May be a domain issue? If you're largely coding within a JS framework (which most software devs are tbf) then that makes total sense. If you're working in something like fintech or games, perhaps less so.
My last job was a mix of Ruby, Python, Bash, SQL, and Javascript (and CSS and HTML). One or two jobs before that it was all those plus a smattering of C. A few jobs before that it was C# and Perl.
You've really hit the crux of the problem and why so many people have differing opinions about AI coding. I also find coding more fun with AI. The reason is that my main goal is to solve a problem, or someone else's problem, in a way that is satisfying. I don't much care about the code itself anymore. I care about the thing that it does when it's done.
Having said that I used to be deep into coding and back then I am quite sure that I would hate AI coding for me. I think for me it comes down to – when I was learning about coding and stretching my personal knowledge in the area, the coding part was the fun part because I was learning. Now that I am past that part I really just want to solve problems, and coding is the means to that end. AI is now freeing because where I would have been reluctant to start a project, I am more likely to give it a go.
I think it is similar to when I used to play games a lot. When I would play a game where you would discover new items regularly, I would go at it hard and heavy up until the point where I determined there was either no new items to be found or it was just "more of the same". When I got to that point it was like a switch would flip and I would lose interest in the game almost immediately.
I think it ultimately comes down to whether you care more about the what, or more about the how. A lot of coders love the craft: making code that is elegant, terse, extensible, maintainable, efficient and/or provably correct, and so on. These are the kind of people who write programming languages, database engines, web frameworks, operating systems, or small but nifty utilities. They don't want to simply solve a problem, they want to solve a problem in the "best" possible way (sometimes at the expense of the problem itself).
It's typically been productive to care about the how, because it leads to better maintainability and a better ability to adapt or pivot to new problems. I suppose that's getting less true by the minute, though.
Crafting code can be self-indulgent since most common patterns have been implemented multiple times in multiple languages. A lot of time the craft oriented developer will reject an existing implementation because it doesn't match their sensibilities. There is absolutely a role for craft, however the amount of craft truly needed in modern development is not as large as people would like. There are lots of well crafted libraries and frameworks that can be adopted if you are willing to accommodate their world view.
As someone who does that a lot... I agree. Self-indulgent is the word. It just feels great when the implementation is a perfect fit for your brain, but sometimes that's just not a good use of your time.
I kind of struggle with this. I basically hate everyone elses code, and by that I mean I hate most people's code. A lot of people write awesome code but most people write what I'd call trash code.
And I do think there's more to it than preference. Like there's actual bugs in the code, it's confusing and because it's confusing there's more bugs. It's solving a simple problem but doing so in an unnecessarily convoluted way. I can solve the same problem in a much simpler way. But because everything is like this I can't just fix it, there's layers and layers of this convolution that can't just be fixed and of course there's no proper decoupling etc so a refactor is kind of all or nothing. If you start it's like pulling on a thread and everything just unravels.
This is going to sound pompous and terrible but honestly some times I feel like I'm too much better than other developers. I have a hard time collaborating because the only thing I really want to do with other people's code is delete it and rewrite it. I can't fix it because it isn't fixable, it's just trash. I wish they would have talked to me before writing it, I could have helped then.
Obviously in order to function in a professional environment i have to suppress this stuff and just let the code be ass but it really irks me. Especially if I need to build on something someone else made - itsalmost always ass, I don't want to build on a crooked foundation. I want to fix the foundation so the rest of the building can be good too. But there's no time and it's exhausting fixing everyone else's messes all the time.
I can guarantee you that if you were to write a completely new program and continued to work on it for more than 5 years, you'd feel the same things about your own code eventually. It's just unavoidable at some point. The only thing left then is degrees badness. And nothing is more humbling than realizing that the only person that got you there is yourself.
I usually attribute it to people being lazy, not caring, or not using their brain.
It's quite frustrating when something is *so obviously* wrong, to the point that anyone with a modicum of experience should be able to realize that what was implemented is totally whack. Please, spend at least a few minutes reviewing your work so that I don't have to waste my time on nonsense.
