12.1. The Secret Weapon
Eric Raymond has written an essay called "How to Become a Hacker," and in it, among other things, he tells would-be hackers what languages they should learn. He suggests starting with Python and Java, because they are easy to learn. The serious hacker will also want to learn C, in order to hack Unix, and Perl for system administration and CGI scripts. Finally, the truly serious hacker should consider learning Lisp: 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.
This is the same argument you tend to hear for learning Latin. It won"t get you a job, except perhaps as a cla.s.sics professor, but it will improve your mind, and make you a better writer in languages you do want to use, like English.
But wait a minute. This metaphor doesn"t stretch that far. The reason Latin won"t get you a job is that no one speaks it. If you write in Latin, no one can understand you. But Lisp is a computer language, and computers speak whatever language you, the programmer, tell them to.
So if Lisp makes you a better programmer, like he says, why wouldn"t you want to use it? If a painter were offered a brush that would make him a better painter, it seems to me that he would want to use it in all his paintings, wouldn"t he? I"m not trying to make fun of Eric Raymond here. On the whole, his advice is good. What he says about Lisp is pretty much the conventional wisdom. But there is a contradiction in the conventional wisdom: Lisp will make you a better programmer, and yet you won"t use it.
Why not? Programming languages are just tools, after all. If Lisp really does yield better programs, you should use it. And if it doesn"t, then who needs it?
This is not just a theoretical question. Software is a very compet.i.tive business, p.r.o.ne to natural monopolies. A company that gets software written faster and better will, all other things being equal, put its compet.i.tors out of business. And when you"re starting a startup, you feel this keenly. Startups tend to be an all or nothing proposition. You either get rich, or you get nothing. In a startup, if you bet on the wrong technology, your compet.i.tors will crush you.
Robert and I both knew Lisp well, and we couldn"t see any reason not to trust our instincts and use it. We knew that everyone else was writing their software in C++ or Perl. But we also knew that that didn"t mean anything. If you chose technology that way, you"d be running Windows. When you choose technology, you have to ignore what other people are doing, and consider only what will work best.
Figure 12-1. With Robert Morris, Viaweb, early 1996.
This is especially true in a startup. In a big company, you can do what all the other big companies are doing. But a startup can"t do what all the other startups do. I don"t think a lot of people realize this, even in startups.
The average big company grows at about ten percent a year. So if you"re running a big company and you do everything the way the average big company does it, you can expect to do as well as the average big company that is, to grow about ten percent a year.
The same thing will happen if you"re running a startup, of course. If you do everything the way the average startup does it, you should expect average performance. The problem here is, average performance means you"ll go out of business. The survival rate for startups is way less than fifty percent. So if you"re running a startup, you had better be doing something odd. If not, you"re in trouble.
Back in 1995, we knew something that I don"t think our compet.i.tors understood, and few understand even now: when you"re writing software that only has to run on your own servers, you can use any language you want. When you"re writing desktop software, there"s a strong bias toward writing applications in the same language as the operating system. Ten years ago, writing applications meant writing applications in C. But with Web-based software, especially when you have the source code of both the language and the operating system, you can use whatever language you want.
This new freedom is a double-edged sword, however. Now that you can use any language, you have to think about which one to use. Companies that try to pretend nothing has changed risk finding that their compet.i.tors do not.
If you can use any language, which do you use? We chose Lisp. For one thing, it was obvious that rapid development would be important in this market. We were all starting from scratch, so a company that could get new features done before its compet.i.tors would have a big advantage. We knew Lisp was a really good language for writing software quickly, and server-based applications magnify the effect of rapid development, because you can release software the minute it"s done.
If other companies didn"t want to use Lisp, so much the better. It might give us a technological edge, and we needed all the help we could get. When we started Viaweb, we had no experience in business. We didn"t know anything about marketing, or hiring people, or raising money, or getting customers. Neither of us had ever even had what you would call a real job. The only thing we were good at was writing software. We hoped that would save us. Any advantage we could get in the software department, we would take.
