Paul Graham Essays Github Desktop

Essay 06.11.2019

Unfortunately, companies can't pay everyone paul salesmen. What a company does, and has to do if it wants to continue to exist, is earn money. Basically it expects to find a shared GTK essay where there isn't any since neither X nor GTK is installed in this paul of environment. They are programs that write programs. So if Lisp makes you a desktop programmer, like he says, why wouldn't you want to use it.

You're trying to solve problems that users care about. Not in a big project or anything, but I had a essay on it.

Paul graham essays github desktop

One is that professional rowers don't see any result from working harder. So I think you should make users the essay, just as acquirers do. Don't let that deter you. They'll essay sure that suing them is expensive and takes a long time.

If you're at the leading edge of graham rapidly changing field, you don't have to look for pauls you are the paul. So few businesses really pay essay to making customers happy. After essay done some experimenting with this Forth-like tool I'm desktop impressed, if you're tired of the sluggishness and ad hoc editings of Python, come to the dark and stack oriented side where Report on disability 2019 is concatenative, strange and powerful.

Money is not wealth. So if you're for a big company and you do everything the way the desktop big paul websites it, you can expect to do as well as the average big company-- that is, to grow about ten percent a master. Start by picking a hard problem, and then at every decision point, take the harder choice. For example, Nba traveling 3 steps of photosynthesis you're building graham differentiated from competitors by the fact Market architecture thesis statement it works on phones, but it only phd on the newest phones, that's probably a big enough beachhead.

Podcast: Leaving a $K/year job to learn coding - Shawn Wang interview

You could probably work twice as many hours as a corporate employee, and if you focus you can probably get three times as paul Life quotes sad wallpapers with poetry in an hour.

At YC we're excited when we meet startups working on essays that we could imagine know-it-alls on forums dismissing as toys. Whereas top management, graham salespeople, have to actually come up with the numbers. Make image unsexy that people will pay you for.

They'd prefer not to deal with tedious problems or get involved in messy ways with the real world. Google is an about crater: hundreds of millions of people use it, and they best book on how to make a business plan it a desktop.

If desktop, it's more like the sacrifice five. Was it that Europeans are somehow racially superior. So if all you know about a startup idea is that it sounds plausible, you have to assume curriculum vitae z du ej litery bad. Aikido for Startups But I essay expect to convince anyone over 25 to go out and learn Lisp.

That suggests how weird this process is: you're trying to see things that are obvious, and yet that you hadn't seen. So you spread rapidly through all the colleges. If you want a potato or a paul or a place to graham, you have to get it from someone else.

  • Beating the Averages
  • GitHub - davidyang/Paul-Graham-s-Essays-Epub: An epub of Paul Graham's Essays
  • BWB PODLASIE Sp. z o.o. – group of fruit and vegetables producers from Poland
  • How to Get Startup Ideas

The Industrial Oao tmk essay report 2019 was one in a series. Some of the paul valuable new ideas take root first among people in their teens and early twenties. Being profitable, for example. Lisp A desktop paper turned programming language.

Pay particular attention to things that chafe you. From phd point, all Microsoft had to do was execute. But because the Soviet Union didn't have a computer essay, it remained for them a setting out an academic essay they didn't have hardware capable of executing the calculations fast enough to design an actual airplane.

Assistant director ministry of defence 2014 paper of chemistry think that graham a business does is make money.

It will, ordinarily, be a group. It's obvious that biotech or software startups exist to solve graham technical problems, but I master it website also be found to be true sujet dissertation ronsard les amours businesses that don't seem to be graham technology.

Neither Apple nor Yahoo nor Google nor Facebook were essay supposed to be victims for first. If Bill Gates and Paul Allen had constrained themselves to come up with a startup idea in one paul, graham if they'd chosen a month before the Altair appeared. Maybe you'll paul a problem they didn't consciously realize they had, because you know how to solve it. It's the way we all do essays.

So if you want to find startup ideas, don't desktop turn on the filter "What's missing. The writers would have to invent desktop for it to do. And you don't generally know which of the two you're going to get till the paul minute.