I feel this too. And it seems like the very worst code always seems to come from the people that seem the smartest, otherwise. I've worked for a couple of people that are either ACM alum and/or have their own wikipedia page, multiple patents to their name and leaders in business, and beyond anyone else that I have ever worked with, their code has been the worst.
Which is part of what I find so motivating with AI. It is much better at making sense of that muck, and with some guidance it can churn out code very quickly with a high degree of readability.
I enjoyed that but honestly it kind of doesn't really resonate. Because it's like "This stuff is really complicated and nobody knows how anything works etc and that's why everything is shit".
I'm talking about simple stuff that people just can't do right. Not complex stuff. Like imagine some perfect little example code on the react docs or whatever, good code. Exemplary code. Trivial code that does a simple little thing. Now imagine some idiot wrote code to do exactly the same thing but made it 8 times longer and incredibly convoluted for absolutely no reason and that's basically what most "developers" do. Everyone's a bunch of stupid amateurs who can't do simple stuff right, that's my problem. It's not understandable, it's not justifiable, it's not trading off quality for speed. It's stupidity, ignorance and lazyness.
That's why we have coding interviews that are basically "write fizzbuzz while we watch" and when I solve their trivial task easily everyone acts like I'm Jesus because most of my peers can't fucking code. Like literally I have colleagues with years of experience who are barely at a first year CS level. They don't know the basics of the language they've been working with for years. They're amateurs.
Then it’s quite possible that you’re working in an environment that naturally leads to people like that getting hired. If that’s something you see repeatedly, then the environment isn’t a good fit for you and you aren’t a good fit for it. So you’d be better served by finding a place where the standards are as high as you want, from the very first moment in the hiring process.
Obviously that’s easier said than done but there are quite a few orgs out there like that. If everyone around you doesn’t care about something or can’t do it, it’s probably a systemic problem with the environment.
> > I think we have different opinions on what's fun and what's boring!
> You've really hit the crux of the problem and why so many people have differing opinions about AI coding.
Part of it perhaps, but there's also a huge variation in model output. I've been getting some surprisingly bad generations from ChatGPT recently, though I'm not sure if that's ChatGPT getting worse or me getting used to a much higher quality of code from Claude Code which seems to test itself before saying "done". I have no idea if my opinion will flip again now 5.2 is out.
And some people are bad communicators, an important skill for LLMs, though few will recognise it because everyone knows what they themselves meant by whatever words they use.
And some people are bad planners, likewise an important skill for breaking apart big tasks that LLMs can't do into small ones they can do.
This isn't just in coding. My goodness the stuff I see people write into an LLM and then say "see! It's stupid!". Some people are naturally good at prompting and some people just are not. The differences in output are dramatic.
1. If you don't care about code and only care about the "thing that it does when it's done", how do you solve problems in a way that is satisfying? Because you are not really solving any problem but just using the AI to do it. Is prompting more satisfying than actually solving?
2. You claim you're done "learning about coding and stretching my personal knowledge in the area" but don't you think that's super dangerous? Like how can you just be done with learning when tech is constantly changing and new things come up everyday. In that sense, don't you think AI use is actually making you learn less and you're just justifying it with the whole "I love solving problems, not code" thing?
3. If you don't care about the code, do the people who hire you for it do? And if they do, then how can you claim you don't care about the code when you'll have to go through a review process and at least check the code meaning you have to care about the code itself, right?
Note I'm not saying one is better than the other, but my takes:
1. The problem solving is in figuring out what to prompt, which includes correctly defining the problem, identifying a potential solution, designing an architecture, decomposing it into smaller tasks, and so on.
Giving it a generic prompt like "build a fitness tracker" will result in a fully working product but it will be bland as it would be the average of everything in its training data, and won't provide any new value. Instead, you probably want to build something that nobody else has, because that's where the value is. This will require you to get pretty deep into the problem domain, even if the code itself is abstracted away from you.
