pookie3000/paul_graham_all_essays huggingface dataset:
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January 2017  
  
People who are powerful but uncharismatic will tend to be disliked. Their
power makes them a target for criticism that they don't have the charisma to
disarm. That was Hillary Clinton's problem. It also tends to be a problem for
any CEO who is more of a builder than a schmoozer. And yet the builder-type
CEO is (like Hillary) probably the best person for the job.  
  
I don't think there is any solution to this problem. It's human nature. The
best we can do is to recognize that it's happening, and to understand that
being a magnet for criticism is sometimes a sign not that someone is the wrong
person for a job, but that they're the right one.  
  
  
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September 2017  
  
The most valuable insights are both general and surprising. F = ma for
example. But general and surprising is a hard combination to achieve. That
territory tends to be picked clean, precisely because those insights are so
valuable.  
  
Ordinarily, the best that people can do is one without the other: either
surprising without being general (e.g. gossip), or general without being
surprising (e.g. platitudes).  
  
Where things get interesting is the moderately valuable insights. You get
those from small additions of whichever quality was missing. The more common
case is a small addition of generality: a piece of gossip that's more than
just gossip, because it teaches something interesting about the world. But
another less common approach is to focus on the most general ideas and see if
you can find something new to say about them. Because these start out so
general, you only need a small delta of novelty to produce a useful insight.  
  
A small delta of novelty is all you'll be able to get most of the time. Which
means if you take this route, your ideas will seem a lot like ones that
already exist. Sometimes you'll find you've merely rediscovered an idea that
did already exist. But don't be discouraged. Remember the huge multiplier that
kicks in when you do manage to think of something even a little new.  
  
Corollary: the more general the ideas you're talking about, the less you
should worry about repeating yourself. If you write enough, it's inevitable
you will. Your brain is much the same from year to year and so are the stimuli
that hit it. I feel slightly bad when I find I've said something close to what
I've said before, as if I were plagiarizing myself. But rationally one
shouldn't. You won't say something exactly the same way the second time, and
that variation increases the chance you'll get that tiny but critical delta of
novelty.  
  
And of course, ideas beget ideas. (That sounds _familiar_.) An idea with a
small amount of novelty could lead to one with more. But only if you keep
going. So it's doubly important not to let yourself be discouraged by people
who say there's not much new about something you've discovered. "Not much new"
is a real achievement when you're talking about the most general ideas.  
  
It's not true that there's nothing new under the sun. There are some domains
where there's almost nothing new. But there's a big difference between nothing
and almost nothing, when it's multiplied by the area under the sun.  
  
  
  
  
  
**Thanks** to Sam Altman, Patrick Collison, and Jessica Livingston for reading
drafts of this.  
  
  
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November 2019  
  
If you discover something new, there's a significant chance you'll be accused
of some form of heresy.  
  
To discover new things, you have to work on ideas that are good but non-
obvious; if an idea is obviously good, other people are probably already
working on it. One common way for a good idea to be non-obvious is for it to
be hidden in the shadow of some mistaken assumption that people are very
attached to. But anything you discover from working on such an idea will tend
to contradict the mistaken assumption that was concealing it. And you will
thus get a lot of heat from people attached to the mistaken assumption.
Galileo and Darwin are famous examples of this phenomenon, but it's probably
always an ingredient in the resistance to new ideas.  
  
So it's particularly dangerous for an organization or society to have a
culture of pouncing on heresy. When you suppress heresies, you don't just
prevent people from contradicting the mistaken assumption you're trying to
protect. You also suppress any idea that implies indirectly that it's false.  
  
Every cherished mistaken assumption has a dead zone of unexplored ideas around
it. And the more preposterous the assumption, the bigger the dead zone it
creates.  
  
There is a positive side to this phenomenon though. If you're looking for new
ideas, one way to find them is by _looking for heresies_. When you look at the
question this way, the depressingly large dead zones around mistaken
assumptions become excitingly large mines of new ideas.  
  
  
  
  
  
  
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April 2012  
  
A palliative care nurse called Bronnie Ware made a list of the biggest regrets
of the dying. Her list seems plausible. I could see myself — _can_ see myself
— making at least 4 of these 5 mistakes.  
  