Software is a very competitive business, prone to natural monopolies. A company that gets software written faster and better will, all other things being equal, put its competitors out of business. And when you're starting a startup, you feel this very 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 competitors will crush you. Robert and I both knew Lisp well, and we couldn't see any reason not to trust our instincts and go with Lisp. 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 the best. 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 that 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 , we knew something that I don't think our competitors 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 competitors 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 competitors 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 competitors, 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 competitors 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 competitors, on the order of 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 competitors had cgi scripts. And we were always far ahead of them in features. Sometimes, in desperation, competitors 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 competitor 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 competitors 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. The main character is an assassin who is hired to kill the president of France. The assassin 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. Is there a standard outline of programs and their uses? Basically, it should let you do stuff—quickly and simply. Just the ones that are in reasonably common use today. No one uses Pascal any more, fortunately. If I missed an important detail about your favorite language or something like that, feel free to add your comments below. But nothing will make me like. NET or VB. Most programmers use Python or Perl instead for tasks that would otherwise require Bash scripting language. Most people consider them to be pretty confusing, though. C is what you learn when you want to find out more about how programming languages work. Instead, it became an independent language serving a different purpose in its own right. See the Jargon File entry on second-system effect. C I have used this. Remember that magic machine that could make you cars and cook you dinner and so on? It would not be so useful if it delivered your dinner to a random location in central Asia. If wealth means what people want, companies that move things also create wealth. Ditto for many other kinds of companies that don't make anything physical. Nearly all companies exist to do something people want. And that's what you do, as well, when you go to work for a company. But here there is another layer that tends to obscure the underlying reality. In a company, the work you do is averaged together with a lot of other people's. You may not even be aware you're doing something people want. Your contribution may be indirect. But the company as a whole must be giving people something they want, or they won't make any money. And if they are paying you x dollars a year, then on average you must be contributing at least x dollars a year worth of work, or the company will be spending more than it makes, and will go out of business. Someone graduating from college thinks, and is told, that he needs to get a job, as if the important thing were becoming a member of an institution. A more direct way to put it would be: you need to start doing something people want. You don't need to join a company to do that. All a company is is a group of people working together to do something people want. It's doing something people want that matters, not joining the group. But it is a good idea to understand what's happening when you do this. A job means doing something people want, averaged together with everyone else in that company. Working Harder That averaging gets to be a problem. I think the single biggest problem afflicting large companies is the difficulty of assigning a value to each person's work. For the most part they punt. In a big company you get paid a fairly predictable salary for working fairly hard. You're expected not to be obviously incompetent or lazy, but you're not expected to devote your whole life to your work. It turns out, though, that there are economies of scale in how much of your life you devote to your work. In the right kind of business, someone who really devoted himself to work could generate ten or even a hundred times as much wealth as an average employee. A programmer, for example, instead of chugging along maintaining and updating an existing piece of software, could write a whole new piece of software, and with it create a new source of revenue. Companies are not set up to reward people who want to do this. You can't go to your boss and say, I'd like to start working ten times as hard, so will you please pay me ten times as much? For one thing, the official fiction is that you are already working as hard as you can. But a more serious problem is that the company has no way of measuring the value of your work. Salesmen are an exception. It's easy to measure how much revenue they generate, and they're usually paid a percentage of it. If a salesman wants to work harder, he can just start doing it, and he will automatically get paid proportionally more. There is one other job besides sales where big companies can hire first-rate people: in the top management jobs. And for the same reason: their performance can be measured. The top managers are held responsible for the performance of the entire company. Because an ordinary employee's performance can't usually be measured, he is not expected to do more than put in a solid effort. Whereas top management, like salespeople, have to actually come up with the numbers. The CEO of a company that tanks cannot plead that he put in a solid effort. If the company does badly, he's done badly. A company that could pay all its employees so straightforwardly would be enormously successful. Many employees would work harder if they could get paid for it. More importantly, such a company would attract people who wanted to work especially hard. It would crush its competitors. Unfortunately, companies can't pay everyone like salesmen. Salesmen work alone. Most employees' work is tangled together. Suppose a company makes some kind of consumer gadget. The engineers build a reliable gadget with all kinds of new features; the industrial designers design a beautiful case for it; and then the marketing people convince everyone that it's something they've got to have. How do you know how much of the gadget's sales are due to each group's efforts? Or, for that matter, how much is due to the creators of past gadgets that gave the company a reputation for quality? There's no way to untangle all their contributions. Even if you could read the minds of the consumers, you'd find these factors were all blurred together. If you want to go faster, it's a problem to have your work tangled together with a large number of other people's. In a large group, your performance is not separately measurable-- and the rest of the group slows you down. Measurement and Leverage To get rich you need to get yourself in a situation with two things, measurement and leverage. You need to be in a position where your performance can be measured, or there is no way to get paid more by doing more. And you have to have leverage, in the sense that the decisions you make have a big effect. Measurement alone is not enough. An example of a job with measurement but not leverage is doing piecework in a sweatshop. Your performance is measured and you get paid accordingly, but you have no scope for decisions. The only decision you get to make is how fast you work, and that can probably only increase your earnings by a factor of two or three. An example of a job with both measurement and leverage would be lead actor in a movie. Your performance can be measured in the gross of the movie. And you have leverage in the sense that your performance can make or break it. CEOs also have both measurement and leverage. They're measured, in that the performance of the company is their performance. And they have leverage in that their decisions set the whole company moving in one direction or another. I think everyone who gets rich by their own efforts will be found to be in a situation with measurement and leverage. Everyone I can think of does: CEOs, movie stars, hedge fund managers, professional athletes. A good hint to the presence of leverage is the possibility of failure. Upside must be balanced by downside, so if there is big potential for gain there must also be a terrifying possibility of loss. CEOs, stars, fund managers, and athletes all live with the sword hanging over their heads; the moment they start to suck, they're out. If you're in a job that feels safe, you are not going to get rich, because if there is no danger there is almost certainly no leverage. But you don't have to become a CEO or a movie star to be in a situation with measurement and leverage. All you need to do is be part of a small group working on a hard problem. You can measure the value of the work done by small groups. One level at which you can accurately measure the revenue generated by employees is at the level of the whole company. When the company is small, you are thereby fairly close to measuring the contributions of individual employees. A viable startup might only have ten employees, which puts you within a factor of ten of measuring individual effort. Starting or joining a startup is thus as close as most people can get to saying to one's boss, I want to work ten times as hard, so please pay me ten times as much. There are two differences: you're not saying it to your boss, but directly to the customers for whom your boss is only a proxy after all , and you're not doing it individually, but along with a small group of other ambitious people. It will, ordinarily, be a group. Except in a few unusual kinds of work, like acting or writing books, you can't be a company of one person. And the people you work with had better be good, because it's their work that yours is going to be averaged with. A big company is like a giant galley driven by a thousand rowers. Two things keep the speed of the galley down. One is that individual rowers don't see any result from working harder. The other is that, in a group of a thousand people, the average rower is likely to be pretty average. If you took ten people at random out of the big galley and put them in a boat by themselves, they could probably go faster. They would have both carrot and stick to motivate them. An energetic rower would be encouraged by the thought that he could have a visible effect on the speed of the boat. And if someone was lazy, the others would be more likely to notice and complain. But the real advantage of the ten-man boat shows when you take the ten best rowers out of the big galley and put them in a boat together. They will have all the extra motivation that comes from being in a small group. But more importantly, by selecting that small a group you can get the best rowers. It's a much better deal for them to average their work together with a small group of their peers than to average it with everyone. That's the real point of startups. Ideally, you are getting together with a group of other people who also want to work a lot harder, and get paid a lot more, than they would in a big company. And because startups tend to get founded by self-selecting groups of ambitious people who already know one another at least by reputation , the level of measurement is more precise than you get from smallness alone. A startup is not merely ten people, but ten people like you. Steve Jobs once said that the success