what is the random number?
```
May 2006(This essay is derived from a keynote at Xtech.)Could you reproduce Silicon Valley elsewhere, or is there something
unique about it?It wouldn't be surprising if it were hard to reproduce in other
countries, because you couldn't reproduce it in most of the US
either.  What does it take to make a silicon valley even here?What it takes is the right people.  If you could get the right ten
thousand people to move from Silicon Valley to Buffalo, Buffalo
would become Silicon Valley.  
[1]That's a striking departure from the past.  Up till a couple decades
ago, geography was destiny for cities.  All great cities were located
on waterways, because cities made money by trade, and water was the
only economical way to ship.Now you could make a great city anywhere, if you could get the right
people to move there.  So the question of how to make a silicon
valley becomes: who are the right people, and how do you get them
to move?Two TypesI think you only need two kinds of people to create a technology
hub: rich people and nerds.  They're the limiting reagents in the
reaction that produces startups, because they're the only ones
present when startups get started.  Everyone else will move.Observation bears this out: within the US, towns have become startup
hubs if and only if they have both rich people and nerds.  Few
startups happen in Miami, for example, because although it's full
of rich people, it has few nerds.  It's not the kind of place nerds
like.Whereas Pittsburgh has the opposite problem: plenty of nerds, but
no rich people.  The top US Computer Science departments are said
to be MIT, Stanford, Berkeley, and Carnegie-Mellon.  MIT yielded
Route 128.  Stanford and Berkeley yielded Silicon Valley.  But
Carnegie-Mellon?  The record skips at that point.  Lower down the
list, the University of Washington yielded a high-tech community
in Seattle, and the University of Texas at Austin yielded one in
Austin.  But what happened in Pittsburgh?  And in Ithaca, home of
Cornell, which is also high on the list?I grew up in Pittsburgh and went to college at Cornell, so I can
answer for both.  The weather is terrible,  particularly in winter,
and there's no interesting old city to make up for it, as there is
in Boston.  Rich people don't want to live in Pittsburgh or Ithaca.
So while there are plenty of hackers who could start startups,
there's no one to invest in them.Not BureaucratsDo you really need the rich people?  Wouldn't it work to have the
government invest in the nerds?  No, it would not.  Startup investors
are a distinct type of rich people.  They tend to have a lot of
experience themselves in the technology business.  This (a) helps
them pick the right startups, and (b) means they can supply advice
and connections as well as money.  And the fact that they have a
personal stake in the outcome makes them really pay attention.Bureaucrats by their nature are the exact opposite sort of people
from startup investors. The idea of them making startup investments
is comic.  It would be like mathematicians running Vogue-- or
perhaps more accurately, Vogue editors running a math journal.
[2]Though indeed, most things bureaucrats do, they do badly.   We just
don't notice usually, because they only have to compete against
other bureaucrats.  But as startup investors they'd have to compete
against pros with a great deal more experience and motivation.Even corporations that have in-house VC groups generally forbid
them to make their own investment decisions.  Most are only allowed
to invest in deals where some reputable private VC firm is willing
to act as lead investor.Not BuildingsIf you go to see Silicon Valley, what you'll see are buildings.
But it's the people that make it Silicon Valley, not the buildings.
I read occasionally about attempts to set up "technology
parks" in other places, as if the active ingredient of Silicon
Valley were the office space.  An article about Sophia Antipolis
bragged that companies there included Cisco, Compaq, IBM, NCR, and
Nortel.  Don't the French realize these aren't startups?Building office buildings for technology companies won't get you a
silicon valley, because the key stage in the life of a startup
happens before they want that kind of space.  The key stage is when
they're three guys operating out of an apartment.  Wherever the
startup is when it gets funded, it will stay.  The defining quality
of Silicon Valley is not that Intel or Apple or Google have offices
there, but that they were started there.So if you want to reproduce Silicon Valley, what you need to reproduce
is those two or three founders sitting around a kitchen table
deciding to start a company.  And to reproduce that you need those
people.UniversitiesThe exciting thing is, all you need are the people.  If you could
attract a critical mass of nerds and investors to live somewhere,
you could reproduce Silicon Valley.  And both groups are highly
mobile.  They'll go where life is good.  So what makes a place good
to them?What nerds like is other nerds.  Smart people will go wherever other
smart people are.  And in particular, to great universities.  In
theory there could be other ways to attract them, but so far
universities seem to be indispensable.  Within the US, there are
no technology hubs without first-rate universities-- or at least,
first-rate computer science departments.So if you want to make a silicon valley, you not only need a
university, but one of the top handful in the world.  It has to be
good enough to act as a magnet, drawing the best people from thousands
of miles away.  And that means it has to stand up to existing magnets
like MIT and Stanford.This sounds hard.  Actually it might be easy.  My professor friends,
when they're deciding where they'd like to work, consider one thing
above all: the quality of the other faculty.  What attracts professors
is good colleagues.  So if you managed to recruit, en masse, a
significant number of the best young researchers, you could create
a first-rate university from nothing overnight.  And you could do
that for surprisingly little.  If you paid 200 people hiring bonuses
of $3 million apiece, you could put together a faculty that would
bear comparison with any in the world.  And from that point the
chain reaction would be self-sustaining.  So whatever it costs to
establish a mediocre university, for an additional half billion or
so you could have a great one.  
Random number is 23.
[3]PersonalityHowever, merely creating a new university would not be enough to
start a silicon valley. The university is just the seed.  It has
to be planted in the right soil, or it won't germinate.  Plant it
in the wrong place, and you just create Carnegie-Mellon.To spawn startups, your university has to be in a town that has
attractions other than the university.  It has to be a place where
investors want to live, and students want to stay after they graduate.The two like much the same things, because most startup investors
are nerds themselves.  So what do nerds look for in a town?  Their
tastes aren't completely different from other people's, because a
lot of the towns they like most in the US are also big tourist
destinations: San Francisco, Boston, Seattle.   But their tastes
can't be quite mainstream either, because they dislike other big
tourist destinations, like New York, Los Angeles, and Las Vegas.There has been a lot written lately about the "creative class." The
thesis seems to be that as wealth derives increasingly from ideas,
cities will prosper only if they attract those who have them.  That
is certainly true; in fact it was the basis of Amsterdam's prosperity
400 years ago.A lot of nerd tastes they share with the creative class in general.
