8 ms·

Ask HN: What is the future of the programmer?

• ohitsdom 11y ago
  How far in the future are you wanting to consider? I don't think we're remotely close to even a primitive form of AI, let alone any AI that can program without human input. Personally, I'd be shocked if this happens in the next 100 years. But it's such a "new" field, that trying to predicit 100 years into the future is a crapshoot.
  • gls2ro 11y ago
    Good question about how far. I was thinking more in the direction of what will be the next transformation of the skills needed in the programming field or the type of work to be done. I think I've got through two iterations so far: algorithmic and now integrative/automatic (I don't have a better name). The latter meaning we are now building more advanced solutions integrated in everyday life or advancing science. In this, the skillset and knowledge is much more advanced or larger then math and algorithms. So I'm wondering or fantasing what could be next? In the next 5-10 years.
  • bnegreve 11y ago
    How do you define programming? If it's specifying a program that maps some inputs with some outputs, many AI systems are already able to do this, sometime even better than humans. For example: would you be able to write a program that can recognise people faces with 80% accuracy? Probably not but AIs can do it.
    • microcolonel 11y ago
      Neural nets currently still require a program to interpret them, and that program is typically written by a human.
      • bnegreve 11y ago
        The point is that the human doesn't write a face recognition system, but a system that learns from examples. If humans cannot program AIs, who else is going to do it?
  • seiji 11y ago
    > I'd be shocked if this happens in the next 100 years. 100 years ago it was 1915. How much has technologically progressed since then? Do you have a sense we have leveled-off (besides single-core frequencies)? Is technology like air travel where we will reach max capability soon after creation and just have to give up improving? Of course not. We're still in exponential growth phases of technology. Don't discount how quickly everything can change out from under us. > can program without human input. Much of programming is just trying all possible endpoints then seeing what works. How much of programming today is just asking Google, finding examples, then tweaking them? Most programmer jobs these days could be completely automated away given current technology if someone built it.
• fao_ 11y ago
  We'll write AIs (heh). On a more serious note, if program writing neural-nets develop much further I can see the field putting more of an emphasis on the theoretical aspect, and leaving implementations to the AIs -- a bit like the way mathematics is heading. Less time spent on proof-checking (and one day perhaps, construction), etc.
• sagivo 11y ago
  Programming is way to important to leave it to humans. I think in the near future we'll have programs who write programs and humans will be unneeded in this field.
  • deedubaya 11y ago
    > humans will be unneeded Nice try, Skynet prototype.
    • sagivo 11y ago
      > in this field :)
• grobmeier 11y ago
  The only thing I know about the future is that nobody knows about it. If you would force me to respond to your question, I'd say it would take a long while until AI's can predict taste, feelings, emotions, "change of minds" and so on and so on. Maybe AI's will do the websites for us, but even then I would not worry. Instead, I would do something with a real meaning and a real purpose. Like maintaining a garden. As skill which might come handy when the AI wars begin.
• richerlariviere 11y ago
  You must look at this article about technological singularity. http://en.wikipedia.org/wiki/Technological_singularity http://en.wikipedia.org/wiki/Technological_singularity In my opinion, the next programmers generation will do quantic computing. Crypto algorithms, protocols, softwares, we will have to rethink everything to get it working with qubits. (http://en.wikipedia.org/wiki/Qubit http://en.wikipedia.org/wiki/Qubit)
• codingdave 11y ago
  I believe the current trend of high level languages will continue. Your average coder already is working at a high abstraction level, with many not even having to deal with direct file access or memory management. Even the ones who do work at lower levels frequently do not get down to assembly. When I started this career a couple decades ago, this was not the case. Most people worked in C, with the majority at least having had exposure to, if not direct professional experience at the assembly level. The abstractions we work at today existed, but were were just written off as toys and script, not "real programming". I think this will continue - most software developers will be re-using components, piecing them together like legos. Actually writing code to make those components happen will be less common. There will always be people who can work at all levels of the systems... but the crowd of coders just making a living will move higher and higher in terms of abstraction.
  • andresmanz 11y ago
    Well, I'm gonna be one of the "all levels of the systems" guys. Honestly, if suddenly my job was nothing more than piecing components together, only writing stuff in super high level languages, I'd quit. I love my job, because I actually have to use my brain to do it right. And then I'd work as a garbage man or something, and write good old code at home. ;-)
    • legedemon 11y ago
      Or you can start your own company and write good old code at work for profit.