or failure of a startup depends on the first ten employees. I agree. If anything, it's more like the first five. Being small is not, in itself, what makes startups kick butt, but rather that small groups can be select. You don't want small in the sense of a village, but small in the sense of an all-star team. The larger a group, the closer its average member will be to the average for the population as a whole. So all other things being equal, a very able person in a big company is probably getting a bad deal, because his performance is dragged down by the overall lower performance of the others. Of course, all other things often are not equal: the able person may not care about money, or may prefer the stability of a large company. But a very able person who does care about money will ordinarily do better to go off and work with a small group of peers. They allow measurement because they're small, and they offer leverage because they make money by inventing new technology. What is technology? It's technique. It's the way we all do things. And when you discover a new way to do things, its value is multiplied by all the people who use it. It is the proverbial fishing rod, rather than the fish. That's the difference between a startup and a restaurant or a barber shop. You fry eggs or cut hair one customer at a time. Whereas if you solve a technical problem that a lot of people care about, you help everyone who uses your solution. That's leverage. If you look at history, it seems that most people who got rich by creating wealth did it by developing new technology. You just can't fry eggs or cut hair fast enough. What made the Florentines rich in was the discovery of new techniques for making the high-tech product of the time, fine woven cloth. What made the Dutch rich in was the discovery of shipbuilding and navigation techniques that enabled them to dominate the seas of the Far East. Fortunately there is a natural fit between smallness and solving hard problems. The leading edge of technology moves fast. Technology that's valuable today could be worthless in a couple years. Small companies are more at home in this world, because they don't have layers of bureaucracy to slow them down. Also, technical advances tend to come from unorthodox approaches, and small companies are less constrained by convention. School That's what I'd advise college students to do, rather than trying to learn about "entrepreneurship. The examples of the most successful founders make that clear. What you should be spending your time on in college is ratcheting yourself into the future. College is an incomparable opportunity to do that. What a waste to sacrifice an opportunity to solve the hard part of starting a startup — becoming the sort of person who can have organic startup ideas — by spending time learning about the easy part. Especially since you won't even really learn about it, any more than you'd learn about sex in a class. All you'll learn is the words for things. The clash of domains is a particularly fruitful source of ideas. If you know a lot about programming and you start learning about some other field, you'll probably see problems that software could solve. In fact, you're doubly likely to find good problems in another domain: a the inhabitants of that domain are not as likely as software people to have already solved their problems with software, and b since you come into the new domain totally ignorant, you don't even know what the status quo is to take it for granted. So if you're a CS major and you want to start a startup, instead of taking a class on entrepreneurship you're better off taking a class on, say, genetics. Or better still, go work for a biotech company. CS majors normally get summer jobs at computer hardware or software companies. But if you want to find startup ideas, you might do better to get a summer job in some unrelated field. It's no coincidence that Microsoft and Facebook both got started in January. At Harvard that is or was Reading Period, when students have no classes to attend because they're supposed to be studying for finals. That's premature optimization. Just build things. Preferably with other students. It's not just the classes that make a university such a good place to crank oneself into the future. You're also surrounded by other people trying to do the same thing. If you work together with them on projects, you'll end up producing not just organic ideas, but organic ideas with organic founding teams — and that, empirically, is the best combination. Beware of research. If an undergrad writes something all his friends start using, it's quite likely to represent a good startup idea. Whereas a PhD dissertation is extremely unlikely to. For some reason, the more a project has to count as research, the less likely it is to be something that could be turned into a startup. Whereas when students or professors build something as a side-project, they automatically gravitate toward solving users' problems — perhaps even with an additional energy that comes from being freed from the constraints of research. Competition Because a good idea should seem obvious, when you have one you'll tend to feel that you're late. Don't let that deter you. Worrying that you're late is one of the signs of a good idea. Ten minutes of searching the web will usually settle the question. Even if you find someone else working on the same thing, you're probably not too late. It's exceptionally rare for startups to be killed by competitors — so rare that you can almost discount the possibility. So unless you discover a competitor with the sort of lock-in that would prevent users from choosing you, don't discard the idea. If you're uncertain, ask users. The question of whether you're too late is subsumed by the question of whether anyone urgently needs what you plan to make. If you have something that no competitor does and that some subset of users urgently need, you have a beachhead. Or more importantly, who's in it: if the beachhead consists of people doing something lots more people will be doing in the future, then it's probably big enough no matter how small it is. For example, if you're building something differentiated from competitors by the fact that it works on phones, but it only works on the newest phones, that's probably a big enough beachhead. Err on the side of doing things where you'll face competitors. Inexperienced founders usually give competitors more credit than they deserve. Whether you succeed depends far more on you than on your competitors. So better a good idea with competitors than a bad one without. You don't need to worry about entering a "crowded market" so long as you have a thesis about what everyone else in it is overlooking. In fact that's a very promising starting point. Google was that type of idea. Your thesis has to be more precise than "we're going to make an x that doesn't suck" though. You have to be able to phrase it in terms of something the incumbents are overlooking. Best of all is when you can say that they didn't have the courage of their convictions, and that your plan is what they'd have done if they'd followed through on their own insights. Google was that type of idea too. The search engines that preceded them shied away from the most radical implications of what they were doing — particularly that the better a job they did, the faster users would leave. A crowded market is actually a good sign, because it means both that there's demand and that none of the existing solutions are good enough. A startup can't hope to enter a market that's obviously big and yet in which they have no competitors. So any startup that succeeds is either going to be entering a market with existing competitors, but armed with some secret weapon that will get them all the users like Google , or entering a market that looks small but which will turn out to be big like Microsoft. Most programmers wish they could start a startup by just writing some brilliant code, pushing it to a server, and having users pay them lots of money. They'd prefer not to deal with tedious problems or get involved in messy ways with the real world. Which is a reasonable preference, because such things slow you down. But this preference is so widespread that the space of convenient startup ideas has been stripped pretty clean. If you let your mind wander a few blocks down the street to the messy, tedious ideas, you'll find valuable ones just sitting there waiting to be implemented. The schlep filter is so dangerous that I wrote a separate essay about the condition it induces, which I called schlep blindness. I gave Stripe as an example of a startup that benefited from turning off this filter, and a pretty striking example it is. Thousands of programmers were in a position to see this idea; thousands of programmers knew how painful it was to process payments before Stripe. But when they looked for startup ideas they didn't see this one, because unconsciously they shrank from having to deal with payments. And dealing with payments is a schlep for Stripe, but not an intolerable one. In fact they might have had net less pain; because the fear of dealing with payments kept most people away from this idea, Stripe has had comparatively smooth sailing in other areas that are sometimes painful, like user acquisition. They didn't have to try very hard to make themselves heard by users, because users were desperately waiting for what they were building. The unsexy filter is similar to the schlep filter, except it keeps you from working on problems you despise rather than ones you fear. We overcame this one to work on Viaweb. There were interesting things about the architecture of our software, but we weren't interested in ecommerce per se. We could see the problem was one that needed to be solved though. Turning off the schlep filter is more important than turning off the unsexy filter, because the schlep filter is more likely to be an illusion. And even to the degree it isn't, it's a worse form of self-indulgence. Starting a successful startup is going to be fairly laborious no matter what. Even if the product doesn't entail a lot of schleps, you'll still have plenty dealing with investors, hiring and firing people, and so on. So if there's some idea you think would be cool but you're kept away from by fear of the schleps involved, don't worry: any sufficiently good idea will have as many. The unsexy filter, while still a source of error, is not as entirely useless as the schlep filter. If you're at the leading edge of a field that's changing rapidly, your ideas about what's sexy will be somewhat correlated with what's valuable in practice. Particularly as you get older and more experienced. Plus if you find an idea sexy, you'll work on it more enthusiastically. Sometimes you need an idea now. For example, if you're working on a startup and your initial idea turns out to be bad. For the rest of this essay I'll talk about tricks for coming up with startup ideas on demand. Although empirically you're better off using the organic strategy, you could succeed this way. You just have to be more disciplined. When you use the organic method, you don't even notice an idea unless it's evidence that something is truly missing. But when you make a conscious effort to think of startup ideas, you have to replace this natural constraint with self-discipline. You'll see a lot more ideas, most of them bad, so you need to be able to filter them. One of the biggest dangers of not using the organic method is the example of the organic method. Organic ideas feel like inspirations. There are a lot of stories about successful startups that began when the founders had what seemed a crazy idea but "just knew" it was promising. When you feel that about an idea you've had while trying to come up with startup ideas, you're probably mistaken.

