of nasty little ones. One of the worst kinds of projects is writing an interface to a piece of software that’s full of bugs. Another is when you have to customize something for an individual client’s complex and ill-defined needs. To hackers these kinds of projects are the death of a thousand cuts.The distinguishing feature of nasty little problems is that you don’t learn anything from them. Writing a compiler is interesting because it teaches you what a compiler is. But writing an interface to a buggy piece of software doesn’t teach you anything, because the bugs are random. So it’s not just fastidiousness that makes good hackers avoid nasty little problems. It’s more a question of self-preservation. Working on nasty little problems makes you stupid. Good hackers avoid it for the same reason models avoid cheeseburgers.
(Incidentally, I think this is what people mean when they talk about the “meaning of life.” On the face of it, this seems an odd idea. Life isn’t an expression; how could it have meaning? But it can have a quality that feels a lot like meaning. In a project like a compiler, you have to solve a lot of problems, but the problems all fall into a pattern, as in a signal. Whereas when the problems you have to solve are random, they seem like noise.)
How do you become a great hacker — or, at the very least, how do you avoid spoiling your hacker potential if you have it?
The key to being a good hacker may be to work on what you like. When I think about the great hackers I know, one thing they have in common is the extreme difficulty of making them work on anything they don’t want to. I don’t know if this is cause or effect; it may be both.
Great hackers are obviously smart, but there’s more to it than that. They’re also extremely curious about how things work. And they focus:
Several friends mentioned hackers’ ability to concentrate– their ability, as one put it, to “tune out everything outside their own heads.” I’ve certainly noticed this. And I’ve heard several hackers say that after drinking even half a beer they can’t program at all. So maybe hacking does require some special ability to focus. Perhaps great hackers can load a large amount of context into their head, so that when they look at a line of code, they see not just that line but the whole program around it. John McPhee wrote that Bill Bradley’s success as a basketball player was due partly to his extraordinary peripheral vision. “Perfect” eyesight means about 47 degrees of vertical peripheral vision. Bill Bradley had 70; he could see the basket when he was looking at the floor. Maybe great hackers have some similar inborn ability. (I cheat by using a very dense language, which shrinks the court.)This could explain the disconnect over cubicles. Maybe the people in charge of facilities, not having any concentration to shatter, have no idea that working in a cubicle feels to a hacker like having one’s brain in a blender. (Whereas Bill, if the rumors of autism are true, knows all too well.)
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