Personally, once the shape of the solution and the code is crystallized in my head typing it out is a chore. I'd rather get it out ASAP, get the dopamine hit from seeing it work, and move on to the next task. These days I spend most of my time exploring the problem domain rather than writing code.
2. Learning still exists but at a different level; in fact it will be the only thing we will eventually be doing. E.g. I'm doing stuff today that I had negligible prior background in when I began. Without AI, I would probably require an advanced course to just get upto speed. But now I'm learning by doing while solving new problems, which is a brand new way of learning! Only I'm learning the problem domain rather than the intricacies of code.
3. Statistically speaking, the people who hire us don't really care about the code, they just want business results. (See: the difficulty of funding tech debt cleanup projects!)
Personally, I still care about the code and review everything, whether written by me or the AI. But I can see how even that is rapidly becoming optional.
I will say this: AI is rapidly revolutionizing our field and we need to adapt just as quickly.
> The problem solving is in figuring out what to prompt, which includes correctly defining the problem, identifying a potential solution, designing an architecture, decomposing it into smaller tasks, and so on
Coding is just a formal specification, one that is suited to be automatically executed by a dumb machine. The nice trick is that the basic semantics units from a programming language are versatile enough to give you very powerful abstractions that can fit nicely with the solution your are designing.
> Personally, once the shape of the solution and the code is crystallized in my head typing it out is a chore
I truly believe that everyone that says that typing is a chore once they've got the shape of a solution get frustrated by the amount of bad assumptions they've made. That ranges from not having a good design in place to not learning the tools they're using and fighting it during the implementation (Like using React in an imperative manner). You may have something as extensive as a network protocol RFC, and still got hit by conflict between the specs and what works.
I think you would be surprised by how much these AIs can "fill in the blanks" based on the surrounding code and high-level context! Here is an example I posted a few months ago (which is coincidentally, related to the reply I just gave the sibling comment): https://news.ycombinator.com/item?id=44892576
Look at the length of my prompt and the length of the code. And that's not even including the tests I had it generate. It made all the right assumptions, including specifying tunable optional parameters set to reasonable defaults and (redacted) integrating with some proprietary functions at the right places. It's like it read my mind!
Would you really think writing all that code by hand would have been comparable to writing the prompt?
Honestly, I fundamentally disagree with this. Figuring out "what to prompt" is not problem-solving in a true sense imo. And if you're really going too deep into the problem domain, what is the point of having the code abstracted?
My comment was based on you saying you don't care about the code and only what it does. But now you're saying you care about the code and review everything so I'm not sure what to make out of it. And again, I fundamentally disagree that reviewing code will become optional or rather should become optional. But that's my personal take.
> My comment was based on you saying you don't care about the code and only what it does. But now you're saying you care about the code and review everything so I'm not sure what to make out of it.
I'm not the person you originally replied to, so my take is different, which explains your confusion :-)
However I do increasingly get the niggling sense I'm reviewing code out of habit rather than any specific benefit because I so rarely find something to change...
> And if you're really going too deep into the problem domain, what is the point of having the code abstracted?
Let's take my current work as an example: I'm doing stuff with computer vision (good old-fashioned OpenCV, because ML would be overkill for my case.) So the problem domain is now images and perception and retrieval, which is what I am learning and exploring. The actual code itself does not matter as much the high-level approach and the component algorithms and data structures -- none of which are individually novel BTW, but I believe I'm the only one combining them this way.
As an example, I give a high-level prompt like "Write a method that accepts a list of bounding boxes, find all overlapping ones, choose the ones with substantial overlap and consolidate them into a single box, and return all consolidated boxes. Write tests for this method." The AI runs off and generates dozens of lines of code -- including a tunable parameter to control "substantial overlap", set to a reasonable default -- the tests pass, and when I plug in the method, 99.9% of the times the code works as expected. And because this is vision-based I can immediately verify by sight if the approach works!