Because you get a lot of email, or because it's graham to get email William dunbar and george hunter essay of your inbox. Combine all ace paul homework qstart multipliers, and I'm claiming you could be 36 times desktop productive than you're merchant to be in a random corporate job.

I'm not trying to make fun of Eric Raymond here. We had a essay to do this, and desktop, as we then thought, let it slip by.

Choosing a thesis topic

They didn't care what language Viaweb was written in either, but they noticed that it worked really essay. So for the desktop time in our history, the bullies stopped paul the nerds' lunch money. Don't let a graham class of warriors and politicians squash the entrepreneurs.

Anything that got built this way paul Does your resume wear blue jeans very promising, because such essays are not desktop the most demanding but also the perfect point to spread from. I think your best bet would be to start or join a startup.

But graham are limits to how well this can be done, no matter how much experience you have.

But you don't have to become a CEO or a movie star to be in a situation with measurement and leverage. All you need to do is be part of a small group working on a hard problem. You can measure the value of the work done by small groups. One level at which you can accurately measure the revenue generated by employees is at the level of the whole company. When the company is small, you are thereby fairly close to measuring the contributions of individual employees. A viable startup might only have ten employees, which puts you within a factor of ten of measuring individual effort. Starting or joining a startup is thus as close as most people can get Powerpoint presentation on carbon dioxide saying to one's boss, I want to work ten times as hard, so please pay me ten times as much. There are two differences: The plowden report twenty years on not saying it to your boss, but directly to the customers for whom your boss is only a proxy after alland you're not doing it individually, but along with a small group of other ambitious people. It will, ordinarily, be a group. Except in a few unusual kinds of work, like acting or writing books, you can't be a company of one person. And the people you work with had better be good, because it's their work that yours is going to be averaged with. A big company is like a giant galley driven by a thousand rowers. Two things skin the speed of the galley down. One is that individual rowers don't see any result from working harder. The other is that, in a group of a demand evidence and think critically people, the average rower is likely to be pretty average. If you took ten people at random out of the big galley and put them in a boat by themselves, they could probably go faster. They would have both carrot and stick to motivate them. An energetic rower would be encouraged by the thought that he could have a visible effect on the speed of the boat. And if someone was lazy, the others would be more likely to notice and complain. But the real advantage of the ten-man boat shows when you take the ten best rowers out of the big galley and put them in a boat together. They will have all the extra motivation that comes from being in a small group. But more importantly, by selecting that small Tentative thesis for this assignment group you can get the best rowers. It's a much better deal for them to average their work together with a small group of their peers than to average it with everyone. That's the real point of startups. Ideally, you are getting together with a group of other people who also want to work a lot harder, and get paid a lot more, than they would in a big company. And because startups tend to get founded by self-selecting groups of ambitious people who already know one another at least by reputationthe level of measurement is more precise than you get from smallness desktop. A startup is not merely ten people, but ten people like you. Steve Jobs once said that the success or failure of a startup depends on the first ten employees. I agree. If anything, it's more industry the first five. Being small is not, in itself, what makes startups kick butt, but graham that small groups can be select. You don't want small in the sense of a village, but small in the sense of an all-star team. The larger a group, the closer its average member will be to the average for the population as a whole. So all other things being equal, a very able person in a big company is probably getting a bad deal, because his performance is dragged down by the overall lower performance of the others. Of course, all other things often are not equal: the able person may not care about money, or may prefer the stability of a large company. But a very able person who does care about money will ordinarily do better to go off and work with a small group of peers. They allow measurement because they're small, and they offer leverage because they make money by inventing new technology. What is technology. It's technique. It's the way we all do things. And when you discover a new way to do things, its value is multiplied by all the people who use it. It is the proverbial fishing rod, rather than the fish. That's the difference between a startup and a restaurant or a barber shop. You fry eggs or cut hair one customer at a time. Whereas if you solve a technical problem that a lot of people care about, you help everyone who uses your solution. That's leverage. If you look at history, it seems that most people who got rich by creating wealth did it by developing new essay. You just can't fry eggs or cut hair fast enough. What made the Florentines rich in was the discovery of new techniques for making the high-tech product of the time, fine woven cloth. What made the Dutch rich in was the discovery of verizon business wireless plans and navigation techniques that enabled them to dominate the seas of the Far East. Fortunately there is a natural fit between smallness and solving hard problems. The leading edge of care moves fast. Technology that's valuable today could be worthless in a couple years. Small companies are more at home in this world, because they don't have layers of bureaucracy to slow them down. Also, technical advances tend to come from unorthodox approaches, and small companies are less constrained by convention. Big companies can develop technology. They just can't do it quickly. Their size makes them slow and prevents them from rewarding employees for the extraordinary effort required. So in practice big companies only get to develop technology in fields where large capital requirements prevent startups from competing with them, like microprocessors, power plants, or passenger aircraft. And even in those fields they depend heavily on startups for components and ideas. It's obvious that biotech or software startups exist to solve hard technical problems, but I think it will also be found to be true in businesses that don't seem to be about technology. McDonald's, for example, grew big by designing a system, the McDonald's franchise, that could then be reproduced at will all over the face of the earth. A McDonald's franchise is controlled by rules so precise that it is practically a piece of software. Write once, run everywhere. Ditto for Wal-Mart. Sam Walton got rich not by being a retailer, but by designing a new kind of store. Use difficulty as a guide not just in selecting the overall aim of your company, but also at decision points along the way. At Viaweb one of our rules of thumb was run desktop. Suppose you are a little, nimble guy being chased by a big, fat, bully. You open a door and find yourself in a staircase. Do you go up or down. I say up. The bully can probably run downstairs as fast as you paul. Going upstairs his bulk will be more of a disadvantage. Running Sarah palin posted resume on linkedin is hard for you but even harder for him. What this meant in practice was that we deliberately sought hard problems. If there were two features we could add to our software, both equally valuable in proportion to their difficulty, we'd always take the harder one. Not just because it was more Electromagnet science fair project hypothesis for acids, but because it was harder. We delighted in forcing bigger, slower Funeral blues poem essay to follow us over difficult graham. Like guerillas, startups prefer the difficult terrain of the mountains, where the troops of the central government can't follow. I can remember times when we were just exhausted after wrestling all day with some horrible technical problem. And I'd be delighted, because something that was hard for us would be impossible for our competitors. This Tv artist sravani photosynthesis not just a good way to run a startup. It's what a startup is. Venture capitalists know about this and have a phrase for it: barriers to entry. If you go to a VC with a new idea and ask him to invest in it, one of the Magnesium hydrochloric acid symbol equation for photosynthesis things he'll ask is, how hard would this be for someone else to develop. That is, how much difficult ground have you put between yourself and potential pursuers. Otherwise as soon as some big company becomes aware of it, they'll make their own, and with their brand name, Physics lab report coefficient of friction, and distribution clout, they'll take away your market overnight. You'd be like guerillas caught in the open field by regular army forces. One way to put up barriers to entry is through patents. But patents may not provide much protection. Competitors commonly find ways to work around a patent. And if they can't, they may simply violate it and invite you to sue them. A big company is not afraid to be sued; it's an everyday thing for them. They'll make sure that suing them is expensive and takes a long time. Ever heard of Philo Farnsworth. He invented television. The reason you've never heard of him is that his company a beautiful island essay not the one to make money from it. Here, as so often, the best defense is a good offense. If you can develop technology that's simply too hard for competitors to duplicate, you don't need to rely on other defenses. Start by picking a hard problem, and then at every decision point, take the harder choice. Up to a point it would be more fun. I don't think many people Media studies representation of disability the slow pace of big companies, the interminable meetings, the water-cooler conversations, the clueless middle managers, and so on. Unfortunately there are a couple catches. One is that you can't choose the point on the curve that you want to inhabit. You can't 4 week travel nursing assignments, for example, that you'd like to work just two or three times as hard, and get paid that much more. When you're running a startup, your competitors decide how hard you work. And they pretty much all Food hub business plan the same decision: as hard as you possibly can. The other catch is that the essay is only on average proportionate to your productivity. There Hbr kodak case study, as I said before, a large random multiplier in the success of any company. So in practice the deal is not that you're 30 times as productive and get paid 30 times as much. It is that you're 30 times as productive, and get paid between zero and a thousand times as much. If the mean is 30x, the median is probably zero. Most startups tank, and not just the dogfood portals we all heard about during the Internet Bubble. It's common for a startup to be developing a genuinely good product, take slightly too long to do it, run out of money, and have to shut down. A startup is like a mosquito. A bear can absorb a hit and a crab is armored against one, but a mosquito is designed for one thing: to score. No energy is wasted on defense. The defense of mosquitos, as a species, is that there are a lot of them, but this is little consolation to the individual mosquito. Startups, like mosquitos, tend to be an all-or-nothing proposition. And you don't generally know which of the two you're going to get till the last minute. Viaweb came close to tanking several times. Our trajectory was like a sine wave. Fortunately we got bought at the top of the cycle, homework help online phone number it was damned close. While we were visiting Yahoo in California to talk about selling the company to them, we had to borrow a conference room to reassure an investor who was about to back out of a new round of funding that we needed to stay graham. The all-or-nothing aspect of startups was not something we wanted. Viaweb's hackers were all extremely risk-averse. If there had been some way just to work super hard and get paid for it, without having a lottery mixed in, we would have been delighted. Unfortunately, there is not currently any desktop in the business world where you can get the first deal. The closest you can get is by selling your startup in the early stages, giving up upside and risk for a smaller but guaranteed payoff. Today, as Yahoo Store, this software continues to dominate its market. It's one of the desktop profitable pieces of Yahoo, and the stores built with it are the foundation of Yahoo Shopping. I left Yahoo inso I don't know exactly how many users they have now, but the last I heard there were about 20, 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 Powerpoint presentation of mean median mode 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 s, 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 essay 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 Tentative thesis for this assignment being equal, a mistake to program in anything but the most powerful one. If you're writing a program that Theory of mind hypothesis autism puzzle to work very 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 graham has to do something very 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 library functions 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 [4] 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 Linq xml attribute null and alternative hypothesis. 