If you had to compress them into a single piece of advice, it might be: don't
be a cog. The 5 regrets paint a portrait of post-industrial man, who shrinks
himself into a shape that fits his circumstances, then turns dutifully till he
stops.  
  
The alarming thing is, the mistakes that produce these regrets are all errors
of omission. You forget your dreams, ignore your family, suppress your
feelings, neglect your friends, and forget to be happy. Errors of omission are
a particularly dangerous type of mistake, because you make them by default.  
  
I would like to avoid making these mistakes. But how do you avoid mistakes you
make by default? Ideally you transform your life so it has other defaults. But
it may not be possible to do that completely. As long as these mistakes happen
by default, you probably have to be reminded not to make them. So I inverted
the 5 regrets, yielding a list of 5 commands

> Don't ignore your dreams; don't work too much; say what you think; cultivate
> friendships; be happy.

which I then put at the top of the file I use as a todo list.  
  
  
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December 2019  
  
I've seen the same pattern in many different fields: even though lots of
people have worked hard in the field, only a small fraction of the space of
possibilities has been explored, because they've all worked on similar things.  
  
Even the smartest, most imaginative people are surprisingly conservative when
deciding what to work on. People who would never dream of being fashionable in
any other way get sucked into working on fashionable problems.  
  
If you want to try working on unfashionable problems, one of the best places
to look is in fields that people think have already been fully explored:
essays, Lisp, venture funding  you may notice a pattern here. If you can find
a new approach into a big but apparently played out field, the value of
whatever you discover will be _multiplied_ by its enormous surface area.  
  
The best protection against getting drawn into working on the same things as
everyone else may be to _genuinely love_ what you're doing. Then you'll
continue to work on it even if you make the same mistake as other people and
think that it's too marginal to matter.  
  
  
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French Translation  
  
  
  
  

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October 2015  
  
This will come as a surprise to a lot of people, but in some cases it's
possible to detect bias in a selection process without knowing anything about
the applicant pool. Which is exciting because among other things it means
third parties can use this technique to detect bias whether those doing the
selecting want them to or not.  
  
You can use this technique whenever (a) you have at least a random sample of
the applicants that were selected, (b) their subsequent performance is
measured, and (c) the groups of applicants you're comparing have roughly equal
distribution of ability.  
  
How does it work? Think about what it means to be biased. What it means for a
selection process to be biased against applicants of type x is that it's
harder for them to make it through. Which means applicants of type x have to
be better to get selected than applicants not of type x.  Which means
applicants of type x who do make it through the selection process will
outperform other successful applicants. And if the performance of all the
successful applicants is measured, you'll know if they do.  
  
Of course, the test you use to measure performance must be a valid one. And in
particular it must not be invalidated by the bias you're trying to measure.
But there are some domains where performance can be measured, and in those
detecting bias is straightforward. Want to know if the selection process was
biased against some type of applicant? Check whether they outperform the
others. This is not just a heuristic for detecting bias. It's what bias means.  
  
For example, many suspect that venture capital firms are biased against female
founders. This would be easy to detect: among their portfolio companies, do
startups with female founders outperform those without? A couple months ago,
one VC firm (almost certainly unintentionally) published a study showing bias
of this type. First Round Capital found that among its portfolio companies,
startups with female founders _outperformed_ those without by 63%.   
  
The reason I began by saying that this technique would come as a surprise to
many people is that we so rarely see analyses of this type. I'm sure it will
come as a surprise to First Round that they performed one. I doubt anyone
there realized that by limiting their sample to their own portfolio, they were
producing a study not of startup trends but of their own biases when selecting
companies.  
  
I predict we'll see this technique used more in the future. The information
needed to conduct such studies is increasingly available. Data about who
applies for things is usually closely guarded by the organizations selecting
them, but nowadays data about who gets selected is often publicly available to
anyone who takes the trouble to aggregate it.  
  
  
  
  
  
  
  
**
|  
  
July 2009  
  
The Segway hasn't delivered on its initial promise, to put it mildly. There
are several reasons why, but one is that people don't want to be seen riding
them. Someone riding a Segway looks like a dork.  
  
My friend Trevor Blackwell built his own Segway, which we called the Segwell.
He also built a one-wheeled version, the Eunicycle, which looks exactly like a
regular unicycle till you realize the rider isn't pedaling. He has ridden them
both to downtown Mountain View to get coffee. When he rides the Eunicycle,
people smile at him. But when he rides the Segwell, they shout abuse from
their cars: "Too lazy to walk, ya fuckin homo?"  
  
