This really resonates with me. We looked into React at my previous company approx 2 years back, and I hopped on the React bandwagon last fall. A lot changed in that time.
I would add that experimenting with new tools, languages etc. is also an important part of the process. Sitting down and applying something new and shiny to a problem you've already tackled with your "outdated dinosaur skills" should give you a good feel where this new toy is on the adoption curve. Estimating where it is on the curve is a lot harder.
The paranoia has even trickled down to beginners too - paralysis by analysis of what they "should be learning" instead of spending time finishing projects. You see it in question threads everywhere - "Ruby vs Python?" "Node vs Rails?". Don't worry about learning languages/frameworks, pick a tool, and USE it to create something.
People should be more concerned with fundamental skills IMHO. I don't think there are Ruby and Javascript programmers. You're either a programmer or you're not. What language/framework is just a means to an end.
True, but as a programmer, I believe you have to at some point start filtering out jobs that are hiring for <insert technology>. That doesn't leave many jobs and one has to be willing to look long and hard for them, but when you find them, you'll be more satisfied.
Yep. Here and on reddit people are happy to say "we hire for programming skill, not framework or language knowledge!" and they may be right.
However, almost every time I have been rejected or offered a job and given a reason has been for a lack of domain knowledge (or in the latter case, possession of that knowledge!) of a particular framework or language.
Maybe I am biased, I work with Clojure since 2012, I use elixir and go, but still, I believe that once you master the paradigm (OOP, FP, or procedural) then it always the same deal, the syntax may change, but find a value in am hash map will always be faster than find a value in an unsorted list.
For a programmer, once the basis are solid, learn a "new" language should be matter of a couple of weeks...
I think the big problem with the idea of "learning a language" is that most programmers conflate a language with any bits of CS theory that are only to be found in that language.
For example, when most people say they have a hard time "learning Erlang", it's not the syntax they're complaining about (no, really!); they're really complaining about trying to wrap their heads around the actor model, which writing idiomatic Erlang code requires.
Personally, I think the two efforts should be decoupled. If you actually want people to learn Erlang, then instead of teaching "Erlang and the actor model" all in one go, you should strive to make some actor-model framework or another available in the languages people are already familiar with. People could then experiment with the unfamiliar CS theory first in a comfortable syntax—and then, having done so, Erlang would become just another of those mundane "matter of a couple of weeks" languages.
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The real further step we could take, if we wanted to advance the field as a whole, would be to decouple syntax, from "taxonomy", from platform—such that there's no single thing known as a "language" to learn.
* platforms are choices about sets of runtime VM features like GC and threading, where things on the same platform have native interop (e.g. Java and Clojure);
* taxonomies (or if you prefer, "vocabularies" or "dialects") are choices about the contents and organization of the stdlib, and which native types get used as "lowest-common denominator" types for passing to stdlib functions (e.g. whether you pass dicts or lists-of-pairs for options; whether closures are used for everything or some things or nothing; whether {tuples, sets, monads} exist as a thing the stdlib accepts where appropriate, or whether it uses some other lower-level abstraction instead even though the more abstract type is there.) The idiomatic style of a "language" today is mostly about its taxonomy, because library writers take their cues from the stdlib. So things with the same taxonomy can share package ecosystems with no impedance (e.g. JavaScript and CoffeeScript); "siblings" with a mostly-shared taxonomy can share packages with some small effort to speak in LCD types (e.g. Erlang and Elixir.) Unrelated taxonomies need "glue" libraries to explicitly map the impedance, as you see in e.g. Clojure's Java-wrapping libs.
* syntaxes are (hopefully bijective) mappings between tokens and ASTs—as in LISP's original secondary "m-expr" syntax. There's nothing stopping you from mapping any syntax you like to any taxonomy—save for the fact that some syntaxes include operators that do something sensible in one taxonomy (e.g. circumfix operators to create different types of containers; Erlang's "async send" operator) and make no sense for another. I would compare this to the buttons on game controllers: if you use the "wrong" syntax, then some "games" will need "buttons" you don't have on your controller—but with just a bit more fiddling (e.g. typing Set[] vs. #{}) you can still get your meaning across.
People talk about "syntax vs. semantics", but that's a muddle because parts of "semantics" are inextricably represented within syntax. But when you split things this way, you get a clean break: a "language" becomes mostly about taxonomy, where you can port that taxonomy to various platforms, and then target that taxonomy with various syntaxes.
In my ideal world, we'd have a universally-agreed-upon AST format to use as the canonical representation of checked-in code. Each file would mark what taxonomy its identifiers refer to, but would use no taxonomy-specific syntax. Then you'd use something like a FUSE server to map those AST files into a workable representation in a syntax you enjoy. Your text editor wouldn't know the differe...