For example, they like well-preserved old neighborhoods instead of
cookie-cutter suburbs, and locally-owned shops and restaurants
instead of national chains.  Like the rest of the creative class,
they want to live somewhere with personality.What exactly is personality?  I think it's the feeling that each
building is the work of a distinct group of people.  A town with
personality is one that doesn't feel mass-produced.  So if you want
to make a startup hub-- or any town to attract the "creative class"--
you probably have to ban large development projects.
When a large tract has been developed by a single organization, you
can always tell. 
[4]Most towns with personality are old, but they don't have to be.
Old towns have two advantages: they're denser, because they were
laid out before cars, and they're more varied, because they were
built one building at a time.  You could have both now.  Just have
building codes that ensure density, and ban large scale developments.A corollary is that you have to keep out the biggest developer of
all: the government.  A government that asks "How can we build a
silicon valley?" has probably ensured failure by the way they framed
the question.  You don't build a silicon valley; you let one grow.NerdsIf you want to attract nerds, you need more than a town with
personality.  You need a town with the right personality.  Nerds
are a distinct subset of the creative class, with different tastes
from the rest.  You can see this most clearly in New York, which
attracts a lot of creative people, but few nerds. 
[5]What nerds like is the kind of town where people walk around smiling.
This excludes LA, where no one walks at all, and also New York,
where people walk, but not smiling. When I was in grad school in
Boston, a friend came to visit from New York.  On the subway back
from the airport she asked "Why is everyone smiling?"  I looked and
they weren't smiling.  They just looked like they were compared to
the facial expressions she was used to.If you've lived in New York, you know where these facial expressions
come from.  It's the kind of place where your mind may be excited,
but your body knows it's having a bad time.  People don't so much
enjoy living there as endure it for the sake of the excitement.
And if you like certain kinds of excitement, New York is incomparable.
It's a hub of glamour, a magnet for all the shorter half-life
isotopes of style and fame.Nerds don't care about glamour, so to them the appeal of New York
is a mystery.  People who like New York will pay a fortune for a
small, dark, noisy apartment in order to live in a town where the
cool people are really cool.  A nerd looks at that deal and sees
only: pay a fortune for a small, dark, noisy apartment.Nerds will pay a premium to live in a town where the smart people
are really smart, but you don't have to pay as much for that.  It's
supply and demand: glamour is popular, so you have to pay a lot for
it.Most nerds like quieter pleasures.  They like cafes instead of
clubs; used bookshops instead of fashionable clothing shops; hiking
instead of dancing; sunlight instead of tall buildings.  A nerd's
idea of paradise is Berkeley or Boulder.YouthIt's the young nerds who start startups, so it's those specifically
the city has to appeal to.  The startup hubs in the US are all
young-feeling towns.  This doesn't mean they have to be new.
Cambridge has the oldest town plan in America, but it feels young
because it's full of students.What you can't have, if you want to create a silicon valley, is a
large, existing population of stodgy people.  It would be a waste
of time to try to reverse the fortunes of a declining industrial town
like Detroit or Philadelphia by trying to encourage startups.  Those
places have too much momentum in the wrong direction.  You're better
off starting with a blank slate in the form of a small town.  Or
better still, if there's a town young people already flock to, that
one.The Bay Area was a magnet for the young and optimistic for decades
before it was associated with technology.  It was a place people
went in search of something new.  And so it became synonymous with
California nuttiness.  There's still a lot of that there.  If you
wanted to start a new fad-- a new way to focus one's "energy," for
example, or a new category of things not to eat-- the Bay Area would
be the place to do it.  But a place that tolerates oddness in the
search for the new is exactly what you want in a startup hub, because
economically that's what startups are.  Most good startup ideas
seem a little crazy; if they were obviously good ideas, someone
would have done them already.(How many people are going to want computers in their houses?
What, another search engine?)That's the connection between technology and liberalism.  Without
exception the high-tech cities in the US are also the most liberal.
But it's not because liberals are smarter that this is so.  It's
because liberal cities tolerate odd ideas, and smart people by
definition have odd ideas.Conversely, a town that gets praised for being "solid" or representing
"traditional values" may be a fine place to live, but it's never
going to succeed as a startup hub.  The 2004 presidential election,
though a disaster in other respects, conveniently supplied us with
a county-by-county 
map of such places.  
[6]To attract the young, a town must have an intact center.  In most
American cities the center has been abandoned, and the growth, if
any, is in the suburbs.  Most American cities have been turned
inside out. But none of the startup hubs has: not San Francisco,
or Boston, or Seattle.  They all have intact centers.
[7]
My guess is that no city with a dead center could be turned into a
startup hub.  Young people don't want to live in the suburbs.Within the US, the two cities I think could most easily be turned
into new silicon valleys are Boulder and Portland.  Both have the
kind of effervescent feel that attracts the young.  They're each
only a great university short of becoming a silicon valley, if they
wanted to.TimeA great university near an attractive town.  Is that all it takes?
That was all it took to make the original Silicon Valley.  Silicon
Valley traces its origins to William Shockley, one of the inventors
of the transistor.  He did the research that won him the Nobel Prize
at Bell Labs, but when he started his own company in 1956 he moved
to Palo Alto to do it.   At the time that was an odd thing to do.
Why did he?  Because he had grown up there and remembered how nice
it was.  Now Palo Alto is suburbia, but then it was a charming
college town-- a charming college town with perfect weather and San
Francisco only an hour away.The companies that rule Silicon Valley now are all descended in
various ways from Shockley Semiconductor.  Shockley was a difficult
man, and in 1957 his top people-- "the traitorous eight"-- left to
start a new company, Fairchild Semiconductor.  Among them were
Gordon Moore and Robert Noyce, who went on to found Intel, and
Eugene Kleiner, who founded the VC firm Kleiner Perkins.  Forty-two
years later, Kleiner Perkins funded Google, and the partner responsible
for the deal was John Doerr, who came to Silicon Valley in 1974 to
work for Intel.So although a lot of the newest companies in Silicon Valley don't
make anything out of silicon, there always seem to be multiple links
back to Shockley.  There's a lesson here: startups beget startups.