Why do Segways provoke this reaction? The reason you look like a dork riding a
Segway is that you look _smug_. You don't seem to be working hard enough.  
  
Someone riding a motorcycle isn't working any harder. But because he's sitting
astride it, he seems to be making an effort. When you're riding a Segway
you're just standing there. And someone who's being whisked along while
seeming to do no work — someone in a sedan chair, for example — can't help but
look smug.  
  
Try this thought experiment and it becomes clear: imagine something that
worked like the Segway, but that you rode with one foot in front of the other,
like a skateboard. That wouldn't seem nearly as uncool.  
  
So there may be a way to capture more of the market Segway hoped to reach:
make a version that doesn't look so easy for the rider. It would also be
helpful if the styling was in the tradition of skateboards or bicycles rather
than medical devices.  
  
Curiously enough, what got Segway into this problem was that the company was
itself a kind of Segway. It was too easy for them; they were too successful
raising money. If they'd had to grow the company gradually, by iterating
through several versions they sold to real users, they'd have learned pretty
quickly that people looked stupid riding them. Instead they had enough to work
in secret. They had focus groups aplenty, I'm sure, but they didn't have the
people yelling insults out of cars. So they never realized they were zooming
confidently down a blind alley.  
  
  
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May 2007  
  
People who worry about the increasing gap between rich and poor generally look
back on the mid twentieth century as a golden age. In those days we had a
large number of high-paying union manufacturing jobs that boosted the median
income. I wouldn't quite call the high-paying union job a myth, but I think
people who dwell on it are reading too much into it.  
  
Oddly enough, it was working with startups that made me realize where the
high-paying union job came from. In a rapidly growing market, you don't worry
too much about efficiency. It's more important to grow fast. If there's some
mundane problem getting in your way, and there's a simple solution that's
somewhat expensive, just take it and get on with more important things. EBay
didn't win by paying less for servers than their competitors.  
  
Difficult though it may be to imagine now, manufacturing was a growth industry
in the mid twentieth century. This was an era when small firms making
everything from cars to candy were getting consolidated into a new kind of
corporation with national reach and huge economies of scale. You had to grow
fast or die. Workers were for these companies what servers are for an Internet
startup. A reliable supply was more important than low cost.  
  
If you looked in the head of a 1950s auto executive, the attitude must have
been: sure, give 'em whatever they ask for, so long as the new model isn't
delayed.  
  
In other words, those workers were not paid what their work was worth.
Circumstances being what they were, companies would have been stupid to insist
on paying them so little.  
  
If you want a less controversial example of this phenomenon, ask anyone who
worked as a consultant building web sites during the Internet Bubble. In the
late nineties you could get paid huge sums of money for building the most
trivial things. And yet does anyone who was there have any expectation those
days will ever return? I doubt it. Surely everyone realizes that was just a
temporary aberration.  
  
The era of labor unions seems to have been the same kind of aberration, just
spread over a longer period, and mixed together with a lot of ideology that
prevents people from viewing it with as cold an eye as they would something
like consulting during the Bubble.  
  
Basically, unions were just Razorfish.  
  
People who think the labor movement was the creation of heroic union
organizers have a problem to explain: why are unions shrinking now? The best
they can do is fall back on the default explanation of people living in fallen
civilizations. Our ancestors were giants. The workers of the early twentieth
century must have had a moral courage that's lacking today.  
  
In fact there's a simpler explanation. The early twentieth century was just a
fast-growing startup overpaying for infrastructure. And we in the present are
not a fallen people, who have abandoned whatever mysterious high-minded
principles produced the high-paying union job. We simply live in a time when
the fast-growing companies overspend on different things.  
  
  
  
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|  
  
After a link to Beating the Averages was posted on slashdot, some readers
wanted to hear in more detail about the specific technical advantages we got
from using Lisp in Viaweb. For those who are interested, here are some
excerpts from a talk I gave in April 2001 at BBN Labs in Cambridge, MA.  
  
  
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| | BBN Talk Excerpts (ASCII)  
  
  
  
  
  

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March 2021  
  
I try to write using ordinary words and simple sentences.  
  