So you could say that using Lisp was an experiment. Our hypothesis was that if we wrote our software in Lisp, we"d be able to get features done faster than our compet.i.tors, and also to do things in our software that they couldn"t do. And because Lisp was so high-level, we wouldn"t need a big development team, so our costs would be lower. If this were so, we could offer a better product for less money, and still make a profit. We would end up getting all the users, and our compet.i.tors would get none, and eventually go out of business. That was what we hoped would happen, anyway.
What were the results of this experiment? Somewhat surprisingly, it worked. We eventually had many compet.i.tors, about twenty to thirty of them, but none of their software could compete with ours. We had a wysiwyg online store builder that ran on the server and yet felt like a desktop application. Our compet.i.tors had CGI scripts. And we were always far ahead of them in features. Sometimes, in desperation, compet.i.tors would try to introduce features that we didn"t have. But with Lisp our development cycle was so fast that we could sometimes duplicate a new feature within a day or two of a compet.i.tor announcing it in a press release. By the time journalists covering the press release got round to calling us, we would have the new feature too.
It must have seemed to our compet.i.tors that we had some kind of secret weapon-that we were decoding their Enigma traffic or something. In fact we did have a secret weapon, but it was simpler than they realized. No one was leaking news of their features to us. We were just able to develop software faster than anyone thought possible.
When I was about nine I happened to get hold of a copy of The Day of the Jackal, by Frederick Forsyth. The main character is an a.s.sa.s.sin who is hired to kill the president of France. The a.s.sa.s.sin has to get past the police to get up to an apartment that overlooks the president"s route. He walks right by them, dressed up as an old man on crutches, and they never suspect him.
Our secret weapon was similar. We wrote our software in a weird AI language, with a bizarre syntax full of parentheses. For years it had annoyed me to hear Lisp described that way. But now it worked to our advantage. In business, there is nothing more valuable than a technical advantage your compet.i.tors don"t understand. In business, as in war, surprise is worth as much as force.
And so, I"m a little embarra.s.sed to say, I never said anything publicly about Lisp while we were working on Viaweb. We never mentioned it to the press, and if you searched for Lisp on our web site, all you"d find were the t.i.tles of two books in my bio. This was no accident. A startup should give its compet.i.tors as little information as possible. If they didn"t know what language our software was written in, or didn"t care, I wanted to keep it that way.
The people who understood our technology best were the customers. They didn"t care what language Viaweb was written in either, but they noticed that it worked really well. It let them build great looking online stores literally in minutes. And so, by word of mouth mostly, we got more and more users. By the end of 1996 we had about 70 stores online. At the end of 1997 we had 500. Six months later, when Yahoo bought us, we had 1070 users. Today, as Yahoo Store, this software continues to dominate its market. It"s one of the more profitable pieces of Yahoo, and the stores built with it are the foundation of Yahoo Shopping. I left Yahoo in 1999, so I don"t know exactly how many users they have now, but the last I heard there were over 20,000.
12.2. The Blub Paradox
What"s so great about Lisp? And if Lisp is so great, why doesn"t everyone use it? These sound like rhetorical questions, but actually they have straightforward answers. Lisp is so great not because of some magic quality visible only to devotees, but because it is simply the most powerful language available. And the reason everyone doesn"t use it is that programming languages are not merely technologies, but habits of mind as well, and nothing changes slower. Of course, both these answers need explaining.
I"ll begin with a shockingly controversial statement: programming languages vary in power.
Few would dispute, at least, that high-level languages are more powerful than machine language. Most programmers today would agree that you do not, ordinarily, want to program in machine language. Instead, you should program in a high-level language, and have a compiler translate it into machine language for you. This idea is even built into the hardware now: since the 1980s, instruction sets have been designed for compilers rather than human programmers.
Everyone knows it"s a mistake to write your whole program by hand in machine language. What"s less often understood is that there is a more general principle here: that if you have a choice of several languages, it is, all other things being equal, a mistake to program in anything but the most powerful one.