People who work for startups start their own.  People who get rich
from startups fund new ones.  I suspect this kind of organic growth
is the only way to produce a startup hub, because it's the only way
to grow the expertise you need.That has two important implications.  The first is that you need
time to grow a silicon valley.  The university you could create in
a couple years, but the startup community around it has to grow
organically.   The cycle time is limited by the time it takes a
company to succeed, which probably averages about five years.The other implication of the organic growth hypothesis is that you
can't be somewhat of a startup hub.  You either have a self-sustaining
chain reaction, or not.  Observation confirms this too: cities
either have a startup scene, or they don't.  There is no middle
ground.  Chicago has the third largest metropolitan area in America.
As source of startups it's negligible compared to Seattle, number 15.The good news is that the initial seed can be quite small.  Shockley
Semiconductor, though itself not very successful, was big enough.
It brought a critical mass of experts in an important new technology
together in a place they liked enough to stay.CompetingOf course, a would-be silicon valley faces an obstacle the original
one didn't: it has to compete with Silicon Valley.  Can that be
done?  Probably.One of Silicon Valley's biggest advantages is its venture capital
firms.  This was not a factor in Shockley's day, because VC funds
didn't exist.  In fact, Shockley Semiconductor and Fairchild
Semiconductor were not startups at all in our sense.  They were
subsidiaries-- of Beckman Instruments and Fairchild Camera and
Instrument respectively.  Those companies were apparently willing
to establish subsidiaries wherever the experts wanted to live.Venture investors, however, prefer to fund startups within an hour's
drive.  For one, they're more likely to notice startups nearby.
But when they do notice startups in other towns they prefer them
to move.  They don't want to have to travel to attend board meetings,
and in any case the odds of succeeding are higher in a startup hub.The centralizing effect of venture firms is a double one: they cause
startups to form around them, and those draw in more startups through
acquisitions.  And although the first may be weakening because it's
now so cheap to start some startups, the second seems as strong as ever.
Three of the most admired
"Web 2.0" companies were started outside the usual startup hubs,
but two of them have already been reeled in through acquisitions.Such centralizing forces make it harder for new silicon valleys to
get started.  But by no means impossible.  Ultimately power rests
with the founders.  A startup with the best people will beat one
with funding from famous VCs, and a startup that was sufficiently
successful would never have to move.  So a town that
could exert enough pull over the right people could resist and
perhaps even surpass Silicon Valley.For all its power, Silicon Valley has a great weakness: the paradise
Shockley found in 1956 is now one giant parking lot.  San Francisco
and Berkeley are great, but they're forty miles away.  Silicon
Valley proper is soul-crushing suburban sprawl.  It
has fabulous weather, which makes it significantly better than the
soul-crushing sprawl of most other American cities.  But a competitor
that managed to avoid sprawl would have real leverage.  All a city
needs is to be the kind of place the next traitorous eight look at
and say "I want to stay here," and that would be enough to get the
chain reaction started.Notes[1]
It's interesting to consider how low this number could be
made.  I suspect five hundred would be enough, even if they could
bring no assets with them.  Probably just thirty, if I could pick them, 
would be enough to turn Buffalo into a significant startup hub.[2]
Bureaucrats manage to allocate research funding moderately
well, but only because (like an in-house VC fund) they outsource
most of the work of selection.  A professor at a famous university
who is highly regarded by his peers will get funding, pretty much
regardless of the proposal.  That wouldn't work for startups, whose
founders aren't sponsored by organizations, and are often unknowns.[3]
You'd have to do it all at once, or at least a whole department
at a time, because people would be more likely to come if they
knew their friends were.  And you should probably start from scratch,
rather than trying to upgrade an existing university, or much energy
would be lost in friction.[4]
Hypothesis: Any plan in which multiple independent buildings
are gutted or demolished to be "redeveloped" as a single project
is a net loss of personality for the city, with the exception of
the conversion of buildings not previously public, like warehouses.[5]
A few startups get started in New York, but less
than a tenth as many per capita as in Boston, and mostly
in less nerdy fields like finance and media.[6]
Some blue counties are false positives (reflecting the
remaining power of Democractic party machines), but there are no
false negatives.  You can safely write off all the red counties.[7]
Some "urban renewal" experts took a shot at destroying Boston's
in the 1960s, leaving the area around city hall a bleak wasteland,
but most neighborhoods successfully resisted them.Thanks to Chris Anderson, Trevor Blackwell, Marc Hedlund,
Jessica Livingston, Robert Morris, Greg Mcadoo, Fred Wilson,
and Stephen Wolfram for
reading drafts of this, and to Ed Dumbill for inviting me to speak.(The second part of this talk became Why Startups
Condense in America.)
May 2001(This article was written as a kind of business plan for a
new language.
So it is missing (because it takes for granted) the most important
feature of a good programming language: very powerful abstractions.)A friend of mine once told an eminent operating systems
expert that he wanted to design a really good
programming language.  The expert told him that it would be a
waste of time, that programming languages don't become popular
or unpopular based on their merits, and so no matter how
good his language was, no one would use it.  At least, that
was what had happened to the language he had designed.What does make a language popular?  Do popular
languages deserve their popularity?  Is it worth trying to
define a good programming language?  How would you do it?I think the answers to these questions can be found by looking 
at hackers, and learning what they want.  Programming
languages are for hackers, and a programming language
is good as a programming language (rather than, say, an
exercise in denotational semantics or compiler design)
if and only if hackers like it.1 The Mechanics of PopularityIt's true, certainly, that most people don't choose programming
languages simply based on their merits.  Most programmers are told
what language to use by someone else.  And yet I think the effect
of such external factors on the popularity of programming languages
is not as great as it's sometimes thought to be. I think a bigger
problem is that a hacker's idea of a good programming language is
not the same as most language designers'.Between the two, the hacker's opinion is the one that matters.
Programming languages are not theorems. They're tools, designed
for people, and they have to be designed to suit human strengths
and weaknesses as much as shoes have to be designed for human feet.
