Other people see all that as an means to an end - and find no joy from the technical aspect of creating something. They're more interested in the end result / product, rather than the process itself.
I think that if you're in group A, it can be difficult to understand group B. In vice versa.
I'm a musician, so I love everything about creating music. From the theory, to the mastery of the instrument, the tens of thousands of hours I've poured into it...finally being able to play something I never thought I'd be able to, just by sheer willpower and practice. Coming up with melodies that feel something to me, or I can relate to something.
On the other hand, I know people that want to jump straight to the end result. They have some melody or idea in their head, and they just want to generate some song that revolves around that idea.
I don't really look down on those people, even though the snobs might argue that they're not "real musicians". I don't understand them, but that's not really something I have to understand either.
So I think there are a lot of devs these days, that have been honing their skills and love for the craft for years, that don't understand why people just want things to be generated, with no effort.
> Other people see all that as an means to an end
I think it's worth pointing out that most people are both these things at different times.
There's things I care about and want a deep understanding of but there's plenty of tasks I want to just "go away". If I had an junior coder - I'd be delegating these. Instead I use AI when I can.
There's also tasks where I want a jump start. I prefer fixing/improving code over writing from scratch so often a bad AI attempt is still valuable to me.
As a manager, say I do hire a junior developer, invest time into them and they level up. I go to the HR department and tell them that they deserve a 30% raise to bring them inline with the other mid level developers.
The HR department is going to say that’s out of policy and then the developer jumps ship.
The tragedy of the commons in a nutshell. Maybe everyone should invest in junior developers so that everyone has mid-level developers to poach later?
There's no doubt about it, there's selfish reasons to teach, mentor, and have a junior under you. We're social creatures. It should be no surprise that what's good for the group is usually good for yourself too. It's kinda as if we were evolutionarily designed to be this way or something ¯\_(ツ)_/¯
Everyone says they don't have time, but you get a lot of time by doing things right instead of doing things twice. And honestly, we're doing it a lot more than twice.
I just don't understand why we're so ready and willing to toss away a skill that allowed us to become the most successful creature on the planet: forethought. It's not just in coding but we're doing it everywhere. Maybe we're just overloaded but you need forethought to fix that, not progressively going fast for the sake of going fast
I leveled up because I practice mentoring others. But it still doesn’t make sense for the organization to hire juniors. Yes I realize someone has to. It’s especially true for managers who have an open req to fill because they need work done now.
On the other hand, my one, only and hopefully last role in BigTech where I worked previously, they could afford to have an intern program and when they came back after college have a 6 month early career/career transition program to get them up to speed. They could afford the dead weight loss.
> a devil’s advocate/hypothetical question.
I'm not saying "don't ask questions." We should all be asking questions! If anything, we should be asking more! But we're in a thread that's contextualized about a division of people. It is only natural for people to interpret as a continuation of what came before.
But to address your point more directly, my answer is that the scenario you presented would be a surefire way to kill a company. Yes, there are big companies that do this, but you'll recognize that they're also monopolies or close it. A company with competition (big or small) is unable to pull off such shortsightedness. What you do for the company is the same thing you do for society: invest in the future. Sure, you wanna be lean and cost efficient but that has to be balanced with security. You don't want your company to go under just because an employee got hit by a truck. You don't want your company to go under just because an employee decides to retire. You're not doing a good job if you have these vulnerabilities. These are things only small startups should be doing and only because they have no choice.
This isn't "dead weight" and I think it is really bad to frame things this way. Most of the time my firewall isn't doing anything, is it "dead weight"? I often buy stocks while markets are low or falling, are these "dead weight"? I went to school to get an education, was this "dead weight"? It would be silly to call any of those things "dead weight", yet they're identical. A "dead weight" employee is one who has the ability to do but does not. It is the person who gets promoted by being performative, by being close to the manager, by looking like they are doing work more than they are. There's a lot of dead weight in companies, and they stick around because they look like they're useful. And conversely, some of your best workers often look like your worst[0].
It is literally Goodhart's Law in action and what I'm pissed about is we as a society have identified this issue and decided "it is a feature, not a bug" despite all the evidence to the contrary. We've dropped so many sayings and cliques that were common and were warnings of enshitification. When was the last time you heard someone say "you get what you pay for"? Or "if you're gonna do something, do it right"? We normalized the work environment of a fucking Dilbert Comic. And here we are, in this thread, defending our Dilbert world. We could have a lot of nice things, but the inescapable truth is that nice things require work. Worse, I'm tired of living in an environment where all the little issues I face in daily life that can easily be fixed are causally brushed away because "it doesn't create value" while we dump billions into the next vaporware. It is deadly irony and I cannot stand this double speak. I just want to make things that work... You'll say "I'm not stopping you" but every person that frames things like above creates a system that does prevent me (and many others). While it isn't a zero sum game, we sure have limited resources and we're all too happy to light them on fire when promised some magic beans. I don't understand why no matter how many times we watch it happen we still do not learn.
You have processes that outlive people. Companies don’t care about society - they care about their bottom line. They aren’t there to make society as a whole better
If you want a society of well trained software engineers ready to work in corporate America, you support your public education system. Just like if you want a society that has universal healthcare, you put the onus on society and not corporate America.
My job is to do what’s best for the company as long as it is not illegal or unethical. My job is not to make society better. I got one open req. I want to hire the best person my budget allows
> You don’t invest in your future ... the average tenure of a software developer is 3 years and at any time an employee can leave.
1) Tragedy of the Commons: If we all act like this, then no one gets invested in. If we all invest in our employees then when they leave another company gets the rewards. That's still true when "we" are the "other company". You still benefit regardless. Under the condition that most companies (or rather at least the big companies) collude in this way. They have good reason to as coalitions maximize utility for all parties involved.
2) Why the fuck are we training people and then tossing them away? We do this in many ways but the most obvious one is hiring a new dev and paying them more than the current devs. Guess what? That new dev needs to be trained and now your old devs are pissed that they aren't getting paid as much. So now you not only waste time and money onboarding someone new, you lose your experience.
> Companies don’t care about society - they care about their bottom line
> My job is to do what’s best for the company as long as it is not illegal or unethical
I don't understand why you think we're in disagreement about this. Every single one of my points has come down to this. I've said it explicitly. My very first message stated that there were selfish reasons to do these things. The selfishness and foresight doesn't apply just to yourself.