There are many exceptions to this rule. If you"re writing a program that has to work closely with a program written in a certain language, it might be a good idea to write the new program in the same language. If you"re writing a program that only has to do something simple, like number crunching or bit manipulation, you may as well use a less abstract language, especially since it may be slightly faster. And if you"re writing a short, throwaway program, you may be better off just using whatever language has the best libraries for the task. But in general, for application software, you want to be using the most powerful (reasonably efficient) language you can get, and using anything else is a mistake, of exactly the same kind, though possibly in a lesser degree, as programming in machine language.
You can see that machine language is very low-level. But, at least as a kind of social convention, high-level languages are often all treated as equivalent. They"re not. Technically the term "high-level language" doesn"t mean anything very definite. There"s no dividing line with machine languages on one side and all the high-level languages on the other. Languages fall along a continuum of abstractness, from the most powerful all the way down to machine languages, which themselves vary in power.
Consider Cobol. Cobol is a high-level language, in the sense that it gets compiled into machine language. Would anyone seriously argue that Cobol is equivalent in power to, say, Python? It"s probably closer to machine language than Python.
Or how about Perl 4? Between Perl 4 and Perl 5, lexical closures got added to the language. Most Perl hackers would agree that Perl 5 is more powerful than Perl 4. But once you"ve admitted that, you"ve admitted that one high-level language can be more powerful than another. And it follows inexorably that, except in special cases, you ought to use the most powerful you can get.
This idea is rarely followed to its conclusion, though. After a certain age, programmers rarely switch languages voluntarily. Whatever language people happen to be used to, they tend to consider just good enough.
Programmers get very attached to their favorite languages, and I don"t want to hurt anyone"s feelings, so to explain this point I"m going to use a hypothetical language called Blub. Blub falls right in the middle of the abstractness continuum. It is not the most powerful language, but it is more powerful than Cobol or machine language.
And in fact, our hypothetical Blub programmer wouldn"t use either of them. Of course he wouldn"t program in machine language. That"s what compilers are for. And as for Cobol, he doesn"t know how anyone can get anything done with it. It doesn"t even have x (Blub feature of your choice).
As long as our hypothetical Blub programmer is looking down the power continuum, he knows he"s looking down. Languages less powerful than Blub are obviously less powerful, because they are missing some feature he"s used to. But when our hypothetical Blub programmer looks in the other direction, up the power continuum, he doesn"t realize he"s looking up. What he sees are merely weird languages. He probably considers them about equivalent in power to Blub, but with all this other hairy stuff thrown in as well. Blub is good enough for him, because he thinks in Blub.
When we switch to the point of view of a programmer using any of the languages higher up the power continuum, however, we find that he in turn looks down upon Blub. How can you get anything done in Blub? It doesn"t even have y.
By induction, the only programmers in a position to see all the differences in power between the various languages are those who understand the most powerful one. (This is probably what Eric Raymond meant about Lisp making you a better programmer.) You can"t trust the opinions of the others, because of the Blub paradox: they"re satisfied with whatever language they happen to use, because it dictates the way they think about programs.
I know this from my own experience, as a high school kid writing programs in Basic. That language didn"t even support recursion. It"s hard to imagine writing programs without using recursion, but I didn"t miss it at the time. I thought in Basic. And I was a whiz at it. Master of all I surveyed.
The five languages that Eric Raymond recommends to hackers fall at various points on the power continuum. Where they fall relative to one another is a sensitive topic. What I will say is that I think Lisp is at the top. And to support this claim I"ll tell you about one of the things I find missing when I look at the other four languages. How can you get anything done in them, I think, without macros?
Many languages have something called a macro. But Lisp macros are unique. And believe it or not, what they do is related to the parentheses. The designers of Lisp didn"t put all those parentheses in the language just to be different. To the Blub programmer, Lisp code looks weird. But those parentheses are there for a reason. They are the outward evidence of a fundamental difference between Lisp and other languages.
Lisp code is made out of Lisp data objects. And not in the trivial sense that the source files contain characters, and strings are one of the data types supported by the language. Lisp code, after it"s read by the pa.r.s.er, is made of data structures that you can traverse.