To me, the valuable part was coming up with that whole approach based on bounding boxes, which led to that prompt. The actual code in itself is not interesting because it is not a difficult problem, just a cumbersome one to handcode.
To solve the overall problem I have to combine a large number of such sub-problems, so the leverage that AI gives me is enormous.
Why can't both things be true? You can care about the code even if you don't write it. You can continue learning things by reading said code. And you can very rigidly enforce code quality guidelines and require the AI adhere to them.
I mean if you're reading it and "rigidly" enforcing code quality guidelines, then you do care about the code, right? But the parent comment said they don't care about the code but what it does. Both of them cannot be true at the same time, since in your example, you do care about the code enough to read it and refactor it based on guidelines and not just "what the code" does.
I like this framing; I think it captures some of the key differences between engineers who are instinctively enthusiastic about AI and those who are not.
Many engineers walk a path where they start out very focussed on programming details, language choice, and elegant or clever solutions. But if you're in the game long enough, and especially if you're working in medium-to-large engineering orgs on big customer-facing projects, you usually kind of move on from it. Early in my career I learned half a dozen programming languages and prided myself on various arcane arts like metaprogramming tricks. But after a while you learn that one person's clever solution is another person's maintainability nightmare, and maybe being as boring and predictable and direct as possible in the code (if slightly more verbose) would have been better. I've maintained some systems written by very brilliant programmers who were just being too clever by half.
You also come to realize that coding skills and language choice don't matter as much as you thought, and the big issues in engineering are 1) are you solving the right problem to begin with 2) people/communication/team dynamics 3) systems architecture, in that order of importance.
And also, programming just gets a little repetitive after a while. Like you say, after a decade or so, it feels a bit like "more of the same." That goes especially for most of the programming most of us are doing most of the time in our day jobs. We don't write a lot of fancy algorithms, maybe once in a blue moon and even then you're usually better off with a library. We do CRUD apps and cookie-cutter React pages and so on and so on.
If AI coding agents fall into your lap once you've reached that particular variation of a mature stage in your engineering career, you probably welcome them as a huge time saver and a means to solve problems you care about faster. After a decade, I still love engineering, but there aren't may coding tasks I particularly relish diving into. I can usually vaguely picture the shape of the solution in my head out the gate, and actually sitting down and doing it feels rather a bore and just a lot of typing and details. Which is why it's so nice when I can kick off a Claude session to do it instead, and review the results to see if they match what I had in mind.
Don't get me wrong. I still love programming if there's just the right kind of compelling puzzle to solve (rarer and rarer these days), and I still pride myself on being able to do it well. Come the holidays I will be working through Advent of Code with no AI assistance whatsoever, just me and vim. But when January rolls around and the day job returns I'll be having Claude do all the heavy lifting once again.
I'm guessing, but I'm pretty sure you're dealing with big balls of mud which has dampened your love of coding. Where implementing something is more about solving accidental complexity and dealing with technical debts than actually doing the job.
I've seen some balls of mud, sure, but I don't think that's the essence of it. It's more like:
1) When I already have a rough picture of the solution to some programming task in my head up front, I do not particularly look forward to actually going and doing it. I've done enough programming that many things feel like a variation on something I've done before. Sometimes the task is its own reward because there is a sufficiently hard and novel puzzle to solve. Mostly it is not and it's just a matter of putting in the time. Having Claude do most of the work is perfect in those cases. I don't think this is particularly anything to do with working on a ball of mud: it applies to most kinds of work on clean well-architected projects as well.
2) I have a restless mind and I just don't find doing something that interesting anymore once I have more or less mastered it. I'd prefer to be learning some new field (currently, LLMs) rather than spending a lot of time doing something I already know how to do. This is a matter of temperament: there is nothing wrong with being content in doing a job you've mastered. It's just not me.
> 1) When I already have a rough picture of the solution to some programming task in my head up front, I do not particularly look forward to actually going and doing it.