> My job is not to make society better
But it is just a weird argument all together anyways. Your job isn't to make society better? Read that again. Your job isn't to make your life better? Certainly a paycheck makes your life better, right? I really hope it isn't making it worse. But we're social creatures too. Your job isn't to make your family's lives better? Your job isn't to make your friends' lives better? If it isn't to better yourself, your family, and your friends, then what the fuck are we even doing here? You have autonomy. And here's the fun part, if we care about our local groups and improve our local groups, this usually improves broader groups by extension. We're interconnected. I'm not saying you need to care about some dude on the opposite side of the country, but I sure as hope you don't think your job is to do harm. The "not illegal or unethical" part really is concerning. Frankly, I'd call doing harm unethical, even if it is small. It's more unethical to steal someone's wallet than to snatch a penny, but both are still unethical.
So I really don't get where you're trying to go with this. Because frankly, the selfish act improves society. It's just you have to consider that other people exist. If you're selfish and you model a world where you're alone, then yeah, maximize yourself at all costs. But when there are other agents in the world, the way to maximize your utility is through coalitions, through improving the group.
> If we all invest in our employees then when they leave another company gets the rewards. That's still true when "we" are the "other company". You still benefit regardless. Under the condition that most companies (or rather at least the big companies) collude in this way. They have good reason to as coalitions maximize utility for all parties involved.
You are right that in a world where most companies collude in this manner, we all benefit.
However, in that world, a company that chooses not to contribute (by investing in inexperienced employees) also has access to the same benefits (trained employees).
Furthermore, they can use the money saved by not contributing to inflate the value of the trained employees (offering them higher pay), so they have an incentive to not contribute. This doubly deprives the rest of us of some of that benefit.
How do we adjust the incentives so that bad actors are not motivated to cheat the system?
(In case it seems like a familiar scenario, yes, this is similar to playing Iterated Prisoners' Dilemma with the rest of the world.)
> However, in that world, a company that chooses not to contribute
But this is still not an optimal strategy. It can give you a short term edge, but you're completely right that it destroys the natural coalition equilibrium. The result is that this destroys the coalition. You get the benefit for a small time period but it doesn't take long for the coalition to be abandoned and once that is done, you no longer gain from this strategy. In this situation the total utility in the system decreases! Not just globally, but each player's utility drops! That's a major problem! It is sacrificing long term rewards for short term ones. Importantly, those long term rewards are quite significant while the short term ones are not.
> How do we adjust the incentives so that bad actors are not motivated to cheat the system?
> this is similar to playing Iterated Prisoners' Dilemma
For some reason people think zero-sum games are common. Lump of Labor (Fixed-Pie) Fallacy is really common[0]. I do see high rates of zero-sum thinking around here on HN and in CS communities, and I'm not sure why it is so common. While I don't have the same expectations for the general public, we create things out of essentially limitless resources. We frequently create value that does not require additional compute or meaningful consumption of current resources (which is also increasing as time marches on). Our whole job is built on the fact that the pie continually grows in size and we are strongly rewarded for making the pie larger in the first place!
Yes I know it’s insane that a manager can’t get the budget to give raises. But can get one to hire someone new at prevailing market rates.
Given those are the facts, I had to aggressively job hop between 6 jobs between 2008-2020 to get the money I wanted after staying at my second job for nine years getting 3% raises.
Now at 50 on my 10th job, I can optimized for different things.
How are you going to convince HR or the PHB that their policies are insane? As a manager or a team lead, your job is to create processes to make developers interchangeable “resources”.
> How are you going to convince HR or the PHB that their policies are insane?
I'm not trying to play wack-a-mole here.
I'm trying to be infectious so that the knowledge becomes widespread. We had it before, so I don't think it is naive to think we can't have it again. It was considered "common sense" before, the question is why it was lost. Given your age I guess I should be asking you why we dropped the aforementioned cliques. It's weird how common "you get what you pay for" was and how now we act in opposition to the clique: buying the cheapest option and making it hard to determine quality.
But as far as you get what you pay for, it’s not hard to find “good enough” framework enterprise developers and have a few good experience “seniors”. Especially with remote work, you dangle that in front of people my age, we are willing to take a haircut. For me now, remote work, autonomy, and a smaller company is worth being able to say “no” to more money when managers at Google (GCP) reach out to me.
By senior, I don’t mean “I codez real gud”, I mean the tech industries definition - someone who can deal with “scope” and “ambiguity” and has a history of highly impactful projects.
Just to be clear, I spent most of my career as an “enterprise dev” until 2020 at 46 when a position at AWS fell into my lap (Professional Services department). I’m no longer there. But it did cause me to pivot to cloud consulting specializing in app dev and now I am a “staff architect” at a third party company.
Even there people get better offers coming in externally than they do an internal promotion.
On a related note, it was also easier coming in as an L6 (senior) than it was to get promoted from an L5 to an L6.
If you work for a company like this, you should jump ship.
On an unrelated note: it’s also easier to get “promoted” to the next level by changing jobs and then coming back than it is to go through the internal promo process at the same BigTech company.
I recognize that and I kind of agree, but I think I don't entirely. Writing the "boring" boilerplate gives me time to think about the hard stuff while still tinkering with something. I think the effect is similar to sleeping on it or taking a walk, but without interrupting the mental cruncing that's going in my brain during a good flow. I piece together something mundane that is as uninteresting as it is mandatory, but at the same time my subconscious is thinking about the real stuff. It's easier that way because the boilerplate does actually, besides being boring, still connect to the real stuff, ultimately.
So, you're kind of working on the same problem even if you're just letting your fingers keep typing something easy. That generates nice waves of intensity for my work. My experience regarding AI tends to break this sea of subconsciousness: you need to focus on getting the AI to do the right thing which, unlike typing it yourself, is ancillary to the original problem. Maybe it's just a matter of practise and at some point I can keep my mind on the domain in question eventhough I'm working an AI instead of typing boilerplate myself.
IMHO there's no joy in doing the same thing multiple times. DRY doesn't help with that, you end up doing a lot of menial work to adapt or integrate previous code.
Most of the for-profit coding is very boring.
So if someone generates their music with AI to get their idea to music you don’t look down on it?
Personally I do, if you don’t have the means to get to the end you shouldn’t get to the end and that goes double in a professional setting. If you are just generating for your own enjoyment go off I guess but if you are publishing or working for someone that’ll publish (aka a professional setting) you should be the means to the end, not AI.
If you're talking about a person using an LLM, or some other ML system, to help generate their music then the LLM is really just a tool for that person.
I can't run 80 mph but I can drive a car that fast, its my tool to get the job done. Should I not be allowed to do that professionally if I'm not actually the one achieving that speed or carrying capacity?
Personally my concerns with LLMs are more related to the unintended consequences and all the unknowns in play given that we don't really know how they work and aren't spending much effort solving interoperability. If they only ever end up being a tool, that seems a lot more in line with previous technological advancements.