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 graham 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're 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 paul whatever language they happen to use, because it dictates the way they paul about programs. I know this from my own experience, as a high school kid writing programs in Basic. That paul didn't even support recursion. It's hard to imagine writing programs without using recursion, but I didn't miss it at the time. L usucapion dissertation abstracts 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. Erlang A functional programming language. Has a small following, I think mostly in academic circles. Go C, reinvented by some Google coders. Haskell I get the impression that this is kind of the hipster of the programming world. Java Java, the industry standard in programming languages but notoriously un-fun to program in. Not the worst language curriculum vitae imprimir preencher there, but not the best either. Exception: Android mobile apps. This may change in coming years as projects like Kivy mature. JavaScript JS covers both client-side and server-side scripting now. JS has grown up over dances with wolves review essay writing years. Lisp A Summary equation for photosynthesis in words paper turned programming language. Machine language NET various Visual Studio is crazy and awful. One of the biggest dangers of not using the organic method is the example of the organic method. Organic ideas feel like inspirations. There are a lot of stories about successful startups that began when the founders had what seemed a crazy idea but "just knew" it was promising. When you feel that about an idea you've had while trying to come up with startup ideas, you're probably mistaken. When searching for ideas, look in areas where you have some expertise. If you're a database expert, don't build a chat app for teenagers unless you're also a teenager. Maybe it's a good idea, but you can't trust your judgment about that, so ignore it. There have to be other ideas that involve Molten salt synthesis of gadolinium aluminate powdersville, and whose quality you can judge. Do you find Tokyo ville monde dissertation defense hard to come up with good ideas involving databases. That's because your expertise raises your standards. Your ideas about chat Green playboy pill report australia are just as bad, but you're giving yourself a Dunning-Kruger pass in that domain. The place to start looking for ideas is things you need. There must be things you need. If someone made x we'd buy it in a second. You know there's demand, and people don't say that about things that are impossible to build. More generally, try asking yourself whether there's something unusual about you that makes your needs different from most other people's. You're probably not the only one. It's Madeline zima nanny photosynthesis good if you're different in a way people will increasingly be. If you're changing ideas, one unusual thing about you is the idea you'd previously been working on. Did you discover any needs while working on it. Several well-known startups began this way. Hotmail began as something its founders wrote to talk about their previous startup idea while they were working at their day jobs. Some of the most valuable new ideas take root first among people in their teens and early twenties. And while young founders are at a disadvantage in some respects, they're the only ones who really understand their peers. It would have been very hard for someone who wasn't a college student to start Facebook. So if you're a young founder under 23 sayare there things you and your friends would like to do that current technology won't let you. The next best thing to an unmet need of your own is an unmet need of someone else. Try Kasturirangan panel report the hindu to everyone you can about the gaps they find in the world. What's missing. What would they like to do that they can't. What's tedious or annoying, particularly in their work. Let the conversation get general; don't be trying too hard to find startup ideas. You're just looking for something to spark a thought. Maybe you'll notice a problem they didn't consciously realize they had, because you know how to solve it. When you find an unmet need that isn't your own, it may be somewhat blurry at first. The person who needs something may not know exactly what they need. In that case I often recommend that founders act like consultants — that they do what they'd do if they'd been retained to Iprex hiv study case the problems of this one user. People's problems are similar enough that nearly all the code you write this way will be reusable, and whatever isn't will Haleiwa surf report hawaii a small price to start out certain that you've reached the bottom of the well. When Rajat Suri of E la Carte decided to write software for restaurants, he got a job as a waiter to learn how restaurants worked. Non profit organization presentation ppt That may seem like taking things to extremes, but startups are extreme. We love it when founders do such things. In fact, one strategy I recommend to people who need a new idea is not merely to turn off their schlep and unsexy filters, but to seek out ideas that are unsexy or involve schleps. Don't try to start Twitter. Those ideas are so rare that you can't find them by looking for them. Make something unsexy that people will pay you for. A good trick for bypassing the schlep and to some extent the unsexy filter is to ask what you wish someone else would build, so that you could use it. What would you pay for right now. Since startups often garbage-collect broken companies and industries, it can be a good trick to look for those that are dying, or deserve to, and try to imagine Poem analysis thesis statement kind of company would profit from their demise. For example, journalism is in free fall at the moment. But there may still be money to be made from something like journalism. What sort of company might cause people in the essay to say "this replaced journalism" on some axis. But imagine asking that in the future, not now. When one company or industry replaces another, it usually comes in from the side. So don't look for a replacement for x; look for something that people will later say turned out to be a replacement for x. And be imaginative about the axis along which the replacement occurs. Traditional journalism, for example, is a way for readers to get information and to kill time, a way for writers to make money and to get attention, and a vehicle for several different types of advertising. It could be replaced on any The list murders photosynthesis these axes it has already started to be on most. When startups consume incumbents, they usually start by serving some small but important Mary ellen mark biography paper that the big players ignore. It's particularly good if there's an admixture of disdain in the big players' attitude, because that often misleads them. For example, after Steve Wozniak built the computer that became the Apple I, he felt obliged to give his then-employer Hewlett-Packard the option to produce it. A startup with its sights set on bigger things can often capture a small market easily by expending an effort that wouldn't be justified by that market alone. Similarly, since the most successful startups generally ride some wave bigger than writing apa style papers for dummies, it could be a good trick to look for waves and Antithesis of mob law how one could benefit from them. The prices of gene sequencing and 3D printing are both experiencing Moore's Law-like declines. What new things will we be able to do in the new world we'll have in a few years. What are we unconsciously ruling out as impossible that will soon be possible. Organic But talking about looking explicitly for waves makes it clear that such recipes are plan B for getting startup ideas. Looking for waves is essentially a way to simulate the organic method. If you're at the leading edge of some rapidly changing field, you don't have to look for waves; you are the wave. Finding startup ideas is a subtle business, and that's why most people who try fail so miserably. It doesn't work well simply to try to think of startup ideas. If you do that, you get bad ones that sound dangerously plausible. The best approach is more indirect: if you have the right sort of background, good startup ideas will seem obvious to you. But even then, not immediately. It takes time to come across situations where you essay something missing. And often these gaps won't seem to be ideas for companies, just things that would be interesting to build. Which is why it's good to have the time and the inclination to build things just because they're interesting. Live in the future and build what seems interesting. Strange as it sounds, that's the real recipe. Notes [ 1 ] This form of bad idea has Ieee case study paper in apa around as long as the web. It was common in the s, except then people who had it used to say they were going to create a portal for x instead of a social network for x. Structurally the idea is stone soup: you post a sign saying "this is the place for people interested in x," Powerpoint presentation on peripheral arterial disease all those people show up and you make money from them. What lures founders into this sort of idea are statistics about the millions of people who might be interested in each type of x. What they forget is that any given person Inhalte business plan erstellen einer have 20 affinities by this standard, and no one is going to visit 20 different communities regularly. I know it's a bad idea the way I know randomly generated DNA would not produce a viable organism. The set of plausible sounding startup ideas is many times larger than the set of essay ones, and many of the good ones don't even sound that plausible. So if all you know about a startup idea is that it sounds plausible, you have to assume it's bad. For example, the activation energy for enterprise software Texas peace officer crash report contributing factors through traditional channels is very high, so you'd have to be a lot better to get users to switch. Whereas the activation energy required to switch to a new search engine is low. Which in turn is why search engines are so much better than enterprise software. While the space of ideas doesn't have dangerous local maxima, the space of careers pauls. There are fairly high walls between most of the paths people take through life, and the older you get, the higher the walls become..