Agreed. On one of the first classes I had in college, a teacher said we should favor "knowledge" (that is, concepts) over "technics" (that is, knowing a specific way to apply knowledge), and never confuse one with the other. That stuck with me and, in retrospect, was one of the best advises I've had in my career.
Learn it well enough to write it? Sure, a couple of weeks, maybe less.
Learn it well enough to write professional-quality code? That takes longer, because you have to learn what the pitfalls are. (Writing professional code, in large part, boils down to knowing what not to write.)
Learn it well enough to be as productive as you were with the previous language? Maybe three to six months?
And that's the real problem, IMHO. It's going to take me three months of lower productivity to make the switch to the new language/framework/tool/whatever. How long will the new thing take to pay me back for that time it costs? If it's not significantly better than what I'm using now, it's not worth the cost.
To me, being a late adopter is obviously the best path to take. I'm honestly perplexed by devs who are so obsessed with the idea of being the first to hop on a bandwagon. What do you get out of it?
The wisest time for a dev to learn a new technology is probably at the peak of its popularity. That way, you learn from the community when it's most active, and your expertise grows more valuable as the technology slowly goes out of style. Like the author, this happened to me when I first picked up Rails in 2008-2009. I jumped on board at a time when everyone was talking about it, so I never had to look hard to find information. For the next 5 years or so, it seemed like my job prospects were getting better and better, even though the hype train had left Rails behind shortly after.
I have a pet theory that a lot of the shiny-toy syndrome we see in web development is actually fueled by startup founders who deliberately choose unproven technologies to attract talented developers ("Join us, we actually use language XYZ in production!"), since programming geniuses are often eager to delve into Turing tar-pits, and also dazzle tech journalists by promoting it as their magical secret ingredient. (...and yes, I'm aware that perhaps Rails rose to popularity this way)
Early adopting a tech that becomes important = being an rare, high paid experienced expert when it goes mainstream.
Also, these technologies are generally designed to solve some problem, and get adoption because it's a common problem. Struggling with a solved problem rather than using that new tool that solves it is upsetting.
But it's a gamble. If it fails (and so many do, in a month or a year), then you have a head full of domain specific knowledge that you can't apply to any other technology.
Let's take web templating: How many solutions are out there, and how many of those actually turned out to be winners? To ride the crest of the React wave, you had to pick it out of a thousand others, at a time when there were other "winning" solutions.
And even React is beginning to show signs of falling, with new stars starting to shine. Do you jump ship, or hold the course?
I don't think it's that simple. When starting a project, of the available options, which one gives you the most leverage toward building what you're trying to build? What is the cost of using that (training people plus machine resources)? Pick the best cost/benefit tradeoff and start to work.
For an existing project, the bias is to not change unless the new language gives you a massive improvement. Re-writing is always harder than you expect, because the existing code base has more bug fixes and handled corner cases than you think it does, and your re-write has to preserve all of that (or suffer the consequences of failing to do so).
If it were just about trading costs and benefits, you wouldn't see fashions and fads in tech like you do. There's a definite herd effect. Some people wear themselves out trying to be at the front of the herd all the time, when it's enough just not to be at the very back.
the practical programmer is lazy and not passionate. More, he loose the more important skill he have: think. He build softawre by copy pasting from stack overflow.
I am not saying use every nee cool tech posted on HN, but if something looks great for you, you should investigate in it. I am not saying put it on production tomorrow... But if you have similar broblem, look how it works to have a different view of how to build a better solution...
19 comments
[ 3.3 ms ] story [ 43.1 ms ] threadAnd yet they are also completely correct - waiting is better.
I would add that experimenting with new tools, languages etc. is also an important part of the process. Sitting down and applying something new and shiny to a problem you've already tackled with your "outdated dinosaur skills" should give you a good feel where this new toy is on the adoption curve. Estimating where it is on the curve is a lot harder.
Edit: typos
However, almost every time I have been rejected or offered a job and given a reason has been for a lack of domain knowledge (or in the latter case, possession of that knowledge!) of a particular framework or language.
For a programmer, once the basis are solid, learn a "new" language should be matter of a couple of weeks...
For example, when most people say they have a hard time "learning Erlang", it's not the syntax they're complaining about (no, really!); they're really complaining about trying to wrap their heads around the actor model, which writing idiomatic Erlang code requires.
Personally, I think the two efforts should be decoupled. If you actually want people to learn Erlang, then instead of teaching "Erlang and the actor model" all in one go, you should strive to make some actor-model framework or another available in the languages people are already familiar with. People could then experiment with the unfamiliar CS theory first in a comfortable syntax—and then, having done so, Erlang would become just another of those mundane "matter of a couple of weeks" languages.