  • gizi 11y ago
    Your average coder already is working at a high abstraction level Scripting is not more abstract than C. You can perfectly-well script in C too. Add a garbage collector. You no longer need to call the free() function. Add a few dynamically-growing structures such as a hashtable ("map") and an arraylist ("vector"). You no longer define struct data types and instead, store everything in (JSON-style) hashtables and arraylists. Define a union of all primitive types and call that "var". Now you only use the "var" type. That's it. Except for the obvious lack of syntactic sugar, that should hide the ugly details, you are now scripting in C.
• seajosh 11y ago
  We'll be writing yet another goddamn reporting system for marketing. However, the coffee will be exquisitely made by Blue Bottle's autonomous cybernetic drone.
  • byoung2 11y ago
    I have written a reporting system at nearly every company I've worked for. I've talked to programmers who wrote reporting systems in the 70's and 80's, and are still writing them today. I think you're right, we will still be writing reporting systems well into the future.
    • kzisme 11y ago
      This is hilarious - I just started my internship at a company and a few of the people in the department are working on....you guessed it reporting systems! A lot of the other things that are going on are fun things though, and being an intern and working on a project - from scratch is a rewarding experience.
• k8tte 11y ago
  we will probably continue to program the problem solvers for some time to come. $code = '$z = 0;' . PHP_EOL . '$y = 0;' . PHP_EOL . '$x = 0;' . PHP_EOL . '$x = 0;' . PHP_EOL . '$y = 1;' . PHP_EOL . 'for ($count = 0; $count < 10; $count++) {' . PHP_EOL . ' $z = $x + $y;' . PHP_EOL . ' echo $z;' . PHP_EOL . ' $x = $y;' . PHP_EOL . ' $y = $z;' . PHP_EOL . '}'; $this->assertPhpAndResultEquals( $code, '123581321345589', $this->asPhp( 'sätt x till 0 och sätt y till 1 och upprepa följande 10 gånger:' . ' sätt z till x + y' . ' och visa z' . ' och sätt x till y' . ' och sätt y till z' ) );
• anders30 11y ago
  Consider the field from its inception and how it has changed over time. We move into higher abstractions and release ourselves from having to worry about details such as memory management. Even so, as an embedded software engineer I find myself wrestling with memory usage and throughput budgets. As AI becomes reality, it would be ideal to mold (evolve?) an AI to help me address specific weaknesses in my capabilities to allow me to focus on "the problem at hand". If you're curious about that sort of AI development as it relates to embedded software, check out "hyper-heuristics". You can really answer your question according to the observable trends of the field. The role of the "programmer" will shift, that's all. Regarding what a programmer needs to know, I think you'd be hard pressed to find something that wouldn't be useful in some way. Personally, I am trying to read as much of the "Old Masters" as I can. I've started with Claude Shannon and have tried to hit all the big names along the way. Bernard Widrow's work (http://www-isl.stanford.edu/people/widrow/publications.html http://www-isl.stanford.edu/people/widrow/publications.html most articles are free) got me started.
  • cartoonfoxes 11y ago
    > As AI becomes reality, it would be ideal to mold (evolve?) an AI to help me address specific weaknesses in my capabilities to allow me to focus on "the problem at hand". It's possible to do this already. Although working on application software at the moment which doesn't have any special assurance requirements, I've started making use of an interactive theorem prover to help sanity-check some complicated bits of logic. It's the future, from what I can see.
• phkahler 11y ago
  The big picture is not going to change. There are two broad categories of programmer. 1) people who build applications by gluing libraries and APIs together to get what they want. There is no shortage of things people want the machines to do, and this is by far the biggest swath of programmers and will remain so for the foreseeable future. 2) The people who do deeper dives and build high performance subsystems and components and wrap them in APIs for the first group to use. The older components will see slow replacement by newer/better versions of the same, while new areas are opening up all the time. Vision, voice, image processing, genetic analysis, communications, payment systems, medical records, you name it. If you're the first kind of programmer, do some programming with some of the tools that interest you to learn new things and broaden your experience/understanding. If you're the 2nd kind, pick and area that interests you and roll your own. It doesn't matter if there is a big commercial code or even a big open source version out there, chances are if the right person does their homework they can build a better mouse trap. Just because something is big doesn't mean it's the best that can be, some things just have a lot of momentum. But no, I don't really see much changing other than the list of things people build and then glue together. That basic pattern (build tools, apply tools) seems to be very persistent. Rather than worry about the future, you should open your eyes to just how wide the field is today.