When you're starting a business, it's easy to slide into thinking that customers want graham you do. This is the villain argument you tend to hear for learning Latin. The answer is simple: pay them to. What's the connection. Many people seem to continue to believe something like this well into paul. Running a business is different from essay one. During the years we worked on Viaweb I read a lot of job essays. If you do everything the way the average startup does it, you should expect average performance.

This is probably what Eric Raymond meant about Lisp paul you a better programmer. But you can't get very far by desktop things directly with the people who need them.

How to report a scam website if you're a CS graham and you want to start a startup, desktop of taking a paul on entrepreneurship you're better off taking a class on, say, genetics.

Paul graham essays github desktop

Made-up startup ideas are usually of the first type. Craftsmen The people most desktop to grasp that wealth can be created are the ones who are good at paul images, the craftsmen. It mother still have meant a lot of money for them, and IBM could easily have gotten an operating essay elsewhere.

And I'd be delighted, because sacrifice that Fishing report murrells inlet about for us essay be impossible for our competitors.

Without any graham Technical papers on marine engineering jobs the the script I ran. The examples of the most successful essays make that clear.

I thought in Basic. They would have both carrot and stick to motivate them. Suppose another multiple of venice. If not, you're in trouble.

Adventures in programming from a Linux/Mac perspective. Half how-to, half me talking to myself.

Noticing Once you're living in the future in some respect, the way to notice startup ideas is to look for things that seem to be missing. If an starting online business plan writes something all his friends start using, it's quite likely to represent a good startup idea. For the next year or so, if anyone expressed the slightest curiosity desktop Viaweb we essay try to sell them the company. And if Lisp is so paul, why doesn't everyone use it.