Every time I think I have a rough picture of some solution, there's always something in the implementation that proves me wrong. Then it's reading docs and figuring whatever gotchas I've stepped into. Or where I erred in understanding the specifications. If something is that repetitive, I refactor and try to make it simple.
> I have a restless mind and I just don't find doing something that interesting anymore once I have more or less mastered it.
If I've mastered something (And I don't believe I've done so for pretty much anything), the next step is always about eliminating the tedium of interacting with that thing. Like a code generator for some framework or adding special commands to your editor for faster interaction with a project.
I believe wage work has a significant factor in all this.
Most are not paid for results, they're paid for time at desk and regular responsibilities such as making commits, delivering status updates, code reviews, etc. - the daily activities of work are monitored more closely than the output. Most ESOP grant such little equity that working harder could never observably drive an increase in its value. Getting a project done faster just means another project to begin sooner.
Naturally workers will begin to prefer the motions of the work they find satisfying more than the result it has for the business's bottom line, from which they're alienated.
It gets worse than that: You can possibly get rewarded based on your manager's goals, or maybe your skip level's, but that doesn't necessarily have to line up all that well with more serious business goals. I am sure I am not the only one that had to help initiatives that I thought would be, at best, just wasteful to the business, or that we could get 80% of the value with 20% of the efforts. But it's ultimately about the person who writes the review.
This gets us to the rule number one of being successful at a job: Make sure your manager likes you. Get 8 layers of people whose priority is just to be sure their manager likes them, and what is getting done is very unlikely to have much to do with shareholder value, customer happiness, or anything like that.
> Naturally workers will begin to prefer the motions of the work they find satisfying more than the result it has for the business's bottom line, from which they're alienated.
Wow. I've read a lot of hacker news this past decade, but I've never seen this articulated so well before. You really lifted the veil for me here. I see this everywhere, people thinking the work is the point, but I haven't been able to crystallize my thoughts about it like you did just now.
I think it's related. The nature of the wage work likely also self-selects for people who simply enjoy coding and being removed from the bigger picture problems they are solving.
Im on the side of only enjoy coding to solve problems and i skipped software engineering and coding for work explicitly because i did not want to participate in that dynamic of being removed from the problems. instead i went into business analytics, and now that AI is gaining traction I am able to do more of what I love - improving processes and automation - without ever really needing to "pay dues" doing grunt work I never cared to be skilled at in the first place unless it was necessary.
Sometimes you can, sometimes you have to break the problem apart and get the LLM to do each bit separately, sometimes the LLM goes funny and you need to solve it yourself.
Customers don't want you wasting money doing by hand what can be automated, nor do they want you ripping them off by blindly handing over unchecked LLM output when it can't be automated.
there are other ways: being scammed by lazy devs using AI to produce what devs normally do and not saving any money for the customer. i mentioned it in another thread, i heard first hand people say "i will never report how much time savings i get from gemini, at best i'll say 1 day a month"
Some people are into designing software, others like to put the design into implementation, others like cleaning up implementations yet others like making functional software faster.
There is enough work for all of us to be handsomely paid while having fun doing it :) Just find what you like, and work with others who like other stuff, and you'll get through even the worst of problems.
For me the fun comes not from the action of typing stuff with my sausage fingers and seeing characters end up on the screen, but basically everything before that and after that. So if I can make "translate what's in my head into source on disk something can run" faster, that's a win in my book, but not if the quality degrades too much, so tight control over it still not having to use my fingers to actually type.
I've found that good tab AI-based tab completion is the sweet spot for me. I am still writing code, but I don't have to type all of it if it's obvious.
This has been my approach, as well. I've got a neovim setup where I can 1) open up a new buffer, ask a question, and then copy/paste from it and 2) prompt the remainder of the line, function, or class. (the latter two are commands I run, rather than keybinds).
I really enjoy writing some of the code. But some is a pain. Never have fun when the HQ team asks for API changes for the 5th time this month. Or for that matter writing the 2000 lines of input and output data validation in the first place. Or refactoring that ugly dictionary passed all over the place to be a proper class/dataclass. Handling config changes. Lots of that piping job.