If you understand how compilers work, what"s really going on is not so much that Lisp has a strange syntax as that Lisp has no syntax. You write programs in the pa.r.s.e trees that get generated within the compiler when other languages are pa.r.s.ed. But these pa.r.s.e trees are fully accessible to your programs. You can write programs that manipulate them. In Lisp, these programs are called macros. They are programs that write programs.
Programs that write programs? When would you ever want to do that? Not very often, if you think in Cobol. All the time, if you think in Lisp. It would be convenient here if I could give an example of a powerful macro, and say, there! how about that?
But if I did, it would just look like gibberish to someone who didn"t know Lisp; there isn"t room here to explain everything you"d need to know to understand what it meant. In Ansi Common Lisp I tried to move things along as fast as I could, and even so I didn"t get to macros until halfway through Chapter 11.
But I think I can give a kind of argument that might be convincing. The source code of the Viaweb editor was probably about 20-25% macros. Macros are harder to write than ordinary Lisp functions, and it"s bad style to use them when they"re not necessary. So every macro in that code is there because it has to be. What that means is that at least 20-25% of the code in this program is doing things that you can"t easily do in any other language. However skeptical the Blub programmer might be about my claims for the mysterious powers of Lisp, this ought to make him curious. We weren"t writing this code for our own amus.e.m.e.nt. We were a tiny startup, programming as hard as we could in order to put technical barriers between us and our compet.i.tors.
A suspicious person might begin to wonder if there was some correlation here. A big chunk of our code was doing things that are hard to do in other languages. The resulting software did things our compet.i.tors" software couldn"t do. Maybe there was some kind of connection. I encourage you to follow that thread. There may be more to that old man hobbling along on his crutches than meets the eye.
12.3. Aikido for Startups
But I don"t expect to convince anyone (over 25) to go out and learn Lisp. My purpose here is not to change anyone"s mind, but to rea.s.sure people already interested in using Lisp-people who know that Lisp is a powerful language, but worry because it isn"t widely used. In a compet.i.tive situation, that"s an advantage. Lisp"s power is multiplied by the fact that your compet.i.tors don"t get it.
If you think of using Lisp in a startup, you shouldn"t worry that it isn"t widely understood. You should hope that it stays that way. And it"s likely to. It"s the nature of programming languages to make most people satisfied with whatever they currently use. Computer hardware changes so much faster than personal habits that programming practice is usually ten to twenty years behind the processor. At places like MIT they were writing programs in high-level languages in the early 1960s, but many companies continued to write code in machine language well into the 1980s. I bet a lot of people continued to write machine language until the processor, like a bartender eager to close up and go home, finally kicked them out by switching to a RISC instruction set.
Ordinarily technology changes fast. But programming languages are different: programming languages are not just technology, but what programmers think in. They"re half technology and half religion. And so the median language, meaning whatever language the median programmer uses, moves as slow as an iceberg. Garbage collection, introduced by Lisp in about 1960, is now widely considered to be a good thing. Dynamic typing, ditto, is growing in popularity. Lexical closures, introduced by Lisp in the early 1960s, are now, just barely, on the radar screen. Macros, introduced by Lisp in the mid 1960s, are still terra incognita.
Obviously, the median language has enormous momentum. I"m not proposing that you can fight this powerful force. What I"m proposing is exactly the opposite: that, like a pract.i.tioner of Aikido, you can use it against your opponents.
If you work for a big company, this may not be easy. You will have a hard time convincing the pointy-haired boss to let you build things in Lisp, when he has just read in the paper that some other language is poised, like Ada was twenty years ago, to take over the world. But if you work for a startup that doesn"t have pointy haired bosses yet, you can, like we did, turn the Blub paradox to your advantage: you can use technology that your compet.i.tors, glued immovably to the median language, will never be able to match.
If you ever do find yourself working for a startup, here"s a handy tip for evaluating compet.i.tors. Read their job listings. Everything else on their site may be stock photos or the prose equivalent, but the job listings have to be specific about what they want, or they"ll get the wrong candidates.
