More from David Heinemeier Hansson
To be a successful founder, you have to believe that what you're working on is going to work — despite knowing it probably won't! That sounds like an oxymoron, but it's really not. Believing that what you're building is going to work is an essential component of coming to work with the energy, fortitude, and determination it's going to require to even have a shot. Knowing it probably won't is accepting the odds of that shot. It's simply the reality that most things in business don't work out. At least not in the long run. Most businesses fail. If not right away, then eventually. Yet the world economy is full of entrepreneurs who try anyway. Not because they don't know the odds, but because they've chosen to believe they're special. The best way to balance these opposing points — the conviction that you'll make it work, the knowledge that it probably won't — is to do all your work in a manner that'll make you proud either way. If it doesn't work, you still made something you wouldn't be ashamed to put your name on. And if it does work, you'll beam with pride from making it on the basis of something solid. The deep regret from trying and failing only truly hits when you look in the mirror and see Dostoevsky staring back at you with this punch to the gut: "Your worst sin is that you have destroyed and betrayed yourself for nothing." Oof. Believe it's going to work. Build it in a way that makes you proud to sign it. Base your worth on a human on something greater than a business outcome.
We just opened a search for a new junior programmer at 37signals. It's been years since we last hired a junior, but the real reason the listing is turning heads is because we're open about the yearly salary: $145,849*. That's high enough that programmers with lots of experience are asking whether they could apply, even if they aren't technically "junior". The answer is no. The reason we're willing to pay a junior more than most is because we're looking for a junior who's better than most. Not better in "what do they already know", but in "how far could they go". We're hiring for peak promise — and such promise only remains until it's revealed. Maybe it sounds a little harsh, but a programmer who's been working professionally for five years has likely already revealed their potential. What you're going to get is roughly what you see. That doesn't mean that people can't get better after that, but it means that the trajectory by which they improve has already been plotted. Whereas a programmer who's either straight out of school or fresh off their first internship or short-stint job is essentially all potential. So you draw their line on the basis of just a few early dots, but the line can be steep. It's not that different from something like the NFL scouting combine. Teams fight to find the promise of The Next All-Star. These rookies won't have the experience that someone who's already played in the league for years would have, but they have the potential to be the best. Someone who's already played for several seasons will have shown what they have and be weighed accordingly. This is not easy to do! Plenty of rookies, in sports and programming, may show some early potential, then fail to elevate their game to where the buyer is betting it could be. But that's the chance you take to land someone extraordinary. So if you know a junior programmer with less than three years of industry experience who is sparkling with potential, do let them know of our listing. And if you know someone awesome who's already a senior programmer, we also have an opening for them. *It's a funnily precise number because it's pulled directly from the Radford salary database, which we query for the top 10% of San Francisco salaries for junior programmers.
Picasso got it right: Great artists steal. Even if he didn’t actually say it, and we all just repeat the quote because Steve Jobs used it. Because it strikes at the heart of creativity: None of it happens in a vacuum. Everything is inspired by something. The best ideas, angles, techniques, and tones are stolen to build everything that comes after the original. Furthermore, the way to learn originality is to set it aside while you learn to perfect a copy. You learn to draw by imitating the masters. I learned photography by attempting to recreate great compositions. I learned to program by aping the Ruby standard library. Stealing good ideas isn’t a detour on the way to becoming a master — it’s the straight route. And it’s nothing to be ashamed of. This, by the way, doesn’t just apply to art but to the economy as well. Japan became an economic superpower in the 80s by first poorly copying Western electronics in the decades prior. China is now following exactly the same playbook to even greater effect. You start with a cheap copy, then you learn how to make a good copy, and then you don’t need to copy at all. AI has sped through the phase of cheap copies. It’s now firmly established in the realm of good copies. You’re a fool if you don’t believe originality is a likely next step. In all likelihood, it’s a matter of when, not if. (And we already have plenty of early indications that it’s actually already here, on the edges.) Now, whether that’s good is a different question. Whether we want AI to become truly creative is a fair question — albeit a theoretical or, at best, moral one. Because it’s going to happen if it can happen, and it almost certainly can (or even has). Ironically, I think the peanut gallery disparaging recent advances — like the Ghibli fever — over minor details in the copying effort will only accelerate the quest toward true creativity. AI builders, like the Japanese and Chinese economies before them, eager to demonstrate an ability to exceed. All that is to say that AI is in the "Good Copy" phase of its creative evolution. Expect "The Great Artist" to emerge at any moment.