If you drive a car 80mph you don't get to claim you are a good runner
Similarly if you use an LLM to generate 10k lines of code, you don't get to claim you are a good programmer
Regardless of the outcome being the "same"
Then you get to the place and they say "now load all of the things in the garage into the truck"
But oops. You didn't bring a truck, because all they told you was "please be at this address at this time", with no mention of needing a truck
My point is that the purpose of commercial programming is not usually just to get to the goal
Often the purpose of commercial programming is to create a foundation that can be extended to meet other goals later, that you may not even be remotely aware of right now
If your foundation is a vibe coded mess that no one understands, you are going to wind up screwed
And yes, part of being a good programmer includes being aware of this
At the same time human ran 'feature' applications like you're talking about often suffer from "let the programmer figure it out" problems where different teams start doing their own things.
Right, but if you use a chess engine to win a chess championship or if you use a motor to win a cycling championship, you would be disqualified because getting the job done is not the point of the exercise.
Art is (or should be) about establishing dialogues and connections between humans. To me, auto-generated art it's like choosing between seeing a phone picture of someone's baby and a stock photo picture of a random one - the second one might "get the job done" much better, but if there's no personal connection then what's the point?
What has always held true so far: <new tool x> abstracts challenging parts of a task away. The only people you will outcompete are those, who now add little over <new tool x>.
But: If in the future people are just using <new tool x> to create a product that a lot of people can easily produce with <new tool x>, then, before long, that's not enough to stand out anymore. The floor has risen and the only way to stand out will always be to use <new tool x> in a way that other people don't.
I understand your point, but I think it is ultimately rooted in a romantic view of the world, rather than the practical truth we live in. We all live a life completely inundated with things we have no expertise in, available to us at almost trivial cost. In fact it is so prevalent that just about everyone takes it for granted.
My entire management chain - manager, director and CTO - are all technical and my CTO was a senior dev at BigTech less then two years ago. But when I have a conversation with any of them, they mostly care about whether the project I’m working on/leading is done on time/within budget/meets requirements.
As long as those three goals are met, money appears in my account.
One of the most renown producers in hip hop - Dr. Dre - made a career in reusing old melodies. Are (were) his protégés - Easy-E, Tupac, Snoop, Eminem, 50 cent, Kendrick Lamar, etc - not real musicians?
It depends entirely on how they're using it. AI is a tool, and it can be used to help produce some wonderful things.
- I don't look down on a photographer because they use a tool to take a beautiful picture (that would have taken a painter longer to paint)
- I don't look down on someone using digital art tools to blur/blend/manipulate their work in interesting ways
- I don't look down on musicians that feed their output through a board to change the way it sounds
AI (and lots of other tools) can be used to replace the creative process, which is not great. But it can also be used to enhance the creative process, which _is_ great.
Look at popular music for the last 400 years. How is that any different than simply copying the previous generations stuff and putting your own spin on it?
If you heard a CD in 1986 then in 2015 you wrote a song subconsciously inspired by that tune, should I look down on you?
I mean, I'm not a huge fan of electronic music because the vast majority of it sounds the same to me, but I don't argue that they are not "real musicians".
I do think that some genres of music will age better than others, but that's a totally different topic.
Of course, everything is on a scale so it's not either/or.
But, like you, how I get there matters to me, not just the destination.
Outside the context of music, a project could be super successful but if the journey was littered with unnecessary stress due to preventable reasons, it will still leave a bad taste in my mouth.
I find it very unlikely anyone who only likes the results will ever pick up the craft in the first place
It takes a very specific sort of person to push through learning a craft they dislike (or don't care about) just because they want a result badly enough
Seems to me that "the result" is "the money" and not "the product".
Because I'd argue those that care about the product, the thing being built, the tool, take a lot of pride in their work. They don't cut corners. They'll slog through the tough stuff to get things done.
These things align much more with the "loves coding" group than "the result". Frankly, everyone cares about "the result" and I think we should be clear about what is actually meant
Nope, your code might look excellent. Why the hell isn't it running though? Three hours later you find you added a b when you closed your editor somewhere in the code in a way your linter didn't pick up and the traceback isn't clear about, maybe you broke some all important regex, it doesn't matter. One second, it's fixed, and you just want to throw the laptop out the window and never work on this project again. So god damned stupid.
And other things are frusterating too. Open a space deliminated python file, god forbid you add a tab without thinking. And what is crazy about that is if the linter is smart enough to say "hey you put a tab here instead of spaces for indent" then why does it even throw the error and not just accept both spaces and tabs? Just another frustration.
Really I would love to just go at it, write code, type, fly, be in the flow state, like one does building something with the hands or making music or doing anything in the physical world. But no. Constant whack a mole. Constantly hitting the brakes. Constant blockers. How long will this take to implement? I have no fucking idea man, could be 5 seconds or 5 weeks and you don't often know until you spend the 5 seconds and see that didn't do it yet.
So much of what we think of as law in music is just being used to the conventions. Lots of amazing music would have been considered noise if created in an earlier time.
> The issue with programming is that it isn't like music or really any other skill where you get feedback right away and operate in a well understood environment.
Funny, I feel the opposite about programming. The feedback comes in milliseconds. Ok the build didn’t break, ok the ui is working, now check if the change I made is right, now run the tests, etc. and the environment is fully documented, depending on your tooling of choice and the quality of its docs.
Programming is similar to music. (A great many software innovators in the 70s and 80s had musical roots). But AI prunes away all the creativity and stylistic expression from the composition and the performance when designing and building software, reducing the enterprise to mere specification -- as if the libretto of the opera were merely an outline, and even that was based on Cliff Notes.
The case for using AI to code is driven strictly by economics and speed. Stylistically and creatively, AI is a no-brainer.
And this is what is causing the friction against LLM's (which are quite useful for getting up to speed with a new concept / language ), the programming itself is the fun bit - I still want to do that bit!
I don't really get any joy from the act of coding, but I also take a lot of pride in doing a good job.
Cutting corners and producing sloppy work is anathema to me, even when I don't really enjoy the work itself
Any work worth doing is worth doing a good job on, even if I don't enjoy the work itself
- A singer might learn to play guitar to sing along to it. Guitar is a means to an end; it is simply a tool to them.
- A guitarist learns to play guitar due to love of the instrument.