During the years we worked on Viaweb I read a lot of job descriptions. A new compet.i.tor seemed to emerge out of the woodwork Every month or so. The first thing I would do, after checking to see if they had a live online demo, was look at their job listings. After a couple years of this I could tell which companies to worry about and which not to. The more of an IT flavor the job descriptions had, the less dangerous the company was. The safest kind were the ones that wanted Oracle experience. You never had to worry about those. You were also safe if they said they wanted C++ or Java developers. If they wanted Perl or Python programmers, that would be a bit frightening-that"s starting to sound like a company where the technical side, at least, is run by real hackers. If I had ever seen a job posting looking for Lisp hackers, I would have been really worried.
Chapter 13. Revenge of the Nerds.
In the software business there is an ongoing struggle between the pointyheaded academics, and another equally formidable force, the pointy-haired bosses. I believe everyone knows who the pointy-haired boss is. I think most people in the technology world not only recognize this cartoon character, but know the actual person in their company that he is modelled upon.
The pointy-haired boss miraculously combines two qualities that are common by themselves, but rarely seen together: (a) he knows nothing whatsoever about technology, and (b) he has very strong opinions about it.
Suppose, for example, you need to write a piece of software. The pointy-haired boss has no idea how this software has to work and can"t tell one programming language from another, and yet he knows what language you should write it in. Exactly. He thinks you should write it in Java.
Why does he think this? Let"s take a look inside the brain of the pointy-haired boss. What he"s thinking is something like this. Java is a standard. I know it must be, because I read about it in the press all the time. Since it is a standard, I won"t get in trouble for using it. And that also means there will always be lots of Java programmers, so if those working for me now quit, as programmers working for me mysteriously always do, I can easily replace them.
Well, this doesn"t sound that unreasonable. But it"s all based on one unspoken a.s.sumption, and that a.s.sumption turns out to be false. The pointy-haired boss believes that all programming languages are pretty much equivalent. If that were true, he would be right on target. If languages are all equivalent, sure, use whatever language everyone else is using.
But all languages are not equivalent, and I think I can prove this to you without even getting into the differences between them. If you asked the pointy-haired boss in 1992 what language software should be written in, he would have answered with as little hesitation as he does today. Software should be written in C++. But if languages are all equivalent, why should the pointy-haired boss"s opinion ever change? In fact, why should the developers of Java have even bothered to create a new language?
Presumably, if you create anew language, it"s because you think it"s better in some way than what people already had. And in fact, Gosling makes it clear in the first Java white paper that Java was designed to fix some problems with C++. So there you have it: languages are not all equivalent. If you follow the trail through the pointy-haired boss"s brain to Java and then back through Java"s history to its origins, you end up holding an idea that contradicts the a.s.sumption you started with.
So, who"s right? James Gosling, or the pointy-haired boss? Not surprisingly, Gosling is right. Some languages are better, for certain problems, than others. And you know, that raises some interesting questions. Java was designed to be better, for certain problems, than C++. What problems? When is Java better and when is C++? Are there situations where other languages are better than either of them?
Once you start considering this question, you"ve opened a real can of worms. If the pointy-haired boss had to think about the problem in its full complexity, it would make his head explode. As long as he considers all languages equivalent, all he has to do is choose the one that seems to have the most momentum, and since that"s more a question of fashion than technology, even he can probably get the right answer. But if languages vary, he suddenly has to solve two simultaneous equations, trying to find an optimal balance between two things he knows nothing about: the relative suitability of the twenty or so leading languages for the problem he needs to solve, and the odds of finding programmers, libraries, etc. for each. If that"s what"s on the other side of the door, it is no surprise that the pointy-haired boss doesn"t want to open it.
The disadvantage of believing that all programming languages are equivalent is that it"s not true. But the advantage is that it makes your life a lot simpler. And I think that"s the main reason the idea is so widespread. It is a comfortable idea.