That kind of writing is easier to read, and the easier something is to read,
the more deeply readers will engage with it. The less energy they expend on
your prose, the more they'll have left for your ideas.  
  
And the further they'll read. Most readers' energy tends to flag part way
through an article or essay. If the friction of reading is low enough, more
keep going till the end.  
  
There's an Italian dish called _saltimbocca_ , which means "leap into the
mouth." My goal when writing might be called _saltintesta_ : the ideas leap
into your head and you barely notice the words that got them there.  
  
It's too much to hope that writing could ever be pure ideas. You might not
even want it to be. But for most writers, most of the time, that's the goal to
aim for. The gap between most writing and pure ideas is not filled with
poetry.  
  
Plus it's more considerate to write simply. When you write in a fancy way to
impress people, you're making them do extra work just so you can seem cool.
It's like trailing a long train behind you that readers have to carry.  
  
And remember, if you're writing in English, that a lot of your readers won't
be native English speakers. Their understanding of ideas may be way ahead of
their understanding of English. So you can't assume that writing about a
difficult topic means you can use difficult words.  
  
Of course, fancy writing doesn't just conceal ideas. It can also conceal the
lack of them. That's why some people write that way, to conceal the fact that
they have __nothing to say. Whereas writing simply keeps you honest. If you
say nothing simply, it will be obvious to everyone, including you.  
  
Simple writing also lasts better. People reading your stuff in the future will
be in much the same position as people from other countries reading it today.
The culture and the language will have changed. It's not vain to care about
that, any more than it's vain for a woodworker to build a chair to last.  
  
Indeed, lasting is not merely an accidental quality of chairs, or writing.
It's a sign you did a good job.  
  
But although these are all real advantages of writing simply, none of them are
why I do it. The main reason I write simply is that it offends me not to. When
I write a sentence that seems too complicated, or that uses unnecessarily
intellectual words, it doesn't seem fancy to me. It seems clumsy.  
  
There are of course times when you want to use a complicated sentence or fancy
word for effect. But you should never do it by accident.  
  
The other reason my writing ends up being simple is the way I do it. I write
the first draft fast, then spend days editing it, trying to get everything
just right. Much of this editing is cutting, and that makes simple writing
even simpler.  
  
  
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August 2004  
  
In a recent talk I said something that upset a lot of people: that you could
get smarter programmers to work on a Python project than you could to work on
a Java project.  
  
I didn't mean by this that Java programmers are dumb. I meant that Python
programmers are smart. It's a lot of work to learn a new programming language.
And people don't learn Python because it will get them a job; they learn it
because they genuinely like to program and aren't satisfied with the languages
they already know.  
  
Which makes them exactly the kind of programmers companies should want to
hire. Hence what, for lack of a better name, I'll call the Python paradox: if
a company chooses to write its software in a comparatively esoteric language,
they'll be able to hire better programmers, because they'll attract only those
who cared enough to learn it. And for programmers the paradox is even more
pronounced: the language to learn, if you want to get a good job, is a
language that people don't learn merely to get a job.  
  
Only a few companies have been smart enough to realize this so far. But there
is a kind of selection going on here too: they're exactly the companies
programmers would most like to work for. Google, for example. When they
advertise Java programming jobs, they also want Python experience.  
  
A friend of mine who knows nearly all the widely used languages uses Python
for most of his projects. He says the main reason is that he likes the way
source code looks. That may seem a frivolous reason to choose one language
over another. But it is not so frivolous as it sounds: when you program, you
spend more time reading code than writing it. You push blobs of source code
around the way a sculptor does blobs of clay. So a language that makes source
code ugly is maddening to an exacting programmer, as clay full of lumps would
be to a sculptor.  
  
At the mention of ugly source code, people will of course think of Perl. But
the superficial ugliness of Perl is not the sort I mean. Real ugliness is not
harsh-looking syntax, but having to build programs out of the wrong concepts.
Perl may look like a cartoon character swearing, but there are cases where it
surpasses Python conceptually.  
  
So far, anyway. Both languages are of course moving targets. But they share,
along with Ruby (and Icon, and Joy, and J, and Lisp, and Smalltalk) the fact
that they're created by, and used by, people who really care about
programming. And those tend to be the ones who do it well.  
  
  
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|  If you liked this, you may also like **_Hackers & Painters_**.