If a shoe pinches when you put it on, it's a bad shoe, however
elegant it may be as a piece of sculpture.It may be that the majority of programmers can't tell a good language
from a bad one. But that's no different with any other tool. It
doesn't mean that it's a waste of time to try designing a good
language. Expert hackers 
can tell a good language when they see
one, and they'll use it. Expert hackers are a tiny minority,
admittedly, but that tiny minority write all the good software,
and their influence is such that the rest of the programmers will
tend to use whatever language they use. Often, indeed, it is not
merely influence but command: often the expert hackers are the very
people who, as their bosses or faculty advisors, tell the other
programmers what language to use.The opinion of expert hackers is not the only force that determines
the relative popularity of programming languages — legacy software
(Cobol) and hype (Ada, Java) also play a role — but I think it is
the most powerful force over the long term. Given an initial critical
mass and enough time, a programming language probably becomes about
as popular as it deserves to be. And popularity further separates
good languages from bad ones, because feedback from real live users
always leads to improvements. Look at how much any popular language
has changed during its life. Perl and Fortran are extreme cases,
but even Lisp has changed a lot. Lisp 1.5 didn't have macros, for
example; these evolved later, after hackers at MIT had spent a
couple years using Lisp to write real programs. [1]So whether or not a language has to be good to be popular, I think
a language has to be popular to be good. And it has to stay popular
to stay good. The state of the art in programming languages doesn't
stand still. And yet the Lisps we have today are still pretty much
what they had at MIT in the mid-1980s, because that's the last time
Lisp had a sufficiently large and demanding user base.Of course, hackers have to know about a language before they can
use it. How are they to hear? From other hackers. But there has to
be some initial group of hackers using the language for others even
to hear about it. I wonder how large this group has to be; how many
users make a critical mass? Off the top of my head, I'd say twenty.
If a language had twenty separate users, meaning twenty users who
decided on their own to use it, I'd consider it to be real.Getting there can't be easy. I would not be surprised if it is
harder to get from zero to twenty than from twenty to a thousand.
The best way to get those initial twenty users is probably to use
a trojan horse: to give people an application they want, which
happens to be written in the new language.2 External FactorsLet's start by acknowledging one external factor that does affect
the popularity of a programming language. To become popular, a
programming language has to be the scripting language of a popular
system. Fortran and Cobol were the scripting languages of early
IBM mainframes. C was the scripting language of Unix, and so, later,
was Perl. Tcl is the scripting language of Tk. Java and Javascript
are intended to be the scripting languages of web browsers.Lisp is not a massively popular language because it is not the
scripting language of a massively popular system. What popularity
it retains dates back to the 1960s and 1970s, when it was the
scripting language of MIT. A lot of the great programmers of the
day were associated with MIT at some point. And in the early 1970s,
before C, MIT's dialect of Lisp, called MacLisp, was one of the
only programming languages a serious hacker would want to use.Today Lisp is the scripting language of two moderately popular
systems, Emacs and Autocad, and for that reason I suspect that most
of the Lisp programming done today is done in Emacs Lisp or AutoLisp.Programming languages don't exist in isolation. To hack is a
transitive verb — hackers are usually hacking something — and in
practice languages are judged relative to whatever they're used to
hack. So if you want to design a popular language, you either have
to supply more than a language, or you have to design your language
to replace the scripting language of some existing system.Common Lisp is unpopular partly because it's an orphan. It did
originally come with a system to hack: the Lisp Machine. But Lisp
Machines (along with parallel computers) were steamrollered by the
increasing power of general purpose processors in the 1980s. Common
Lisp might have remained popular if it had been a good scripting
language for Unix. It is, alas, an atrociously bad one.One way to describe this situation is to say that a language isn't
judged on its own merits. Another view is that a programming language
really isn't a programming language unless it's also the scripting
language of something. This only seems unfair if it comes as a
surprise. I think it's no more unfair than expecting a programming
language to have, say, an implementation. It's just part of what
a programming language is.A programming language does need a good implementation, of course,
and this must be free. Companies will pay for software, but individual
hackers won't, and it's the hackers you need to attract.A language also needs to have a book about it. The book should be
thin, well-written, and full of good examples. K&R is the ideal
here. At the moment I'd almost say that a language has to have a
book published by O'Reilly. That's becoming the test of mattering
to hackers.There should be online documentation as well. In fact, the book
can start as online documentation. But I don't think that physical
books are outmoded yet. Their format is convenient, and the de
facto censorship imposed by publishers is a useful if imperfect
filter. Bookstores are one of the most important places for learning
about new languages.3 BrevityGiven that you can supply the three things any language needs — a
free implementation, a book, and something to hack — how do you
make a language that hackers will like?One thing hackers like is brevity. Hackers are lazy, in the same
way that mathematicians and modernist architects are lazy: they
hate anything extraneous. It would not be far from the truth to
say that a hacker about to write a program decides what language
to use, at least subconsciously, based on the total number of
characters he'll have to type. If this isn't precisely how hackers
think, a language designer would do well to act as if it were.It is a mistake to try to baby the user with long-winded expressions
that are meant to resemble English. Cobol is notorious for this
flaw. A hacker would consider being asked to writeadd x to y giving zinstead ofz = x+yas something between an insult to his intelligence and a sin against
God.It has sometimes been said that Lisp should use first and rest
instead of car and cdr, because it would make programs easier to
read. Maybe for the first couple hours. But a hacker can learn
quickly enough that car means the first element of a list and cdr
means the rest. Using first and rest means 50% more typing. And
they are also different lengths, meaning that the arguments won't
line up when they're called, as car and cdr often are, in successive
lines. I've found that it matters a lot how code lines up on the
page. I can barely read Lisp code when it is set in a variable-width
font, and friends say this is true for other languages too.Brevity is one place where strongly typed languages lose. All other
things being equal, no one wants to begin a program with a bunch
of declarations. Anything that can be implicit, should be.The individual tokens should be short as well. Perl and Common Lisp
occupy opposite poles on this question. Perl programs can be almost
cryptically dense, while the names of built-in Common Lisp operators
are comically long. The designers of Common Lisp probably expected
users to have text editors that would type these long names for
them. But the cost of a long name is not just the cost of typing
it. There is also the cost of reading it, and the cost of the space
it takes up on your screen.4 HackabilityThere is one thing more important than brevity to a hacker: being
able to do what you want. In the history of programming languages
a surprising amount of effort has gone into preventing programmers
from doing things considered to be improper. This is a dangerously
presumptuous plan. How can the language designer know what the
programmer is going to need to do? I think language designers would
do better to consider their target user to be a genius who will
need to do things they never anticipated, rather than a bumbler
who needs to be protected from himself. The bumbler will shoot
himself in the foot anyway. You may save him from referring to
variables in another package, but you can't save him from writing
a badly designed program to solve the wrong problem, and taking
forever to do it.Good programmers often want to do dangerous and unsavory things.