Some like proving and deriving, for others it's a tool to solve other problems
i say this as someone who cut my teeth on this stuff growing up and seeing the evolution, it's both. and at some point it's honestly elitism and gatekeeping. i sort of cringe when it's called a "craft" because it's not like woodworking or something. the process is both full of joy but so is the end result, and the nature of our industry is that the process is ALWAYS changing.
you accumulate a depth of knowledge and watch as it washes away in a few years. that kind of change, and the big kind of change that AI brings scares people so they start clinging to it like it's some kind of centuries old trade lol.
Many of these folks would do well to walk over to the intersection of Market, Bush, and Battery Streets in San Francisco and gaze up at the Mechanics Monument.
Programming something more sophisticated with AI? AI is pretty much useless if you're doing anything somewhat novel. What it excels at is vomiting code that has already been written a million times so you can build yet another Electron cross-platform app.
Even when I'm stuck in hell, fighting the latest undocumented change in some obscure library or other grey-bearded creation, the LLM, although not always right, is there for me to talk to, when before I'd often have no one. It doesn't judge or sneer at you, or tell you to "RTFM". It's better than any human help, even if its not always right because its at least always more reliable and you don't have to bother some grey beard who probably hates you anyway.
Even more so, I remember making a Chrome extension and feeling intimidated. I knew that I'd be comfortable with most of it given that JS is used but I just didn't know how to start.
With an LLM it is way faster to spin up some default config and get going versus reading a tutorial. What I've noticed in that respect is that I just read what it does and then immediately reason why it's there. "Oh, there's a manifest.json file with permissions and a few other things, fair, makes sense. Oh, so you have the HTML/CSS/JS of the extension, you have the HTML/CSS/JS of the page you're injecting some code into and you have the JS of a background worker. Ah yea, I get that."
And then I just get immediately on coding.
How if it hallucinate and gives you wrong code and explanation? It is better to read documentations and tutorials first.
Then the code won't compile, or more likely your editor/IDE will say that it's invalid code. If you're using something like Cursor in agent mode, if invalid code is generated then it gets detected and the LLM keeps re-running until something is valid.
> It is better to read documentations and tutorials first.
I "trust" LLM's more than tutorials, there's so much garbage out there. For documentation, if the LLM suggests something, you can see the docstrings in your IDE. A lot of the time that's enough. If not, I usually go read the implementation if I _actually_ care about how something works, because you can't always trust documentation either.
As for my editor saying it is invalid..? That is just as untrustworthy as an LLM.
>I "trust" LLM's more than tutorials, there's so much garbage out there.
Yes, rubbish generated by AI. That is the rubbish out there. The stuff written by people is largely good.
I interpreted the "hallucination" part as the AI using functions that don't exist. I don't consider that a problem because it's immediately obvious.
Yes, AI can suggest syntactically valid code that does the wrong thing. If it obviously does the wrong thing, then that's not really an issue either because it should be immediately obvious that it's wrong.
The problem is when it suggests something that is syntactically valid and looks like it works but is ever slightly wrong. But in my experience, it's pretty common to come across that stuff like that in "tutorials" as well.
> Yes, rubbish generated by AI. That is the rubbish out there. The stuff written by people is largely good.
I pretty strongly disagree. As soon as it became popular for developers to have a "brand", the amount of garbage started growing. The stuff written before the late 00's was mostly good, but after that the balance began slowly shifting towards garbage. AI definitely increased the rate at which garbage was generated though.
To be fair, I as a dev with ten or fifteen years experience I do that too. That's why I always have to through test the results of new code before pushing to production. People act as if using AI should remove that step, or alternatively, as if it suddenly got much more burdensome. But honestly it's the part that has changed least for me since adopting an AI in the loop workflow. At least the AIncan help with writing automated tests now which helps a bit.
Emphatic no.
There were heaps of rubbish being generated by people for years before the advent of AI, in the name of SEO and content marketing.
I'm actually amazed at how well LLMs work given what kind of stuff they learned from.
Hallucinations are a thing. With a competent human on the other end of the screen, they are not such an issue. And the benefits you can reap from having LLMs as a sometimes-mistaken advisory tool in your personal toolbox are immense.
Also something are meant to be approached with the correct foundational knowledge (you can’t do 3D without geometry, trigonometry, and matrixes. And a healthy dose of physics). Almost every time I see people strugling with documentation, it was because they lacked domain knowledge.
1. Code doesn't compile. This case is obvious on what to do.
2. Code does compile.
I don't work in Cursor, I read the code quick, to see the intent. And when done with that decide to copy/paste it and test the output.
You can learn a lot by simply reading the code. For example, when I see in polars a `group_by` function call but I didn't know polars could do that, now I know because I know SQL. Then I need to check the output, if the output corresponds to what I expect a group by function to do, then I'll move on.
There comes a point in time where I need more granularity and more precision. That's the moment where I ditch the AI and start to use things such as documentation and my own mind. This happens one to two hours after bootstrapping a project with AI in a language/library/framework I initially knew nothing about. But now I do, I know a few hours worth of it. That's enough to roughly know where everything is and not be in setup hell and similar things. Moreover, by just reading the code, I get a rough idea on how beginner to intermediate programmers think about the problem space the code is written in as there's always a certain style of writing certain code. This points me into the direction on how to think about it. I see it as a hint, not as the definitive answer. I suspect that experts think differently about it, but given that I'm just a "few hours old" in the particular language/lib/framework, I think knowing all of this is already really amazing.
AI helps with quicker bootstrapping by virtue of reading code. And when it gets actually complicated and/or interesting, then I ditch it :)
That's not a jab, but a serious question. We act like people don't "hallucinate" all the time - modern software engineering devops is all about putting in guardrails to detect such "hallucinations".
Add to this that someone who uses a LLM to "just do things" for them like this is very unlikely to have much useful knowledge and so can't really resolve these issues themselves it's a recipe for disaster and not at all a time saver over simply learning and doing yourself.
For what it's worth I've found that LLMs are pretty much only good for well understood basic theory that can give you a direction to look in and that's about it. I used to use GitHub Copilot (which years ago was (much?) better than Cursor with Claude Sonnet just a few months ago) to tab complete boilerplate and stuff but concluded that overall, I wasn't really saving time and energy because as nice as tab-completing boilerplate sometimes was, it also invariably turned into "It suggested something interesting, let's see if I can mold it into something useful" taking up valuable time, leading nowhere good in general and just generally being disruptive.
I work as a consultant assessing other people's code and it's hard not to lose my religion, sort of speak.
Sadly, I find it sorely lacking at dealing with build systems and that particular type of boilerplate, mostly because it seems to mix up different versions of things too much and gives you totally broken setups more often than not. I’d just as soon never deal with the he’ll that is front end build/lint/test config again.
AI generated tests are a bad idea.