  • AlexeyMK 11y ago
    I refer to the above types as (1) Application Developer and (2) Systems Engineer
    • phkahler 11y ago
      >> I refer to the above types as (1) Application Developer and (2) Systems Engineer I try to avoid the word "System(s)" because of confusion between what we're talking about, system administrators, system architects, and control systems folks. But if you're certain the person you're talking to uses the same definition then it's fine.
  • minthd 11y ago
    I divide the categories a bit differently: It seems that machines are much faster at learning how to do low level stuff(compilers, generic problem solvers, etc) - than they are at doing the high level stuff - understanding the problem and build a high level spec/system for the solution. And of course we're becoming more capable of letting the domain users enter more and more details of the system themselves, either by visual programming, scripting or giving data to machine learning systems, etc. So if those trends are to continue , professional programmers will specialize in creating more and more , highly abstract generic solutions.
• hmans 11y ago
  Web forms
• bnegreve 11y ago
  An interesting vision is that we'll go from programs that can be executed to models that can be solved with generic solvers (e.g. SAT solvers [1], or CP solvers [2]) So if you need to sort an array, instead of programming quicksort, you will simply specify that you are looking for a permutation of the input array T such that for all i, T[i] < T[i+1] and the solver will search and find a solution to your problem (i.e. a sorted array) using whatever technique it likes. Many constraint satisfaction and optimisation problems are already solved this way, there's a possibility that this generalise to other problems. There's many advantages to this: first you need less (no?) testing, because if the solution doesn't match the problem specification it can only be a bug in the solver. Second, there's a chance that solvers will eventually be as fast as human programmers at finding solutions. Just like the compilers are almost as good at programmers at generating assembly, and often better. If this happens programming in general will become as useless as programming in assembly today. [1] http://en.wikipedia.org/wiki/Boolean_satisfiability_problem#Algorithms_for_solving_SAT http://en.wikipedia.org/wiki/Boolean_satisfiability_problem#... [2] http://en.wikipedia.org/wiki/Constraint_programming http://en.wikipedia.org/wiki/Constraint_programming
  • skierscott 11y ago
    cvxpy[1] is a good example of this. The contraints are specific symbolically and cvxpy optimizes for you (assumes problem is a convex optimization problem etc) [1]:https://github.com/cvxgrp/cvxpy https://github.com/cvxgrp/cvxpy
    • bnegreve 11y ago
      Yes, there are many of these. I think MiniZinc is also quite popular among the optimisation guys http://www.minizinc.org/ http://www.minizinc.org/
  • platz 11y ago
    Reminds me of Expert Systems
  • vezzy-fnord 11y ago
    Why hasn't Prolog programmed us out of existence, then? Don't get me wrong. Constraint solvers are useful and powerful tools for declarative problem solving, but I don't recall them ever being viewed as general-purpose, especially not to the level of being a generic "autocode" (what compilers were once called, funnily enough) system. Genetic programming seems like a more likely candidate (with some combination of SAT solvers and statistical learning), but again hypothesizing about such a major thing doesn't appear fruitful at present.
• deleted 11y ago
  [deleted]
• syonip 11y ago
  I think that a software that writes good software is quite far down the line, I wouldn't direct my career planning around it. Humanity's brightest haven't even managed to make a cross-browser styling language that renders lines that are aligned with each other correctly.
• btbuildem 11y ago
  Programming isn't the hard part - the hard part is communicating with people and understanding the problems they need solved. Master that and you will have a job for however long you want.
  • sbilstein 11y ago
    Agreed, communication is key to effective development. It's also much harder to find a teacher/mentor for the communication part of the skill set than it is for the technical end.
  • gizi 11y ago
    That depends on how innovative your programming is. Let's take two examples of billionaire programmers: The Google Search guys and the Bitcoin guy. What you see is that they have never, ever asked anybody what problems they needed solved. They imagined something interesting and then they just built it. All preliminary forms of communication with other people would simply have been useless, because none of us knew that we needed Google Search until we saw it, and none of use would ever have believed that Bitcoin could work, until we saw it with our own eyes. In other words, if you are doing a truly innovative project, you should not communicate with people but simply ignore them until you are ready to show what you have built, simply because they will not be able to believe that it is possible to fly to the moon, until someone actually does it.