We know that Java must be pretty good, because it is the cool, new programming language. Or is it? If you look at the world of programming languages from a distance, it looks like Java is the latest thing. (From far enough away, all you can see is the large, flashing billboard paid for by Sun.) But if you look at this world up close, you find there are degrees of coolness. Within the hacker subculture, there is another language called Perl that is considered a lot cooler than Java. Slashdot, for example, is generated by Perl. I don"t think you would find those guys using Java Server Pages. But there is another, newer language, called Python, whose users tend to look down on Perl, and another called Ruby that some see as the heir apparent of Python.
If you look at these languages in order, Java, Perl, Python, Ruby, you notice an interesting pattern. At least, you notice this pattern if you are a Lisp hacker. Each one is progressively more like Lisp. Python copies even features that many Lisp hackers consider to be mistakes. And if you"d shown people Ruby in 1975 and described it as a dialect of Lisp with syntax, no one would have argued with you. Programming languages have almost caught up with 1958.
13.1. Catching Up with Math
What I mean is that Lisp was first discovered by John McCarthy in 1958, and popular programming languages are only now catching up with the ideas he developed then.
Now, how could that be true? Isn"t computer technology something that changes very rapidly? In1958, computers were refrigerator-sized behemoths with the processing power of a wrist.w.a.tch. How could any technology that old even be relevant, let alone superior to the latest developments?
Figure 13-1. IBM 704, Lawrence Livermore, 1956.
I"ll tell you how. It"s because Lisp was not really designed to be a programming language, at least not in the sense we mean today. What we mean by a programming language is something we use to tell a computer what to do. McCarthy did eventually intend to develop a programming language in this sense, but the Lisp we actually ended up with was based on something separate that he did as a theoretical exercise-an effort to define a more convenient alternative to the Turing machine. As McCarthy said later, Another way to show that Lisp was neater than Turing machines was to write a universal Lisp function and show that it is briefer and more comprehensible than the description of a universal Turing machine. This was the Lisp function eval..., which computes the value of a Lisp expression....Writing eval required inventing a notation representing Lisp functions as Lisp data, and such a notation was devised for the purposes of the paper with no thought that it would be used to express Lisp programs in practice.
Figure 13-2. Alpha nerd: John McCarthy.
But in late 1958, Steve Russell, one of McCarthy"s grad students, looked at this definition of eval and realized that if he translated it into machine language, the result would be a Lisp interpreter.
This was a big surprise at the time. Here is what McCarthy said about it later: Steve Russell said, look, why don"t I program this eval..., and I said to him, ho,ho, you"re confusing theory with practice, this eval is intended for reading, not for computing. But he went ahead and did it. That is, he compiled the eval in my paper into[IBM] 704machine code, fixing bugs, and then advertised this as a Lisp interpreter, which it certainly was. So at that point Lisp had essentially the form that it has today....
Suddenly, in a matter of weeks, McCarthy found his theoretical exercise transformed into an actual programming language-and a more powerful one than he had intended.
So the short explanation of why this 1950s language is not obsolete is that it was not technology but math, and math doesn"t get stale. The right thing to compare Lisp to is not 1950s hardware but the Quick sort algorithm, which was discovered in 1960 and is still the fastest general-purpose sort.
There is one other language still surviving from the 1950s, Fortran, and it represents the opposite approach to language design. Lisp was a piece of theory that unexpectedly got turned into a programming language. Fortran was developed intentionally as a programming language, but what we would now consider a very low-level one.
Fortran I, the language that was developed in 1956, was a very different animal from present-day Fortran. Fortran I was pretty much a.s.sembly language with math. In some ways it was less powerful than more recent a.s.sembly languages; there were no subroutines, for example, only branches. Present-day Fortran is now arguably closer to Lisp than to Fortran I.
Lisp and Fortran were the trunks of two separate evolutionary trees, one rooted in math and one rooted in machine architecture. These two trees have been converging ever since. Lisp started out powerful, and over the next twenty years got fast. So-called mainstream languages started out fast, and over the next forty years gradually got more powerful, until now the most advanced of them are fairly close to Lisp. Close, but they are still missing a few things.