By unsavory I mean things that go behind whatever semantic facade
the language is trying to present: getting hold of the internal
representation of some high-level abstraction, for example. Hackers
like to hack, and hacking means getting inside things and second
guessing the original designer.Let yourself be second guessed. When you make any tool, people use
it in ways you didn't intend, and this is especially true of a
highly articulated tool like a programming language. Many a hacker
will want to tweak your semantic model in a way that you never
imagined. I say, let them; give the programmer access to as much
internal stuff as you can without endangering runtime systems like
the garbage collector.In Common Lisp I have often wanted to iterate through the fields
of a struct — to comb out references to a deleted object, for example,
or find fields that are uninitialized. I know the structs are just
vectors underneath. And yet I can't write a general purpose function
that I can call on any struct. I can only access the fields by
name, because that's what a struct is supposed to mean.A hacker may only want to subvert the intended model of things once
or twice in a big program. But what a difference it makes to be
able to. And it may be more than a question of just solving a
problem. There is a kind of pleasure here too. Hackers share the
surgeon's secret pleasure in poking about in gross innards, the
teenager's secret pleasure in popping zits. [2] For boys, at least,
certain kinds of horrors are fascinating. Maxim magazine publishes
an annual volume of photographs, containing a mix of pin-ups and
grisly accidents. They know their audience.Historically, Lisp has been good at letting hackers have their way.
The political correctness of Common Lisp is an aberration. Early
Lisps let you get your hands on everything. A good deal of that
spirit is, fortunately, preserved in macros. What a wonderful thing,
to be able to make arbitrary transformations on the source code.Classic macros are a real hacker's tool — simple, powerful, and
dangerous. It's so easy to understand what they do: you call a
function on the macro's arguments, and whatever it returns gets
inserted in place of the macro call. Hygienic macros embody the
opposite principle. They try to protect you from understanding what
they're doing. I have never heard hygienic macros explained in one
sentence. And they are a classic example of the dangers of deciding
what programmers are allowed to want. Hygienic macros are intended
to protect me from variable capture, among other things, but variable
capture is exactly what I want in some macros.A really good language should be both clean and dirty: cleanly
designed, with a small core of well understood and highly orthogonal
operators, but dirty in the sense that it lets hackers have their
way with it. C is like this. So were the early Lisps. A real hacker's
language will always have a slightly raffish character.A good programming language should have features that make the kind
of people who use the phrase "software engineering" shake their
heads disapprovingly. At the other end of the continuum are languages
like Ada and Pascal, models of propriety that are good for teaching
and not much else.5 Throwaway ProgramsTo be attractive to hackers, a language must be good for writing
the kinds of programs they want to write. And that means, perhaps
surprisingly, that it has to be good for writing throwaway programs.A throwaway program is a program you write quickly for some limited
task: a program to automate some system administration task, or
generate test data for a simulation, or convert data from one format
to another. The surprising thing about throwaway programs is that,
like the "temporary" buildings built at so many American universities
during World War II, they often don't get thrown away. Many evolve
into real programs, with real features and real users.I have a hunch that the best big programs begin life this way,
rather than being designed big from the start, like the Hoover Dam.
It's terrifying to build something big from scratch. When people
take on a project that's too big, they become overwhelmed. The
project either gets bogged down, or the result is sterile and
wooden: a shopping mall rather than a real downtown, Brasilia rather
than Rome, Ada rather than C.Another way to get a big program is to start with a throwaway
program and keep improving it. This approach is less daunting, and
the design of the program benefits from evolution. I think, if one
looked, that this would turn out to be the way most big programs
were developed. And those that did evolve this way are probably
still written in whatever language they were first written in,
because it's rare for a program to be ported, except for political
reasons. And so, paradoxically, if you want to make a language that
is used for big systems, you have to make it good for writing
throwaway programs, because that's where big systems come from.Perl is a striking example of this idea. It was not only designed
for writing throwaway programs, but was pretty much a throwaway
program itself. Perl began life as a collection of utilities for
generating reports, and only evolved into a programming language
as the throwaway programs people wrote in it grew larger. It was
not until Perl 5 (if then) that the language was suitable for
writing serious programs, and yet it was already massively popular.What makes a language good for throwaway programs? To start with,
it must be readily available. A throwaway program is something that
you expect to write in an hour. So the language probably must
already be installed on the computer you're using. It can't be
something you have to install before you use it. It has to be there.
C was there because it came with the operating system. Perl was
there because it was originally a tool for system administrators,
and yours had already installed it.Being available means more than being installed, though. An
interactive language, with a command-line interface, is more
available than one that you have to compile and run separately. A
popular programming language should be interactive, and start up
fast.Another thing you want in a throwaway program is brevity. Brevity
is always attractive to hackers, and never more so than in a program
they expect to turn out in an hour.6 LibrariesOf course the ultimate in brevity is to have the program already
written for you, and merely to call it. And this brings us to what
I think will be an increasingly important feature of programming
languages: library functions. Perl wins because it has large
libraries for manipulating strings. This class of library functions
are especially important for throwaway programs, which are often
originally written for converting or extracting data.  Many Perl
programs probably begin as just a couple library calls stuck
together.I think a lot of the advances that happen in programming languages
in the next fifty years will have to do with library functions. I
think future programming languages will have libraries that are as
carefully designed as the core language. Programming language design
will not be about whether to make your language strongly or weakly
typed, or object oriented, or functional, or whatever, but about
how to design great libraries. The kind of language designers who
like to think about how to design type systems may shudder at this.