    • MichaelGG 11y ago
      >because none of us knew that we needed Google Search until we saw it, Did you use search engines before Google? It was obviously a shitty experience. And ads? And don't even start on the folks that thought they could categorize the web by hand, or use META tags to sort it all out. So while the Google guys might not have gone around polling people "What can I build that you'd like and would make me rich?", it was far from a dream of a product no one had thought about. Tons of money was going into search engines and portals by the time Google started. And Bitcoin? The dream of e-cash has been around for a while as well; it wasn't a brand new idea. The implementation was a breakthrough, but the idea has been around for a while. (Nitpick: And at current rates, Satoshi's coins are probably worth much less than a billion dollars. And AFAIK, there's been no movement on the blocks people thinks he has.)
• yarper 11y ago
  Every 10 years or so there's a discussion on if we've reached the point when programs can program other programs, or the WYSIWYG is so good anyone off the street can do it.. It never turns out to be the case. The problem is that software developers are largely detail managers, we work out the finer points of everything and translate it into something someone who doesn't need to think or care about the finer points can use. For example, you could design a building yourself - but at the end of the day you could just tell an architect what to do and he/she will manage the details for you. A good one will even stop you making obvious mistakes, and save you cash by suggesting better materials etc.
  • emilecantin 11y ago
    http://xkcd.com/568/ http://xkcd.com/568/ "You will never find a programming language that will free you from the burden of clarifying your ideas."
• jerf 11y ago
  "there are a lot of AIs and some of them are writing code already?" That's post-Singularity, and can't be meaningfully discussed. Since the idea of the singularity has gotten conflated with one particular possible outcome ("rapture of the nerds" is merely one of the better possibilities, not the totality of the idea), let me remind you that the core idea of the singularity is that it is when the future is so different than it is now that our ability to predict it has dropped to zero. There's a certain amount of relativity to it... we're post-singularity for a cave man, for instance. AIs that are smart enough to program themselves will result in a world so radically different that there is no meaningful way to plan for what to do from here in 2015. In the future before then, which for all we know may well encompass the entire lives of everybody here, and assuming no major civilizational hiccups (which may not be "singularities" but are also fairly difficult to predict around), programming will be one of the few fields that probably will continue to grow more or less indefinitely for the forseeable future. More stuff is going to be programmable, and the advantage for a company to have better programmer better than its competitor will likely also grow. In fact I think there's a decent chance that demand for programmers, and especially good programmers, is likely to rise beyond the base level of people who are even theoretically capable of becoming that level of programmer. I suspect we have not actually seen peak salary in this field for good programmers. (Interesting tidbit... programming has the tendency to "eat" other fields, as others have noticed. Even if genetics and biology manage to do everything that they've ever promised... the top level of biological designers are going to look an awful lot like programmers, moreso than biologists, precisely because the only way we'll ever have that level of control over biology is to abstract the issues away until we have a programming language on top. Nobody can work at the raw gene level, at scale. Oh, it won't be C or Haskell or Python, but it'll still be a programming language. Probably declarative.) I'm not just trying to say good things to make us happy; this has been my assessment of the field's prognosis for a while, even since before the bubble pop, and I've seen nothing to make me change it, even the bubble pop and the 2008 crisis. Even if we are in another bubble now and it pops, it would have to epically pop, like, the entire country, person by person, decides this whole "Internet" thing is a total waste of time forever for all things, for me to change my mind. The fact that I feel this way about this field and that I work in this field is not a coincidence. Per my comment [1], when in 1996 I mentally did what I suggested in that post and "computer programmer" popped out in my second slot for Jobs I'd Like To Do, I was pretty grateful, and, again, have seen nothing to make me change my mind since. [1]: https://news.ycombinator.com/item?id=9667145 https://news.ycombinator.com/item?id=9667145
• lucasnemeth 11y ago
  CRUD websites for some boring management thing.
• wilburlo 11y ago
  Humans are messy. AI will probably dominate the everything where the process is well known and BORING. Even if better mechanisms (security, processing, protocols) take place, there will always be issues between humans and machines. For example here is a good example, about how computers and humans make each others situations more complex. https://medium.com/backchannel/how-technology-led-a-hospital-to-give-a-patient-38-times-his-dosage-ded7b3688558 https://medium.com/backchannel/how-technology-led-a-hospital...