I've been writing Python for 20+ years and I still can't use unittest.mock without looking up the details every time. ChatGPT and Claude are great at that, which means I use it more often because I don't have to deal with the frustration of figuring it out.
Absolutely 0 framework or libs, nothing even for logging. Code architecture that would be left in the dust by most university semester projects.
This is how plsql codebases look, but boy Java (and rest of the world) moved quite far since 1995.
I’ve been on projects with multiple languages, but the truly active code was done in only two. The other languages were used in completed modules where we do routine maintenance and rare alterations.
LLMs. I've expanded the circle of languages I use on a frequent basis quite dramatically since I started leaning on LLMs more. I used to be Python, SQL and JavaScript only. These days I'm using jq, AppleScript, Bash, Go, awk, sed, ffmpeg and so many more.
I used to avoid infrequently used DSLs because I couldn't hold them in my memory. Now I'll happily use "the best tool for the job" without worrying about spinning up on all the details first.
I keep seeing people saying to use an LLM to write boilerplate, but like... do you not just copy that from another project where you already wrote it?
Also, I know that people love to joke on modern software and JS in particular. But if you take react code from 2020 and drop it into a new react codebase it still works. Even class based components work. Yes, if you jumped on the newest framework bandwagon every time stuff will break all the time, but AI won’t be able to help you with that either. If you went for relatively stable frameworks, you can re use boilerplate completely or with relatively minimal adjustments
If you take a project from 2020 it's a bit of a pain to upgrade it.
I ran this prompt (and others like it) and it actually worked!
This code needs to be upgraded to the new
recommended JavaScript library from
Google. Figure out what that is and
then look up enough documentation to
port this code to it
If you keep re-using boilerplate once in a while copying it from elsewhere is fine. If you re-use it all the time, just get a macro setup in your editor of choice. IMHO that is way more efficient than asking AI to produce somewhat consistent boilerplate
So yes, boilerplate, but also yes, there is definitely something to be gained from using ai assistants.
Haven't much used AI to assist. After all, hard enough finding authentic humans capable and willing to voluntarily review/critique one's code. So far AI doesn't consistently provide that kind of help. OTOH seems almost certain over time AI systems will improve in terms of specific and comprehensive "insights" into the particular types of code one is writing.
I think an issue is that human creativity is hard to measure. Likely enough AI is even tougher to assess. Probably AI will increasingly be assigned tasks like constructing project skeletons, assuring parts can be joined together without undue strain, handling "boilerplate" and other routine chores. To be sure the landscape will look different in 50 years, I'm certain we'd be amazed were we able to see what future systems will be doing.
In any case, we shouldn't hesitate to use tools that genuinely boost our creativity. One badly needed role would be enabling development of higher reliability software. Still that's a far cry from the contributions emanating from the best of human originality, talent and motivation.
Source: Generative Deep Learning by David Foster, 2nd edition, published in 2023. From “Tokenization” on page 134.
“If you use word tokens: …. willnever be able to predict words outside of the training vocabulary.”
"If you use character tokens: The model may generate sequences of characters that form words outside the training vocabulary."
And like I said, single-byte tokens very much are a part of word tokenisers, or to be precise, their token selection. "Word tokeniser" is a misnomer in any case - they are word piece tokenisers. English is simple enough that word pieces can be entire words. With languages where you have numerous suffixes, prefixes, and even in-fixes as a part of one "word" (as defined by "one or more characters preceded or followed by a space" - because the truth is more complicated than that), you have not so much "word tokenisers" as "subword tokenisers". A character tokeniser is just a special case of a subword tokeniser where the length of each subword is exactly 1.
“If you use word tokens: …. willnever be able to predict words outside of the training vocabulary.”
"If you use character tokens: The model may generate sequences of characters that form words outside the training vocabulary."
That’s a lot of trauma you’re dealing with.
Of course, it all depends how you use the LLM. While the same can be true for StackOverflow, the LLMs just scale the issues up.
> The rest is boiler plate, cargo-culted, Dockerfile, build system and bash environment variable passing circle of hell that I really could care less about.
With expertise in anything, I'm sorry, but you also got to do the shit work. To be a great musician you gotta practice boring scales. It's true even if you just want to be a sub par one.
But a little grumpy is good. It drives you to fix things, and frankly, that's our job. The things that are annoying and creating friction don't need be repeated over and over, they need alternative solutions. The scripts you build are valuable. The "useless" knowledge you gain isn't so useless. Those little details add up without you knowing and make you better.
That undocumented code makes you frustrated and reminds you to document your own. You don't want to be a hypocrite. The author of the thing you're using probably thought the same thing: "No one is gonna use this garbage, I'm not going to waste my time documenting it". Yet here we are. Over and over again yet we don't learn the lesson.
I'm not gonna deny there's assholes. There are. But even assholes teach you. At worst, they teach you how not to act.
And some people are you telling you to RTM and not RTFM. Sure, it has lots of extra information in it that you don't need to get your specific job done, but have you also considered that it has lots of extra information in it? The person that wrote it clearly thought the context was important. Maybe it isn't. In that case, you learned a lesson in how not to write documentation!
What I'm getting at is that there's a lot of learning done all over the place. Trying to take out all the work and only have "the fun" is harming yourself and has a large potential to make less time for the fun stuff[0]. I'd be surprised if I'm alone in this, but a lot of stuff I enjoy now was stuff that originally frustrated me. IME this is pretty common! It's true for every person I know. Similarly, it's also true for things I learned that I thought I'd never use again. It always has a way of coming back.
I'm not going to pretend it's all fun and games. I'm explicitly saying it's not. But I'm confident in the long run it's better. Despite the lack of accuracy, I use LLMs (and Google, and even the TFM) like I would a solution guide the homework problems when I was in school. Try first, then consult. The struggle is an investment in your future. It sucks, but if all the best things in life were easy then we'd all have them. I'm just trying to convince you that it pays off.
I'm completely aware this is all context dependent. There's a time and place for everything. But given the percentages you mention (even taken as exaggeration), something sounds wrong. It's hard to suggest specific solutions without details but I'd be surprised if there weren't better and more rewarding solutions than having the LLM do it for you
[0] That's the big danger and what drives distrust in them. Because you need to work extra hard to find mistakes, increasing workload, not decreasing, because debugging is most of the job!
While it looks like a productivity boost, there's a clear price to pay. The more you use it, the less you learn and the less you are able to assess quality.