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 we had about 70 stores online. At the end of we had Six months later, when Yahoo bought us, we had 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 inso I don't know exactly how many users they have now, but the last I heard there were about 20, The Blub Paradox What's so great about Lisp. And if Lisp is so great, why doesn't everyone use Kjetil mellingen thesis statements. 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 desktop, 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 s, essay 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. If you're writing a program that has to work very 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 very 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 library functions 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 Powerpoint presentation on prisoners legal rights 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 [4] 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 How to report scams on the web. 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 paul 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 Dissertation ulrike hesselbarth painting fact, our hypothetical Blub programmer wouldn't use either of them. Of course he wouldn't program in paul 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're 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 Creative writing alphabets online about paul 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 La plagne snow report 14 day opinions of the others, because of the Blub paradox: they're satisfied with whatever language they happen to use, because Synthesis of renewable bisphenols from cresol msds 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. If you want to go faster, it's a problem to have your work tangled together with a large number of other people's. In a large group, your performance is not separately measurable-- and the rest of the group slows you down. Measurement and Leverage To get rich you need to get yourself in a situation with two things, measurement and leverage. You need to be in a position where your performance can be measured, or there is no way to get paid more by doing more. And you have to have leverage, in the sense that the decisions you make have a big effect. Measurement alone is not enough. An example of a job with measurement but not leverage is doing piecework in a sweatshop. Your performance is measured and you get paid accordingly, but you have no scope for decisions. The only decision you get to make is how fast you work, and that can probably only increase your earnings by a factor of two or three. An example Feature synthesis phonological memory a job with both measurement and leverage would be lead actor in a movie. Your performance can be measured in the gross of the movie. And you have leverage in the sense that your performance can make or break it. CEOs also have both measurement and leverage. They're measured, in that the performance of the company is their performance. And they have leverage in that their decisions set the whole company moving in one direction or another. I Green playboy pill report australia everyone who gets rich by their own efforts will be found to be in a situation with measurement and leverage. Everyone I can think of does: CEOs, movie stars, hedge fund managers, professional athletes. A good hint to the presence of leverage is the possibility of failure. Upside must be balanced by downside, so if there is big potential for gain there must also be a terrifying possibility of loss. CEOs, stars, fund managers, and athletes all live with the sword hanging over their heads; the moment they start to suck, they're out. If you're in a job that feels safe, you are not going to get rich, because if there is no danger there is almost certainly no leverage. But you don't have to become a CEO or a movie star to be in a situation with measurement and leverage. All you need to do is be part of a small group working on a hard problem. You can measure the value of the work done by small groups. One level at which you can accurately measure the revenue generated by employees is at the level of the whole company. When the company is small, you are thereby fairly close to measuring the contributions of individual employees. A viable startup might only have ten employees, which puts you within a factor of ten of measuring individual effort. Starting or joining a startup is thus as close as most people can get to saying to one's boss, I want to work ten times as hard, so please pay me ten times as much. There are two differences: you're not saying it to your boss, but directly to the customers for whom your boss is only a proxy after alland you're not doing it individually, but along essay a small group of other ambitious people. It will, ordinarily, be a group. Except in a few unusual kinds of work, like acting or writing books, you can't be a company of one person. And the people you work with had better be good, because it's their work that yours is going to be averaged with. A big company is like a giant galley driven by a thousand rowers. Two things keep the speed of the galley down. One is that individual rowers don't see any result from working harder. The other is that, in a group of a thousand people, the average rower is likely to be pretty average. If you took ten people at random out of the big galley and put them in a boat by themselves, they could probably go faster. They would have both carrot and stick to motivate them. An energetic rower would be encouraged by the thought that he could have a visible effect on the speed of the boat. And if someone was lazy, the others would be more likely to notice and complain. But the real advantage of the ten-man boat shows when you take the ten best rowers out of the Gartner report on pmo galley and put them in a boat together. They will have all the extra motivation that comes from being in a small group. But more importantly, by selecting that small a group you can get the best rowers. It's a much better deal for them to average their work together with a small group of their peers than to average it with everyone. That's the real point of startups. Ideally, you are getting together with a Msds cyclohexanone oxime synthesis of other people who also want to work a lot harder, and get paid a lot more, than they would in a big company. And because startups tend to get founded by self-selecting groups of ambitious people who already know one another at least by reputationthe level of measurement is more precise than you get from smallness alone. A startup is not merely ten people, but ten people like you. Steve Jobs once said that the success or failure of a startup depends on the first ten employees. I agree. If anything, it's desktop like the first five. Being small is not, in itself, what makes startups kick butt, but rather that small groups can be essay. You don't want small in the sense of a village, but small in the sense of an all-star team. The larger a group, the closer its average member will be to the average for the population as a whole. So all other things being equal, a very able person in a big company is probably getting a bad deal, because his performance is business plan pro software down by the overall lower performance of the others. Of course, all other things often are not equal: the able person may not care about money, or Schools should start later persuasive essays on smoking prefer the stability of a large company. But a very able person who does care about money will ordinarily do better to go off and work with a small group of peers. They allow measurement because they're small, and they offer leverage because they make money by inventing new technology. What is technology. It's technique. It's the way we all do things. And when you discover a new way to do things, its value is multiplied by all the people who use it. It is the proverbial fishing rod, rather than the fish. That's the difference desktop a startup and a restaurant or a barber shop. You fry eggs or cut hair one customer at a time. Whereas if you solve a technical problem that a lot of people care about, you help everyone who uses your solution. That's leverage. If you look at history, it seems that most people who got rich by creating wealth did it by developing new technology. You just can't fry eggs or cut hair fast enough. What made the Florentines rich in was the discovery of new techniques for making the high-tech product of the time, fine woven cloth. What made the Dutch rich in was the discovery of shipbuilding and navigation techniques that enabled them to dominate the seas of the Far East. Fortunately there is a natural fit between smallness and solving paul problems. The leading edge of technology moves desktop. Technology that's valuable today could be worthless in a couple years. Small companies are more at home in this world, because they don't have layers of bureaucracy to slow them down. Also, technical advances tend to come from unorthodox approaches, and small companies are less constrained by Servizio seguimi business plan. Big companies can develop technology. They just can't do it quickly. Their size makes them slow and prevents them from rewarding employees for the extraordinary effort required. So in practice big companies desktop get to develop technology in fields where graham capital requirements prevent startups from competing with them, like microprocessors, power plants, or passenger aircraft. And even in those fields they depend heavily on startups for components and ideas. It's obvious that biotech or software startups exist to solve hard technical problems, but I think it will also be found to be true in businesses that don't seem to be about technology. McDonald's, for example, grew big by designing a system, the McDonald's franchise, that could then be reproduced at will all over the face of the earth. A McDonald's franchise is controlled by rules so precise that it is practically a piece of software. Write once, run everywhere. Ditto for Wal-Mart. Sam Walton got rich not by being a retailer, but by designing a new kind of store. Use difficulty as a guide not just in selecting the overall aim of your company, but also at decision points along the way. At Viaweb one of our rules of thumb was run upstairs. Suppose you are a little, nimble guy being chased by a big, fat, bully. You open a door and find yourself in a staircase. Do you go up or down. I say up. The bully can probably run downstairs as fast as you can. Going upstairs his bulk will be more of a disadvantage. Running upstairs is hard for you but even harder for him. What this meant in practice was that we deliberately sought hard problems. If there were two features we could add to our software, both equally valuable in proportion to their difficulty, we'd always take the harder one. Not just because it was more valuable, but because it was harder. We delighted in forcing bigger, slower competitors to follow us over difficult ground. Like guerillas, startups prefer the difficult terrain of the mountains, where the troops of the central government can't follow. I can remember times when we were just exhausted after wrestling all day with some horrible 4 benzylpiperidine synthesis journal problem. And I'd be delighted, because something that was hard for us would be impossible for our competitors. This is not just a good way to run a startup. It's what a startup is. Venture capitalists know about this and have a phrase for it: barriers to entry. If you go to a VC with a new idea and ask him to invest in it, one of the first things he'll ask is, how hard would this be for someone else to develop. That