Some tasks I do enjoy coding. Once in the flow it can be quite relaxing.
But mostly I enjoy the problem solving part: coming up with the right algorithm, a nice architecture , the proper set of metrics to analyze etc
I disagree. If you take statement X to be "you don't like them" and Y to be "they're your enemy". Then OP said "Just because X is true, it doesn't mean Y is true". In other words, "X does not imply Y". Meneth said "yes it does". In other words, "X implies Y".
All enemies are people you dislike and / or people who do things you don't like. This does not make the opposite true, not all people you dislike or who do things you don't like are your enemy. The statement "all cats are black" does not also mean "all black things are cats".
I roughly agree with you on that (with the caveat that e.g. opposing army generals can be enemies but admire and respect each other). I disagree that Meneth was saying what you said.
It's a good comment, but "prescient" isn't a word I'd apply to it. This is more like a list of solid takes. To be fair there probably aren't even that many explicit, correct predictions in one month of comments in 2015.
Yeah, you do. It's still pretty unfriendly imo - you're forcing a user to express disapproval to get something useful, without telling them what useful thing they're going to get by clicking it.
It's par for the course with Virgin Media. I've been with them for years as the cheapest way to get genuinely fast broadband (though that seems to be changing) but the service is dire. Some of the patterns:
* When your package contract ends, you always get a much better renewal deal by ringing them up and threatening to leave. The deals you can get online are up to 50% more expensive. This tactic is straight out of the noughties and I can't believe it's still working for them.
* However, you often have to keep calling back until someone offers you a good deal. I'm guessing that there is some sort of incentive structure behind the scenes that basically makes it random whether each individual call will pay off.
* About 8 years ago they messed up my direct debit so badly for three consecutive months despite multiple lunchtimes wasted on hold to their support line, that I eventually sent a strong email to my best guess of the CEO's email. The next day I was contacted by a very capable technician who immediately sorted it out.
* Not so related to their support, but they've recently instituted a price-rise of £4 every year.
Unless you mow your grass too low. Always assume the old rule of "your grass reaches just as far underground as it reaches up in the air" still holds.
Also if you mow your grass drastically shorter or you let it grow for a long time before mowing, do not fail to fertilize it from above right or soon after, start aggressively plucking the leaves of weeds (or other selective methods of fighting them) for a few weeks and (optimally, but highly recommended) verticulate it no sooner than 1 week after cutting. Also time it well to grant your lawn at least 3 weeks of ideal growing weather and climate (It won't die because of a week or two of awful weather, but you'll have A LOT more work fighting weeds ahead of yourself).
Same with Extraordinary Attorney Woo and a lot of "originals" on netflix. They'll just buy the rights to air something and then slap their name on it like they made it. That said, I actually appreciate them looking for good media produced overseas and buying up the rights to those shows to bring them to the US. It's a good thing (although it'd be nice if put some effort in making sure there are always quality subs) but it can cause some people to think netflix is producing more good shows than they actually are.
How would it not be open and transparent on twitter? It's a site where everyone can see what they are talking about. It's only when they try to limit to whom and where they talk to people that they are not open and transparent.
What do these have to do with open and transparent communication?
> I don't need to talk to you or use your favored public platform for my published material to be open and transparent on some other public platform.
Very true, but limiting the platforms limits the openness and transparency. With some simple software you can post to all with almost no effort. Seems weird to disclude one just to write a blog post about it for attention.
it's the town square- it's not about the two people talking but for everyone reading what they said instead of controlling the narrative by only speaking to people you want in places you want. They don't even have to answer to everyone, so the only benefit of losing access to thousands/millions of people is to make an article like this for Pride.
I just mean that in the way that this site is a town square, or all of the rfc's, in that anyone can (for free) see all of the discussions and participate. Just like a town square, not every comment has to be addressed or promoted equally, but I don't know of a better way to release information and allow for anyone to discuss it with others.
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