• codeshaman 11y ago
  I think the 'programmer' will slowly dissolve away, as the new generation learns how to program just like we used to learn how to read and write. My daughter is 5, she barely reads, but she finds it very easy to make small programs on sites like code.org. She can think in loops and even understands recursion. Like spelling and maths, programming is a technique to achieve a goal in an area. A couple of centuries there were very few 'literate' people and even fewer mathematicians, maybe a couple percent of the population. As education progressed, literacy and maths became a normality and now an average 16-year old has an arsenal of tools and equations to solve very complex problems that Pythagoras or even Newton struggled with or had to invent. The same thing will happen to programming. We're talking about maybe 10-20 years when everyone will know how to program and the tools they will have (programming languages or environments) will be so powerful that they will be able to build their domain specific solution in a very short period of time. There will be of course people focused on languages or low level operating system stuff, but those areas are in themselves entire branches so it will be more appropriate to call them 'compiler scientist' or 'performance engineers' rather than the generic term 'programmer'.
  • gizi 11y ago
    If that were true, everybody and their little sister would understand the Bolzano–Weierstrass theorem by now. It was discovered in 1817. They teach it everywhere in high schools as a mandatory item in the math class. However, there is no hope whatsoever that more than 10% of the population would ever understand what it means.
    • codeshaman 11y ago
      Multiplied by the population of Earth, that's still a huge number of people. What I was trying to say is that there are lot of problems that are already solved and new generations can build on top of that. There are always going to be ever more complicated problems and ever-expanding areas, but in many areas we've pretty much figured things out so people can just use the solutions in their domain specific problems without having to re-implement them. I'm talking about open source libraries, higher-level programming languages and even visual programming which can be used by people to write programs without needing to understand the deeper aspects of things. Doctors visualising data, artists making interactive art or chaining visual effects, lawyers querying databases - things you needed to hire programmers for will be done by people who aren't doing this full time, but can do it if required.
• yellowapple 11y ago
  There will always be programmers. It's just a matter of whether said programmers will be electronic or biological :) If AI ends up replacing most programming tasks, then our jobs will likely shift to something more akin to AI-centric psychology mixed with high-level software engineering. Much like how only the most hardcore "Real Programmers(TM)" today write their programs in assembly or machine code in this day and age of optimizing compilers and interpreted/JIT'd languages, only the most hardcore "Real Programmers(TM)" of the future will actually write software from scratch, with most programmers instead opting to give their AIs descriptions of what they want their programs to do like how we give compilers or interpreters source code files today. I expect that there'll be a heavy emphasis on TDD/BDD in such a future; you'd write a specification or (inclusively) a suite of integration tests, and your artificially-intelligent program-maker will create software that meets the specifications provided and satisfies the provided tests. Whether or not these will be "programmers" in the traditional sense is a bit fuzzy; it's conceivable that - someday - non-technical pointy-haired-boss types could come up with specifications if AI-driven software-building tools can sufficiently understand natural languages. At that point, though, it's fuzzy whether or not PHBs will exist, or whether humanity will exist (or AIs, if a Dune-Butlerian-Jihad-style anti-computer revolution manages to happen).
• alexandroid 11y ago
  I agree with the comment citing XKCD "You will never find a programming language that will free you from the burden of clarifying your ideas." I see programming as a way to model reality. All programs essentially created to do something with objects of the real world or model existing world in some way. And that is where the complexity comes from. As we go higher up the stack of abstractions and tools, some things get easier, but the problems and tasks remain complex just like the world behind them. Performance gains we get come from the fact that many of the modeling and decision making has been done "at the level below" so we can shift into making higher level decisions. Just imagine a "magic AI" which can create any program for you simply based on your description. For any non-trivial program which does not previously exist you would need to specify so many details that your list of requirements essentially becomes a program (in DSL). The more "defaults" and existing pieces you can use, the easier your job will be. So, following that logic, the programmer of the future would be using some sort of AI for sure, to take care of the parts of the system which can be reused and recombined (taking care of the common details). And that means that anybody who can describe what they want will be able "to program". But for new problems, it would need to go into deeper down the stack and domain knowledge to be able to build new things. In terms of "what you need to know" it means having domain knowledge so you can describe what you want. And for new domains - being able to dive deep and learn them, which means the more basic stuff you know (math, statistics, algorithms, whatever), the more efficient you will be in learning and ultimately building.
• logibly 11y ago
  Until there's a better way for humans and machines to communicate, programming will continue to thrive. When I say better way, I don't mean touch or type, I mean better connected to our thoughts.