I'm sure it's faster in the short term. Just like copy-paste-from-stack-overflow is. But it is debt. The shit builds and builds. But I think the problem is we're so surrounded by shit we've just normalized it. It is incredible how much bloat and low hanging fruit there is that can be cheaply resolved but there is no will to. And in my experience, it isn't just a lack of will, it is a lack of recognition. If the engineers can't recognize shit, then how do we build anything better? It is literally our job to find problems
Frankly I don't want to spend 2 hours reading documentation just to find out some arcane incantation that gets the computer to do what I want it to do.
The interesting part of programming to me is designing the logic. It's the 'this, then that, except when this' flow that I'm really interested in, not the search for some obscure library that has some function that will parse this csv.
Llms are great for that, and let me get away from the pointless grind and into the things that I enjoy and are actually providing value.
The pair programming is also a super good thing. I work best when I can spitball and throw out random ideas and get quick feedback. Llms let me do that without bothering others who have their own work to do.
Then you are just straight up not cut out to be a software developer
The existence of LLMs may reduce the need to slog through documentation, but it will not remove that need
The purpose of programming is to provide value for people, not to read documents.
There is more to "providing value" than simply producing working code
Does it have known security exploits built in that you have no idea about because you couldn't be bothered to read documentation?
Is the "value" you provided extremely temporary because someone is going to come along and exploit your shitty LLM generated code to steal all of your client's customer data?
Software Engineering isn't just about writing code it is about understanding what you're building because if you don't, other people will exploit that
Solving problems for real people. Isn't the answer here kind of obvious?
Our field has a whole ethos of open-source side projects people do for love and enjoyment. In the same way that you might spend your weekends in a basement woodworking shop without furnishing your entire house by hand, I think the craft of programming will be just fine.
Now you don't really have to be precise at any level to get something 'working'. You may not be familiar with the generated language or libaries but it could look good enough (like the assembly would have looked good enough). So, sure, if you are very familiar with the generated language and libraries and you inspect every line of generated code then maybe you will be ok. But often the reason you are using an LLM is because e.g. you don't understand or use bash frequently enough to get it to do what you want. Well, the LLM doesn't understand it either. So that weird bash construct that it emitted - did you read the documentation for it? You might have if you had to write it yourself.
In the end there could be code in there that nothing (machine or human) understands. The less hard-won experience you have with the target and the more time-pressed you are the more likely it is that this will occur.
The output of the LLM is determined by the weights (parameters of the artificial neural network) estimated in the training as well as a pseudo-random number generator (unless its influence, called "temperature", is set to 0).
That means LLMs behave as "processes" rather than algorithms, unlike any code that may be generated from them, which is algorithmic (unless instrcuted otherwise; you could also tell an LLM to generate an LLM).
What used to be a project doing a CMS backend, now is spent doing configurations on a SaaS product, and if we are lucky, a few containers/serveless for integrations.
There are already AI based products that can automate those integrations if given enough data samples.
Many believe AI will keep using current programming languages as translation step, just like those Assembly developers thought compiling via Assembly text generation and feeding into an Assembly would still be around.
Confused by what you mean. Is this not the case?
You can naturally revert to old ways, by asking for the Assembly manually, and call the Assembler yourself.
No. There are a thousand other ways of solving problems for real people, so that doesn't explain why some choose software development as their preferred method.
Presumably, the reason for choosing software development as the method of solving problems for people is because software development itself brings joy. Different people find joy in different aspects even of that, though.
For my part, the stuff that AI is promising to automate away is much of the stuff that I enjoy about software development. If I don't get to do that, that would turn my career into miserable drudgery.
Perhaps that's the future, though. I hope not, but if it is, then I need to face up to the truth that there is no role for me in the industry anymore. That would pretty much be a life crisis, as I'd have to find and train for something else.
Software development is almost unique in the scale that it operates at. I can write code once and have it solve problems for dozens, hundreds, thousands or even millions of people.
If you want your work to solve problems for large numbers of people I have trouble thinking of any other form of work that's this accessible but allows you to help this many others.
Fields like civil engineering are a lot harder to break into!
There's inertia in the industry. It's not like what you're describing could happen in the blink of an eye. You may well be at the end of your career when this prophecy is fulfilled, if it ever comes true. I sure will be at the end of mine and I'll probably work for at least another 20 years.
And what happened? Programmers make the queries and embed them into code that creates dashboards that managers look at. Or managers ask analysts who have to interpret the dashboards for them... It rather created a need for more programmers.
Compare embedded SQL with prompts - SQL queries compared to assembler or FORTRAN code is closer to English prose for sure. Did it take some fun away? Perhaps, if manually traversing a network database is fun to anyone, instead of declaratively specifying what set of data to retrieve. But it sure gave new fun to people who wanted to see results faster (let's call them "designers" rather than "coders"), and it made programming more elegant due to the declarativity of SQL queries (although that is cancelled out again by the ugliness of mixing two languages in the code).
Maybe the question is: Does LLM-based coding enable a new kind of higher level "design flow" to replace "coding flow"? (Maybe it will make a slightly different group of people happy?)
I don't see why we should seek an explanation if there are thousands of ways to be useful to people. Is being a lawyer particularly better than being an accountant?
Look at the majority of the tech sector for the last ten years or so and tell me this answer again.
Like I guess this is kind of true, if "problems for real people" equals "compensating for inefficiencies in our system for people with money" and "solutions" equals "making a poor person do it for them and paying them as little as legally possible."
(Interesting how people talk about AI destroying programming jobs all the time, but rarely mention the impact of billions of dollars of code being given away.)
Open source software is not just different in the license, it’s different in the design
Linux also doesn’t take jobs away - the majority of contributors are paid by companies, afaik
How true that is depends on what sort of software you write. Very little of what I've accomplished in my career can be fairly described as "automating other people's jobs away".
"Yes, yes... Satellites stay in orbit for a while. What about it?"
"Looks a bit cramped in there."
"Stop complaining, at least it's a real job, now get in, we're about to launch."
I've worked in a medical space writing software so that people can automate away the job that their bodies used to do before they broke.
Now all those jobs are gone because of you.
Depends what you write. What I work on isn't about eliminating jobs at all, if anything it creates them. And like, actual, good jobs that people would want, not, again, paying someone below the poverty line $5 to deliver an overpriced burrito across town.
Not always. Recruitment budgets have limits, so it's a fixed number of employees either providing services to a larger number of customers thanks to software, or serving fewer customers or do so less often without the software.
If the work those workers were doing before software was truly valuable. Companies would find other ways to scale, and simply pass the higher costs onwards to consumers.
Would you mind naming a few instance of the workers coming out ahead?
I doubt the displaced computers managed to find a better job on average. Probably even their kids were disadvantaged since the parents had fewer options to support their education.
So, who knows if this specific group of people and their descendants ever fully recovered let alone got ahead.