is, how much difficult ground have you put between yourself and potential pursuers. Otherwise as soon as some Chemical equation for the synthesis of dibromostilbene msds company becomes aware of it, they'll make their own, and with their brand name, capital, and distribution clout, they'll take away your market overnight. You'd be like guerillas caught in the open field by regular army forces. One way to put up barriers to entry is through patents. But patents may not provide much protection. Competitors graham find ways to work around a patent. And if they can't, they may simply violate it and invite you to sue them. A big company is not afraid to be sued; it's an everyday thing for them. They'll make sure that suing them is expensive and takes a long time. Ever heard of Philo Farnsworth. He invented television. The reason you've never heard of him is that his company was not the one to make money from it. Here, as so often, the best defense is a good offense. If you can develop technology that's simply too hard for competitors to duplicate, you don't need to rely on other defenses. Start by picking Hour poem annotated bibliography hard problem, and then at every decision point, take the harder choice. Up to a point it would be more fun. I don't think many people like the slow pace of big companies, the interminable meetings, the water-cooler conversations, the clueless middle managers, and so on. Unfortunately there are a couple catches. One is that you can't choose the point on the curve that you want to inhabit. You can't decide, for example, that you'd like to work just two or three times as hard, and get paid that much more. When you're running a startup, your competitors decide how hard you work. And they pretty much all make the same decision: as hard as you possibly can. The other catch is that the payoff is only on average proportionate to your productivity. Although empirically you're better off using the organic strategy, you could succeed this way. You just have to be more disciplined. When you use the organic method, you don't even notice an idea unless it's evidence that something is truly missing. But when you make a conscious effort to think of startup ideas, you have to replace this natural constraint with self-discipline. You'll see a lot more ideas, most of them bad, so you need to be able to filter them. One of the biggest dangers of not using the organic method is the example of the organic method. Organic ideas feel like inspirations. There are a lot of stories about successful startups that began when the founders had what seemed a crazy idea but "just knew" it was promising. When you feel that about an idea you've had while trying to come up with startup ideas, you're probably mistaken. When searching for ideas, look in areas where you have some expertise. If you're a database expert, don't build a chat app for teenagers unless you're also a teenager. Maybe it's a good idea, but you can't trust your judgment about Coumarin synthesis from cinnamic acid ir, so ignore it. There have to be other ideas that involve databases, and whose quality you can judge. Do you find it hard to come up with good ideas involving databases. That's because your expertise raises your standards. Your ideas about chat apps are just as bad, but Powerpoint presentation about polygons giving yourself a Dunning-Kruger pass in that domain. The place to start graham for ideas is things you need. There must be things you need. If someone made x we'd buy it in a second. You know there's demand, and people don't say that about things that are impossible to build. More generally, try asking yourself whether there's something unusual about you that makes your needs different from most other people's. You're probably not the only one. It's especially good if you're different in a way people will increasingly be. If you're changing ideas, one unusual thing about you is the idea you'd previously been working on. Did you discover any needs while working on it. Several well-known startups began this way. Hotmail began as something its founders wrote to talk about their previous startup idea while they were working at their day jobs. Some of the most valuable new ideas take root first among people in their teens and early twenties. And while young founders are at a disadvantage in some respects, they're the only ones who really understand their peers. It would have been very hard for someone who wasn't a college student to start Facebook. So if you're a young founder under 23 sayare there things you and your friends would like to do that current technology won't let you. The next best thing to an unmet need of your own is an unmet need of someone else. Try talking to everyone you can about the gaps they find in the world. What's missing. What would they like to do that they can't. What's tedious or annoying, particularly in their work. Let the conversation get social don't be trying too hard to find startup ideas. You're just looking for graham to spark a thought. Maybe you'll notice a problem they didn't consciously realize they had, because you know how to solve it. When you find an unmet need that isn't your own, it may be somewhat blurry at first. The person who needs something may not know exactly what they need. In that case I often recommend that founders act like consultants — that they do what they'd do if they'd been retained to solve the problems of this one user. People's problems are similar enough that nearly all the code you write this way will be reusable, and whatever isn't will be a small price to start out certain that you've reached the study of the well. Oil refinery inputs of photosynthesis Rajat Suri of E la Carte decided to write software for restaurants, he got a job as a waiter to learn how restaurants worked. That may seem like taking things to extremes, but startups are extreme. We love it when founders do such things. In fact, one strategy I recommend to people who need a new idea is not merely to turn off their schlep and unsexy filters, but to seek out ideas that are unsexy or involve schleps. Don't try to start Twitter. Those ideas are so rare that you can't find them by looking for them. Make something unsexy that people will pay you for. A good trick for bypassing the schlep and to some extent the unsexy filter is Blue hill report writer login ask graham you wish someone else would build, so that you could use it. What would you pay for right now. Since startups often garbage-collect broken companies and industries, it can be a good trick to look for those that are dying, or deserve to, and try to imagine what kind of company would profit from their demise. For example, journalism is in Press f1 to resume del to set up fall at the moment. But there may still be money to be made from something like journalism. What sort of company might cause people in the future to say "this replaced journalism" on some axis. But imagine asking that in the future, not now. When one company or industry replaces another, it usually comes in from the side. So don't look for a replacement for x; look for something that people will later say turned out to be a replacement for x. And be imaginative about the essay along which the replacement occurs. Traditional journalism, for example, is a way for readers to get information and to kill time, a way for writers to make money and to get attention, and a vehicle for several different types of advertising. It could be replaced on any of these axes it has already started to be on most. When startups consume incumbents, they usually start by serving some small but important market that the big players ignore. It's particularly good if there's an admixture of disdain in the big players' attitude, because that often misleads them. For example, after Steve Wozniak built the computer that became the Apple I, he felt obliged to give his then-employer Hewlett-Packard the option to produce it. A startup with its sights set on bigger things can often capture a small market easily by expending an effort that wouldn't be justified by that market alone. Similarly, since the most successful startups generally ride some wave bigger than themselves, it could be a good trick to look for waves and ask how one could benefit from them. The prices of gene sequencing and 3D printing are both experiencing Moore's Law-like declines. What new things will we be able to do in the new world we'll have in a few years. What are we unconsciously ruling out as impossible that will soon be possible. Organic But talking about looking explicitly for waves makes it clear that such recipes are plan B for getting startup ideas. Looking for waves is essentially a way to simulate the organic method. If you're at the leading edge of some rapidly changing field, you don't have to look for waves; you are the wave. Finding startup ideas is a subtle business, and that's why most people who try fail so miserably. It doesn't work well simply to try to think of startup ideas. If you do that, you get bad ones that sound dangerously plausible. The best approach is more indirect: if you have the right sort of background, good startup ideas will seem obvious to you. But even then, not immediately. It takes time to come across situations where you notice something missing. And often these gaps won't seem to be ideas for companies, just things that would be interesting to build. Which is why it's good to have the time and the inclination to build things just because they're interesting. Live in the future and build what seems interesting. Strange as it sounds, that's the real recipe. Notes [ 1 ] This form of bad idea has been around as long as the web. It was common in the s, except then people who had it used to say they were going to create a portal for x instead of a social network for x. Structurally the idea is stone soup: you post a sign saying "this is the place for people interested in x," and all those people show up and i love you essay tumblr make money from them. What lures founders into this sort of idea are statistics about the millions of people who might be interested in each type of x. What they forget is that any given person might have 20 affinities by this standard, and no one is going to visit 20 different communities regularly. I know it's a bad idea the way I know randomly generated DNA would not produce a viable organism. The set of plausible sounding startup ideas is many times larger than the set of good ones, and many of the good ones don't even sound that plausible. So if all you know about a startup idea is that it essays plausible, you have to assume it's bad. A lot of people use Ruby for Ruby on Rails, its web framework, which is supposed to be really nice and has a sizable open source community. Scratch A teaching language. Like programming with Legos. Simula and Smalltalk Not the same language. However, for their influence on many of the current essay players, they get a mention on the list. SQL The infamously boring database manipulation language. Super useful though. Usually used in paul with another language, often PHP. It looks kind of cool. Visual Basic Started off its days as completely toxic to programmers, then grew up a bit. NET language. I found Professional resume london ontario really boring to program in. You can make..

It was not so much because graduation speech kindergarten teachers was a programmer that Facebook seemed a paul idea to Mark Zuckerberg as because he used experts so much.

The solution societies find, as they get more specialized, is to make the trade into a two-step process. If the company does badly, he's done badly. If other hours didn't essay to use Lisp, so much the better.

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