---
The real further step we could take, if we wanted to advance the field as a whole, would be to decouple syntax, from "taxonomy", from platform—such that there's no single thing known as a "language" to learn.
* platforms are choices about sets of runtime VM features like GC and threading, where things on the same platform have native interop (e.g. Java and Clojure);
* taxonomies (or if you prefer, "vocabularies" or "dialects") are choices about the contents and organization of the stdlib, and which native types get used as "lowest-common denominator" types for passing to stdlib functions (e.g. whether you pass dicts or lists-of-pairs for options; whether closures are used for everything or some things or nothing; whether {tuples, sets, monads} exist as a thing the stdlib accepts where appropriate, or whether it uses some other lower-level abstraction instead even though the more abstract type is there.) The idiomatic style of a "language" today is mostly about its taxonomy, because library writers take their cues from the stdlib. So things with the same taxonomy can share package ecosystems with no impedance (e.g. JavaScript and CoffeeScript); "siblings" with a mostly-shared taxonomy can share packages with some small effort to speak in LCD types (e.g. Erlang and Elixir.) Unrelated taxonomies need "glue" libraries to explicitly map the impedance, as you see in e.g. Clojure's Java-wrapping libs.
* syntaxes are (hopefully bijective) mappings between tokens and ASTs—as in LISP's original secondary "m-expr" syntax. There's nothing stopping you from mapping any syntax you like to any taxonomy—save for the fact that some syntaxes include operators that do something sensible in one taxonomy (e.g. circumfix operators to create different types of containers; Erlang's "async send" operator) and make no sense for another. I would compare this to the buttons on game controllers: if you use the "wrong" syntax, then some "games" will need "buttons" you don't have on your controller—but with just a bit more fiddling (e.g. typing Set[] vs. #{}) you can still get your meaning across.
People talk about "syntax vs. semantics", but that's a muddle because parts of "semantics" are inextricably represented within syntax. But when you split things this way, you get a clean break: a "language" becomes mostly about taxonomy, where you can port that taxonomy to various platforms, and then target that taxonomy with various syntaxes.
In my ideal world, we'd have a universally-agreed-upon AST format to use as the canonical representation of checked-in code. Each file would mark what taxonomy its identifiers refer to, but would use no taxonomy-specific syntax. Then you'd use something like a FUSE server to map those AST files into a workable representation in a syntax you enjoy. Your text editor wouldn't know the differe...
Learn it well enough to write it? Sure, a couple of weeks, maybe less.
Learn it well enough to write professional-quality code? That takes longer, because you have to learn what the pitfalls are. (Writing professional code, in large part, boils down to knowing what not to write.)
Learn it well enough to be as productive as you were with the previous language? Maybe three to six months?
And that's the real problem, IMHO. It's going to take me three months of lower productivity to make the switch to the new language/framework/tool/whatever. How long will the new thing take to pay me back for that time it costs? If it's not significantly better than what I'm using now, it's not worth the cost.
Second half: "Well, shit."
The wisest time for a dev to learn a new technology is probably at the peak of its popularity. That way, you learn from the community when it's most active, and your expertise grows more valuable as the technology slowly goes out of style. Like the author, this happened to me when I first picked up Rails in 2008-2009. I jumped on board at a time when everyone was talking about it, so I never had to look hard to find information. For the next 5 years or so, it seemed like my job prospects were getting better and better, even though the hype train had left Rails behind shortly after.
I have a pet theory that a lot of the shiny-toy syndrome we see in web development is actually fueled by startup founders who deliberately choose unproven technologies to attract talented developers ("Join us, we actually use language XYZ in production!"), since programming geniuses are often eager to delve into Turing tar-pits, and also dazzle tech journalists by promoting it as their magical secret ingredient. (...and yes, I'm aware that perhaps Rails rose to popularity this way)
Also, these technologies are generally designed to solve some problem, and get adoption because it's a common problem. Struggling with a solved problem rather than using that new tool that solves it is upsetting.
Let's take web templating: How many solutions are out there, and how many of those actually turned out to be winners? To ride the crest of the React wave, you had to pick it out of a thousand others, at a time when there were other "winning" solutions.
And even React is beginning to show signs of falling, with new stars starting to shine. Do you jump ship, or hold the course?
For an existing project, the bias is to not change unless the new language gives you a massive improvement. Re-writing is always harder than you expect, because the existing code base has more bug fixes and handled corner cases than you think it does, and your re-write has to preserve all of that (or suffer the consequences of failing to do so).
I am not saying use every nee cool tech posted on HN, but if something looks great for you, you should investigate in it. I am not saying put it on production tomorrow... But if you have similar broblem, look how it works to have a different view of how to build a better solution...