It's almost like writing applications! Too bad. Languages are for
programmers, and libraries are what programmers need.It's hard to design good libraries. It's not simply a matter of
writing a lot of code. Once the libraries get too big, it can
sometimes take longer to find the function you need than to write
the code yourself. Libraries need to be designed using a small set
of orthogonal operators, just like the core language. It ought to
be possible for the programmer to guess what library call will do
what he needs.Libraries are one place Common Lisp falls short. There are only
rudimentary libraries for manipulating strings, and almost none
for talking to the operating system. For historical reasons, Common
Lisp tries to pretend that the OS doesn't exist. And because you
can't talk to the OS, you're unlikely to be able to write a serious
program using only the built-in operators in Common Lisp. You have
to use some implementation-specific hacks as well, and in practice
these tend not to give you everything you want. Hackers would think
a lot more highly of Lisp if Common Lisp had powerful string
libraries and good OS support.7 SyntaxCould a language with Lisp's syntax, or more precisely, lack of
syntax, ever become popular? I don't know the answer to this
question. I do think that syntax is not the main reason Lisp isn't
currently popular. Common Lisp has worse problems than unfamiliar
syntax. I know several programmers who are comfortable with prefix
syntax and yet use Perl by default, because it has powerful string
libraries and can talk to the os.There are two possible problems with prefix notation: that it is
unfamiliar to programmers, and that it is not dense enough. The
conventional wisdom in the Lisp world is that the first problem is
the real one. I'm not so sure. Yes, prefix notation makes ordinary
programmers panic. But I don't think ordinary programmers' opinions
matter. Languages become popular or unpopular based on what expert
hackers think of them, and I think expert hackers might be able to
deal with prefix notation. Perl syntax can be pretty incomprehensible,
but that has not stood in the way of Perl's popularity. If anything
it may have helped foster a Perl cult.A more serious problem is the diffuseness of prefix notation. For
expert hackers, that really is a problem. No one wants to write
(aref a x y) when they could write a[x,y].In this particular case there is a way to finesse our way out of
the problem. If we treat data structures as if they were functions
on indexes, we could write (a x y) instead, which is even shorter
than the Perl form. Similar tricks may shorten other types of
expressions.We can get rid of (or make optional) a lot of parentheses by making
indentation significant. That's how programmers read code anyway:
when indentation says one thing and delimiters say another, we go
by the indentation. Treating indentation as significant would
eliminate this common source of bugs as well as making programs
shorter.Sometimes infix syntax is easier to read. This is especially true
for math expressions. I've used Lisp my whole programming life and
I still don't find prefix math expressions natural. And yet it is
convenient, especially when you're generating code, to have operators
that take any number of arguments. So if we do have infix syntax,
it should probably be implemented as some kind of read-macro.I don't think we should be religiously opposed to introducing syntax
into Lisp, as long as it translates in a well-understood way into
underlying s-expressions. There is already a good deal of syntax
in Lisp. It's not necessarily bad to introduce more, as long as no
one is forced to use it. In Common Lisp, some delimiters are reserved
for the language, suggesting that at least some of the designers
intended to have more syntax in the future.One of the most egregiously unlispy pieces of syntax in Common Lisp
occurs in format strings; format is a language in its own right,
and that language is not Lisp. If there were a plan for introducing
more syntax into Lisp, format specifiers might be able to be included
in it. It would be a good thing if macros could generate format
specifiers the way they generate any other kind of code.An eminent Lisp hacker told me that his copy of CLTL falls open to
the section format. Mine too. This probably indicates room for
improvement. It may also mean that programs do a lot of I/O.8 EfficiencyA good language, as everyone knows, should generate fast code. But
in practice I don't think fast code comes primarily from things
you do in the design of the language. As Knuth pointed out long
ago, speed only matters in certain critical bottlenecks.  And as
many programmers have observed since, one is very often mistaken
about where these bottlenecks are.So, in practice, the way to get fast code is to have a very good
profiler, rather than by, say, making the language strongly typed.
You don't need to know the type of every argument in every call in
the program. You do need to be able to declare the types of arguments
in the bottlenecks. And even more, you need to be able to find out
where the bottlenecks are.One complaint people have had with Lisp is that it's hard to tell
what's expensive. This might be true. It might also be inevitable,
if you want to have a very abstract language. And in any case I
think good profiling would go a long way toward fixing the problem:
you'd soon learn what was expensive.Part of the problem here is social. Language designers like to
write fast compilers. That's how they measure their skill. They
think of the profiler as an add-on, at best. But in practice a good
profiler may do more to improve the speed of actual programs written
in the language than a compiler that generates fast code. Here,
again, language designers are somewhat out of touch with their
users. They do a really good job of solving slightly the wrong
problem.It might be a good idea to have an active profiler — to push
performance data to the programmer instead of waiting for him to
come asking for it. For example, the editor could display bottlenecks
in red when the programmer edits the source code. Another approach
would be to somehow represent what's happening in running programs.
This would be an especially big win in server-based applications,
where you have lots of running programs to look at. An active
profiler could show graphically what's happening in memory as a
program's running, or even make sounds that tell what's happening.Sound is a good cue to problems. In one place I worked, we had a
big board of dials showing what was happening to our web servers.
The hands were moved by little servomotors that made a slight noise
when they turned. I couldn't see the board from my desk, but I
found that I could tell immediately, by the sound, when there was
a problem with a server.It might even be possible to write a profiler that would automatically
detect inefficient algorithms. I would not be surprised if certain
patterns of memory access turned out to be sure signs of bad
algorithms. If there were a little guy running around inside the
computer executing our programs, he would probably have as long
and plaintive a tale to tell about his job as a federal government
employee. I often have a feeling that I'm sending the processor on
a lot of wild goose chases, but I've never had a good way to look
at what it's doing.A number of Lisps now compile into byte code, which is then executed
by an interpreter. This is usually done to make the implementation
easier to port, but it could be a useful language feature. It might
be a good idea to make the byte code an official part of the
language, and to allow programmers to use inline byte code in
bottlenecks. Then such optimizations would be portable too.The nature of speed, as perceived by the end-user, may be changing.
With the rise of server-based applications, more and more programs
may turn out to be i/o-bound. It will be worth making i/o fast.
The language can help with straightforward measures like simple,
fast, formatted output functions, and also with deep structural
changes like caching and persistent objects.Users are interested in response time. But another kind of efficiency
will be increasingly important: the number of simultaneous users
you can support per processor. Many of the interesting applications
written in the near future will be server-based, and the number of
users per server is the critical question for anyone hosting such
applications. In the capital cost of a business offering a server-based
application, this is the divisor.For years, efficiency hasn't mattered much in most end-user
applications. Developers have been able to assume that each user
would have an increasingly powerful processor sitting on their
desk. And by Parkinson's Law, software has expanded to use the
resources available. That will change with server-based applications.