The world changes. Those changes cause a need, a job fulfills that need. The world changes again, the need disappears. Why should the job then persist?
Because if you pursue a career and invest time and money into it over the course of your life, especially in the highly Americanized way which involves both a substantial time and MORE substantial outlay of money to achieve that, and you then go on to live in a society that demands you earn a living or starve/freeze to death, it is unconscionably immoral to fuck with other people's means to earn that living for your own profit.
And to be clear, that doesn't mean "you can never change your career," that's nonsense. People do that all the time, out of necessity or just desire. However currently the ability to do that is heavily gate-kept via the income of the person wanting to do the switching, and for a lot of the people most likely to be automated, they barely make enough to survive right now, where in the hell are they getting capital to retrain themselves on a new career?
And that's not even going into the physiological challenges. You objectively, factually, learn better when you are younger, and it's also worth noting that society at large benefits more from you learning at a younger age like we traditionally do, because you spend the first few years rolling around your house annoying your mother, you spend up to age 18 (usually) in mandatory K-12 education, you spend between 2 and 8 years in college after that if you decide to go or alternatively, a few years learning a trade or something, and then you have what we generally aim for about 40 years of being a productive member of society. If you have to retrain in the middle of that, that's just less efficient on every front. It costs you money and time, it costs society your productivity for however long you leave the workforce and return to education, and of course that's assuming you can afford to do it at all, and don't end up just lurching from one job that's about to nix you to the next, being miserable and depressed, until you can't find another and then you end up in the homeless system.
In my mind at least, the only way I can comprehend anyone being in favor of this sort of system is they imagine themselves one day being on the top of it, because that's the only group of people who are actually benefiting from this sort of instability. The looming threat of and execution of job automation has massive boons for employers; fewer employees can produce at higher rates, the job market is flooded with recently laid off people which lowers the value of labor and lets employers pay the ones who are hired on after less money, and the overall instability "vibes" present makes employees more willing to tolerate bullshit from their employer because they know how much the job market sucks and they don't want to find another, or, who knows, maybe they are trying and literally can't for the previous reasons.
Like in my mind, this just comes down to whether you think you're more likely to be the boot or the neck under the boot, and that's going to decide how you feel about this.
Haven't we been automating jobs away since the industrial revolution? I know AI may be an exception to this trend, but at least with classical programming, demand goes up, GDP per capita goes up, and new industries are born.
I mean, there's three ways to get stuff done: do it yourself, get someone else to do it, or get a machine to do it.
#2 doesn't scale, since someone still has to do it. If we want every person to not be required to do it (washing, growing food, etc), #3 is the only way forward. Automation and specialization have made the unthinkable possible for an average person. We've a long way to go, but I don't see automation as a fundamentally bad thing, as long as there's a simultaneous effort to help (especially those who are poor) transition to a new form of working.
What is qualitatively different this time is that it affects intellectual abilities - there is nothing higher up in the work "food chain". Replacing physical work you could always argue you'd have time to focus on making decisions. Replacing decision making might mean telling people go sit on the beach and take your universal basic income (UBI) cheque, we don't need you anymore.
Sitting on the beach is not as nice as it sounds for some; if you don't agree, try doing it for 5 years. Most people require work to have some sense of purpose, it gives identity, and it structures their time.
Furthermore, if you replaced lorry drivers with self-driving cars, you'd destroy the most commonly held job in North America as well as South America, and don't tell me that they can be retrained to be AI engineers or social media influencers instead (some can only be on the road, some only want to be on the road).
So no, we don't need to retrain them to be AI engineers if we have an active shortage of electricians and plumbers. Now, perhaps there aren't enough jobs—I haven't looked at exact numbers—but we still have a long ways to go before I think everything is automated.
Everything being slop seems to be the much more likely issue in my eyes[1].
[1] https://titotal.substack.com/p/slopworld-2035-the-dangers-of...
Somehow everyone who says this misses that never in the history of the United States (and most other countries tbh) has this been true.
We just consign people to the streets in industrial quantity. More underserved to act as the lubricant for capitalism.
I see capitalism invoked as a "boogey man" a lot, which fair enough, you can make an emotional argument, but it's not specific enough to actually be helpful in coming up with a solution to help these people.
In fact, capitalism has been the exact thing that has lifted so many out of poverty. Things can be simultaneously bad and also have gotten better over time.
I would argue that the biggest issue is education, but that's another tangent...
I'll be sure to alert the next person I encounter working UberEats for slave wages that the resources exist that they cannot use. I'm sure this difference will impact their lives greatly.
Edit: My point isn't that UberEats drivers make slave wages (though they do): My point is that from the POV of said people and others who need the aforementioned resources, whether they don't exist or exist and are unusable is fucking irrelevant.
[1] https://babel.hathitrust.org/cgi/pt?id=mdp.39015022383221&se...
[2] https://www.indeed.com/cmp/Uber/salaries/Driver (select United States as location)
I think they were using “slave wages” as a non-literal relative term to the era.
As you did.
A hundred years before your example, the “slave wages” were actually slave wages.
I think it’s fair to say a lot of gig workers, especially those with families, are having a very difficult time economically.
I expect gig jobs lower unemployment substantially, due to being convenient and easy to get, and potentially flexible with hours, but they lower average employment compensation.
Great point. I wonder if this has to do with the current housing crisis and cost of utilities... Food has never been more affordable, in fact free with food banks and soup kitchens. But (IMHO) onerous zoning has really slowed down development and driven up prices.
Another cost is it's pretty much impossible to do anything without a smartphone and internet. I suppose libraries have free internet, but being able to get to said library is another issue.
And like you said, contract work trades flexibility for benefits, and that gets exploited by these companies.
I guess it just sucks sometimes because these issues are super hairy (shut down Uber, great, now you've just put everyone out of a job). "For every complex problem there is a solution which is clear, simple, and wrong."
* Everything is more expensive. You say "food has never been more affordable" but I'll absolutely challenge that. Food banks and kitchens are heavily locale-dependent type resources, and are not distributed according to the needs of the populace, but rather according to the ability and willingness of given communities to sustain them.
* You skated right past the need for a smartphone, mentioning, then going on to cite libraries for some reason. This is just a non-solution to a gig worker who will receive jobs and report their status/completion via a smartphone while on the go, doing the work. Ergo to even begin gig work, one REQUIRES a smart phone WITH a data plan.