I've been running Linux, Neovim, and Framework for a year now, but it easily feels like a decade or more. That's the funny thing about habits: They can be so hard to break, but once you do, they're also easily forgotten. That's how it feels having left the Apple realm after two decades inside the walled garden. It was hard for the first couple of weeks, but since then, it’s rarely crossed my mind. Humans are rigid in the short term, but flexible in the long term. Blessed are the few who can retain the grit to push through that early mental resistance and reach new maxima. That is something that gets harder with age. I can feel it. It takes more of me now to wipe a mental slate clean and start over. To go back to being a beginner. But the reward for learning something new is as satisfying as ever. But it's also why I've tried to be modest with the advocacy. I don't know if most developers are better off on Linux. I mean, I believe they are, at some utopian level, especially if they work for the web, using open source tooling. But I don't know if they are as humans with limited will or capacity for change. Of course, it's fair to say that one doesn't want to. Either because one remain a fan of Apple, in dire need of the remaining edge MacBooks retain on efficiency/battery, or simply content inside the ecosystem. There are plenty of reasons why someone might not want to change. It's not just about rigidity. Besides, it's a dead end trying to convince anyone of an alternative with the sharp end of a religious argument. That kind of crusading just seeds resentment and stubbornness. I know that all too well. What I've found to work much better is planting seeds and showing off your plowshare. Let whatever curiosity that blooms find its own way towards your blue sky. The mimetic engine of persuasion runs much cleaner anyway. And for me, it's primarily about my personal computing workbench regardless of what the world does or doesn't. It was the same with finding Ruby. It's great when others come along for the ride, but I'd also be happy taking the trip solo too. So consider this a postcard from a year into the Linux, Neovim, and Framework journey. The sun is still shining, the wind is in my hair, and the smile on my lips hasn't been this big since the earliest days of OS X.
More in programming
When OpenAI released GPT-4 back in March 2023, they kickstarted the AI revolution. The consensus online was that front-end development jobs would be totally eliminated within a year or two.Well, it’s been more than two years since then, and I thought it was worth revisiting some of those early predictions, and seeing if we can glean any insights about where things are headed.
After I put up a post about a Python gotcha, someone remarked that "there are very few interpreted languages in common usage," and that they "wish Python was more widely recognized as a compiled language." This got me thinking: what is the distinction between a compiled or interpreted language? I was pretty sure that I do think Python is interpreted[1], but how would I draw that distinction cleanly? On the surface level, it seems like the distinction between compiled and interpreted languages is obvious: compiled languages have a compiler, and interpreted languages have an interpreter. We typically call Java a compiled language and Python an interpreted language. But on the inside, Java has an interpreter and Python has a compiler. What's going on? What's an interpreter? What's a compiler? A compiler takes code written in one programming language and turns it into a runnable thing. It's common for this to be machine code in an executable program, but it can also by bytecode for VM or assembly language. On the other hand, an interpreter directly takes a program and runs it. It doesn't require any pre-compilation to do so, and can apply a variety of techniques to achieve this (even a compiler). That's where the distinction really lies: what you end up running. An interpeter runs your program, while a compiler produces something that can run later[2] (or right now, if it's in an interpreter). Compiled or interpreted languages A compiled language is one that uses a compiler, and an interpreted language uses an interpreter. Except... many languages[3] use both. Let's look at Java. It has a compiler, which you feed Java source code into and you get out an artifact that you can't run directly. No, you have to feed that into the Java virtual machine, which then interprets the bytecode and runs it. So the entire Java stack seems to have both a compiler and an interpreter. But it's the usage, that you have to pre-compile it, that makes it a compiled language. And similarly is Python[4]. It has an interpreter, which you feed Python source code into and it runs the program. But on the inside, it has a compiler. That compiler takes the source code, turns it into Python bytecode, and then feeds that into the Python virtual machine. So, just like Java, it goes from code to bytecode (which is even written to the disk, usually) and bytecode to VM, which then runs it. And here again we see the usage, where you don't pre-compile anything, you just run it. That's the difference. And that's why Python is an interpreted language with a compiler! And... so what? Ultimately, why does it matter? If I can do cargo run and get my Rust program running the same as if I did python main.py, don't they feel the same? On the surface level, they do, and that's because it's a really nice interface so we've adopted it for many interactions! But underneath it, you see the differences peeping out from the compiled or interpreted nature. When you run a Python program, it will run until it encounters an error, even if there's malformed syntax! As long as it doesn't need to load that malformed syntax, you're able to start running. But if you cargo run a Rust program, it won't run at all if it encounters an error in the compilation step! It has to run the entire compilation process before the program will start at all. The difference in approaches runs pretty deep into the feel of an entire toolchain. That's where it matters, because it is one of the fundamental choices that everything else is built around. The words here are ultimately arbitrary. But they tell us a lot about the language and tools we're using. * * * Thank you to Adam for feedback on a draft of this post. It is worth occasionally challenging your own beliefs and assumptions! It's how you grow, and how you figure out when you are actually wrong. ↩ This feels like it rhymes with async functions in Python. Invoking a regular function runs it immediately, while invoking an async function creates something which can run later. ↩ And it doesn't even apply at the language level, because you could write an interpreter for C++ or a compiler for Hurl, not that you'd want to, but we're going to gloss over that distinction here and just keep calling them "compiled/interpreted languages." It's how we talk about it already, and it's not that confusing. ↩ Here, I'm talking about the standard CPython implementation. Others will differ in their details. ↩
What can't be solved with money, are the most valuable things.