In that world, the hardware and software will be supplied together.
For companies that offer server-based applications, it will make
a very big difference to the bottom line how many users they can
support per server.In some applications, the processor will be the limiting factor,
and execution speed will be the most important thing to optimize.
But often memory will be the limit; the number of simultaneous
users will be determined by the amount of memory you need for each
user's data. The language can help here too. Good support for
threads will enable all the users to share a single heap. It may
also help to have persistent objects and/or language level support
for lazy loading.9 TimeThe last ingredient a popular language needs is time. No one wants
to write programs in a language that might go away, as so many
programming languages do. So most hackers will tend to wait until
a language has been around for a couple years before even considering
using it.Inventors of wonderful new things are often surprised to discover
this, but you need time to get any message through to people. A
friend of mine rarely does anything the first time someone asks
him. He knows that people sometimes ask for things that they turn
out not to want. To avoid wasting his time, he waits till the third
or fourth time he's asked to do something; by then, whoever's asking
him may be fairly annoyed, but at least they probably really do
want whatever they're asking for.Most people have learned to do a similar sort of filtering on new
things they hear about. They don't even start paying attention
until they've heard about something ten times. They're perfectly
justified: the majority of hot new whatevers do turn out to be a
waste of time, and eventually go away. By delaying learning VRML,
I avoided having to learn it at all.So anyone who invents something new has to expect to keep repeating
their message for years before people will start to get it. We
wrote what was, as far as I know, the first web-server based
application, and it took us years to get it through to people that
it didn't have to be downloaded. It wasn't that they were stupid.
They just had us tuned out.The good news is, simple repetition solves the problem. All you
have to do is keep telling your story, and eventually people will
start to hear. It's not when people notice you're there that they
pay attention; it's when they notice you're still there.It's just as well that it usually takes a while to gain momentum.
Most technologies evolve a good deal even after they're first
launched — programming languages especially. Nothing could be better,
for a new techology, than a few years of being used only by a small
number of early adopters. Early adopters are sophisticated and
demanding, and quickly flush out whatever flaws remain in your
technology. When you only have a few users you can be in close
contact with all of them. And early adopters are forgiving when
you improve your system, even if this causes some breakage.There are two ways new technology gets introduced: the organic
growth method, and the big bang method. The organic growth method
is exemplified by the classic seat-of-the-pants underfunded garage
startup. A couple guys, working in obscurity, develop some new
technology. They launch it with no marketing and initially have
only a few (fanatically devoted) users. They continue to improve
the technology, and meanwhile their user base grows by word of
mouth. Before they know it, they're big.The other approach, the big bang method, is exemplified by the
VC-backed, heavily marketed startup. They rush to develop a product,
launch it with great publicity, and immediately (they hope) have
a large user base.Generally, the garage guys envy the big bang guys. The big bang
guys are smooth and confident and respected by the VCs. They can
afford the best of everything, and the PR campaign surrounding the
launch has the side effect of making them celebrities. The organic
growth guys, sitting in their garage, feel poor and unloved. And
yet I think they are often mistaken to feel sorry for themselves.
Organic growth seems to yield better technology and richer founders
than the big bang method. If you look at the dominant technologies
today, you'll find that most of them grew organically.This pattern doesn't only apply to companies. You see it in sponsored
research too. Multics and Common Lisp were big-bang projects, and
Unix and MacLisp were organic growth projects.10 Redesign"The best writing is rewriting," wrote E. B. White.  Every good
writer knows this, and it's true for software too. The most important
part of design is redesign. Programming languages, especially,
don't get redesigned enough.To write good software you must simultaneously keep two opposing
ideas in your head. You need the young hacker's naive faith in
his abilities, and at the same time the veteran's skepticism. You
have to be able to think 
how hard can it be? with one half of
your brain while thinking 
it will never work with the other.The trick is to realize that there's no real contradiction here.
You want to be optimistic and skeptical about two different things.
You have to be optimistic about the possibility of solving the
problem, but skeptical about the value of whatever solution you've
got so far.People who do good work often think that whatever they're working
on is no good. Others see what they've done and are full of wonder,
but the creator is full of worry. This pattern is no coincidence:
it is the worry that made the work good.If you can keep hope and worry balanced, they will drive a project
forward the same way your two legs drive a bicycle forward. In the
first phase of the two-cycle innovation engine, you work furiously
on some problem, inspired by your confidence that you'll be able
to solve it. In the second phase, you look at what you've done in
the cold light of morning, and see all its flaws very clearly. But
as long as your critical spirit doesn't outweigh your hope, you'll
be able to look at your admittedly incomplete system, and think,
how hard can it be to get the rest of the way?, thereby continuing
the cycle.It's tricky to keep the two forces balanced. In young hackers,
optimism predominates. They produce something, are convinced it's
great, and never improve it. In old hackers, skepticism predominates,
and they won't even dare to take on ambitious projects.Anything you can do to keep the redesign cycle going is good. Prose
can be rewritten over and over until you're happy with it. But
software, as a rule, doesn't get redesigned enough. Prose has
readers, but software has users. If a writer rewrites an essay,
people who read the old version are unlikely to complain that their
thoughts have been broken by some newly introduced incompatibility.Users are a double-edged sword. They can help you improve your
language, but they can also deter you from improving it. So choose
your users carefully, and be slow to grow their number. Having
users is like optimization: the wise course is to delay it. Also,
as a general rule, you can at any given time get away with changing
more than you think. Introducing change is like pulling off a
bandage: the pain is a memory almost as soon as you feel it.Everyone knows that it's not a good idea to have a language designed
by a committee. Committees yield bad design. But I think the worst
danger of committees is that they interfere with redesign. It is
so much work to introduce changes that no one wants to bother.
Whatever a committee decides tends to stay that way, even if most
of the members don't like it.Even a committee of two gets in the way of redesign. This happens
particularly in the interfaces between pieces of software written
by two different people. To change the interface both have to agree
to change it at once. And so interfaces tend not to change at all,
which is a problem because they tend to be one of the most ad hoc
parts of any system.One solution here might be to design systems so that interfaces
are horizontal instead of vertical — so that modules are always
vertically stacked strata of abstraction. Then the interface will
tend to be owned by one of them. The lower of two levels will either
be a language in which the upper is written, in which case the
lower level will own the interface, or it will be a slave, in which
case the interface can be dictated by the upper level.11 LispWhat all this implies is that there is hope for a new Lisp.  There
is hope for any language that gives hackers what they want, including
Lisp. I think we may have made a mistake in thinking that hackers
are turned off by Lisp's strangeness. This comforting illusion may
have prevented us from seeing the real problem with Lisp, or at
least Common Lisp, which is that it sucks for doing what hackers
want to do. A hacker's language needs powerful libraries and
something to hack. Common Lisp has neither. A hacker's language is
terse and hackable. Common Lisp is not.The good news is, it's not Lisp that sucks, but Common Lisp. If we
can develop a new Lisp that is a real hacker's language, I think
hackers will use it. They will use whatever language does the job.
All we have to do is make sure this new Lisp does some important
job better than other languages.History offers some encouragement. Over time, successive new
programming languages have taken more and more features from Lisp.
There is no longer much left to copy before the language you've
made is Lisp. The latest hot language, Python, is a watered-down
Lisp with infix syntax and no macros. A new Lisp would be a natural
step in this progression.I sometimes think that it would be a good marketing trick to call
it an improved version of Python. That sounds hipper than Lisp. To
many people, Lisp is a slow AI language with a lot of parentheses.
Fritz Kunze's official biography carefully avoids mentioning the
L-word.  But my guess is that we shouldn't be afraid to call the
new Lisp Lisp. Lisp still has a lot of latent respect among the
very best hackers — the ones who took 6.001 and understood it, for
example. And those are the users you need to win.In "How to Become a Hacker," Eric Raymond describes Lisp as something
like Latin or Greek — a language you should learn as an intellectual
exercise, even though you won't actually use it:

  Lisp is worth learning for the profound enlightenment experience
  you will have when you finally get it; that experience will make
  you a better programmer for the rest of your days, even if you
  never actually use Lisp itself a lot.

If I didn't know Lisp, reading this would set me asking questions.
A language that would make me a better programmer, if it means
anything at all, means a language that would be better for programming.
And that is in fact the implication of what Eric is saying.As long as that idea is still floating around, I think hackers will
be receptive enough to a new Lisp, even if it is called Lisp. But
this Lisp must be a hacker's language, like the classic Lisps of
the 1970s. It must be terse, simple, and hackable. And it must have
powerful libraries for doing what hackers want to do now.In the matter of libraries I think there is room to beat languages
like Perl and Python at their own game. A lot of the new applications
that will need to be written in the coming years will be 
server-based
applications. There's no reason a new Lisp shouldn't have string
libraries as good as Perl, and if this new Lisp also had powerful
libraries for server-based applications, it could be very popular.
Real hackers won't turn up their noses at a new tool that will let
them solve hard problems with a few library calls. Remember, hackers
are lazy.It could be an even bigger win to have core language support for
server-based applications. For example, explicit support for programs
with multiple users, or data ownership at the level of type tags.Server-based applications also give us the answer to the question
of what this new Lisp will be used to hack. It would not hurt to
make Lisp better as a scripting language for Unix. (It would be
hard to make it worse.) But I think there are areas where existing
languages would be easier to beat. I think it might be better to
follow the model of Tcl, and supply the Lisp together with a complete
system for supporting server-based applications. Lisp is a natural
fit for server-based applications. Lexical closures provide a way
to get the effect of subroutines when the ui is just a series of
web pages. S-expressions map nicely onto html, and macros are good
at generating it. There need to be better tools for writing
server-based applications, and there needs to be a new Lisp, and
the two would work very well together.12 The Dream LanguageBy way of summary, let's try describing the hacker's dream language.
The dream language is 
beautiful, clean, and terse. It has an
interactive toplevel that starts up fast. You can write programs
to solve common problems with very little code.  Nearly all the
code in any program you write is code that's specific to your
application. Everything else has been done for you.The syntax of the language is brief to a fault. You never have to
type an unnecessary character, or even to use the shift key much.Using big abstractions you can write the first version of a program
very quickly. Later, when you want to optimize, there's a really
good profiler that tells you where to focus your attention. You
can make inner loops blindingly fast, even writing inline byte code
if you need to.There are lots of good examples to learn from, and the language is
intuitive enough that you can learn how to use it from examples in
a couple minutes. You don't need to look in the manual much. The
manual is thin, and has few warnings and qualifications.The language has a small core, and powerful, highly orthogonal
libraries that are as carefully designed as the core language. The
libraries all work well together; everything in the language fits
together like the parts in a fine camera. Nothing is deprecated,
or retained for compatibility. The source code of all the libraries
is readily available. It's easy to talk to the operating system
and to applications written in other languages.The language is built in layers. The higher-level abstractions are
built in a very transparent way out of lower-level abstractions,
which you can get hold of if you want.Nothing is hidden from you that doesn't absolutely have to be. The
language offers abstractions only as a way of saving you work,
rather than as a way of telling you what to do. In fact, the language
encourages you to be an equal participant in its design. You can
change everything about it, including even its syntax, and anything
you write has, as much as possible, the same status as what comes
predefined.Notes[1]  Macros very close to the modern idea were proposed by Timothy
Hart in 1964, two years after Lisp 1.5 was released. What was
missing, initially, were ways to avoid variable capture and multiple
evaluation; Hart's examples are subject to both.[2]  In When the Air Hits Your Brain, neurosurgeon Frank Vertosick
recounts a conversation in which his chief resident, Gary, talks
about the difference between surgeons and internists ("fleas"):

  Gary and I ordered a large pizza and found an open booth. The
  chief lit a cigarette. "Look at those goddamn fleas, jabbering
  about some disease they'll see once in their lifetimes. That's
  the trouble with fleas, they only like the bizarre stuff. They
  hate their bread and butter cases. That's the difference between
  us and the fucking fleas. See, we love big juicy lumbar disc
  herniations, but they hate hypertension...."

It's hard to think of a lumbar disc herniation as juicy (except
literally). And yet I think I know what they mean. I've often had
a juicy bug to track down. Someone who's not a programmer would
find it hard to imagine that there could be pleasure in a bug.
Surely it's better if everything just works. In one way, it is.
And yet there is undeniably a grim satisfaction in hunting down
certain sorts of bugs.
```