* And, again, the pay is shit. In my relatively wealthy area, a good Uber Eats driver can make about $13 to $16 an hour, which on it's face sounds okay for a job that requires basic smartphone literacy and a driver's license. But just think about that. For starters, more than half statistically is tips, which aren't guaranteed and are based on performance. A performance, mind, that is subject to dozens of factors entirely outside the control of the driver. Further, it requires the use of the driver's personal vehicle (or one they have access to anyway) which costs obviously fuel, but traveling so many miles so fast will also mean more frequent oil changes, more replacement parts, not to mention a STEEP increase in the odds of bodily injury on the part of the driver, and NONE of this is being handled by Uber. All of these costs and risks are being felt by the driver.
And that still leaves tons of expenses on the table: insurance for the vehicle, many drivers want to run multiple apps which can require the use of multiple phones and therefore multiple data plans, they need to keep their vehicles clean and tidy for cargo or even passengers, they need to be available at the peak times for orders in order to make any money at all, and even if they do ALL OF THAT right... they are not guaranteed any wage, at all. If they simply don't get orders, or refuse too many and have the systems shadowban them, or simply aren't in the right place, their entire "shift" as it were can be a net loss for them.
> I guess it just sucks sometimes because these issues are super hairy (shut down Uber, great, now you've just put everyone out of a job). "For every complex problem there is a solution which is clear, simple, and wrong."
The solution is I think quite simple here: Uber (and all the rest of these gig apps to be clear) should be paying these people a wage, and the people should be driving cars in a fleet owned by Uber. You know, like Taxi companies did. Taxi drivers made tips, sure, occasionally, but they were hourly employees like any other. If they got in a car accident, the company was insured for that, both for the car and the worker. The employees enjoyed at least some benefits, didn't need to maintain or clean their own cars, certainly didn't need to buy the cars, and showed up to a place, on a schedule, and did a job. Like was normal before the "gig economy."
> You skated right past the need for a smartphone.
Hmm? Like when I said "Another cost is it's pretty much impossible to do anything without a smartphone and internet"?
> a good Uber Eats driver can make about $13 to $16 an hour
Source? That doesn't line up with what I found.
> A performance, mind, that is subject to dozens of factors entirely outside the control of the driver.
This is just FUD if you haven't cited your sources on average/median/distribution of pay in whatever area.
You have a very good point on liability issues though.
> The solution is I think quite simple here
Thus increasing prices of rides, causing users to stop using the service, further shrinking pay? Uber just started being profitable after dumping billions of dollars in subsidies, on top of bad pay. If you make them full-time employees, you may just shut off the one source of income they have.
Uber won because they offered a superior service to taxis. I'm not going to open the can of worms of their predatory behavior, but there was still a significant part that was a better service.
Again, I am planning on helping these people, I think they should be helped, but you really need to think through what could happen if you force a company to become insolvent.
[1] https://ourworldindata.org/grapher/long-term-prices-food?foc...
I bet you like Steven Pinker. He does this shit too where he goes "people 50 years ago didn't even have air conditioning, and now a poor person has one in their car and one in their home" which ignores several things that are going to be their own rabbit holes so I'm just going to not, but that doesn't mean things are better. Yeah, poor people have more stuff, more creature comforts, more "luxuries" today than kings had in the 1400's. That doesn't change the fact that they're barely getting by, living perpetually on a debt and stress treadmill that studies too numerous to count have shown decrease their quality of life, shorten their overall lifespan and lead to health problems, in a country where having health problems is also, totally but coincidence I'm sure, the fastest ticket one can have to poverty.
And the worst part is, it doesn't NEED to be that way. We have more of... basically everything than we ever have, yet it all costs more, and tons of businesses go under, and everybody gets poorer, while the richest grow ever, ever, ever richer.
2 trillion was transferred from the working class to the 1% during COVID. 2. Fucking. Trillion. Dollars.
> Hmm? Like when I said "Another cost is it's pretty much impossible to do anything without a smartphone and internet"?
"Pretty much impossible" and "impossible" are not the same. It is not possible to do gig work without a smartphone.
> Source? That doesn't line up with what I found.
It's going to vary widely based on locale. Mine when I commented was the suburbs of Chicago.
> This is just FUD if you haven't cited your sources on average/median/distribution of pay in whatever area.
Yeah, it is. Because gig work is inconsistent. Would you be okay working your job when your salary was completely dependent on your performance, sure, but also just how much work you had to do during that particular day, and if there was a decent chance that one day you show up to your office, sit on your ass for 8 hours, and go home without a penny?
I doubt it.
> Thus increasing prices of rides
This just in: products and services should cost what it costs for them to be created/rendered unto you, with a little more at the end so the person doing it earns a living. If you can't afford to have a person pick up a burrito for you, drive it across town in a car, and drop it on your doorstep, I would humbly suggest you get in your own car, and get your own burrito.
> Uber just started being profitable after dumping billions of dollars in subsidies
Then shut the doors! If what you're doing doesn't work, close up shop! Why does Uber have to exist? Are people better off being Uber drivers than being homeless? I mean, I guess? I wouldn't call that an open and shut case. If all the people doing gig work were instead completely unemployed, and out protesting in the streets of their capital cities, maybe society would actually do something about the rampant exploitation? Maybe all these companies couldn't get away with paying people utterly shit wages if we didn't mandate that those on assistance programs find jobs, any jobs, even if those jobs don't get them off the assistance?
I would turn this back to you: instead of asking me why people are entitled to food, why are these massive companies entitled to exist? Why are we funneling people with few options towards them to work as many hours as they can while remaining firmly below the poverty line? Why do we demand people who are starving take a certain number of interviews every week so we give them access to a menial amount of sustenance, while judging them for taking it?
> Uber won because they offered a superior service to taxis. I'm not going to open the can of worms of their predatory behavior,
Yeah I bet you're not, because you don't want to think about HOW that victory was achieved, be it the financial cost, or the human cost. Now you have a shiny app and can get rides around your city. Nobody gives a shit about the fate of labor as long as they get instant gratifications, same as it ever was.
Sure, if you completely disregard the past 200 years or so of history.
What helps me is to think of it like I'm a kid again, learning to code full of ideas but without any pre-conceived notions. Rather than the Microsoft QuickBasic manual in my hands, I've got Gemini & Claude Code. I would be gleefully coding up a storm of games, websites, dubious webcrawlers, robots, and lord knows what else. Plenty of flow to be had.
I guess if you code stuff that had been coded a lot in public repos, it is fine, otherwise AI does not help in any way. Actually, I think I wasted more time trying to make it produce the output I wish for than it took me to do this myself.
If you're somewhere in between (where I am now) it's situationally useful for small sub-components but you need to filter it heavily or you'll end up wasting a day or two going down a wrong rabbit-hole either because you don't know the domain well enough to tell when it's bullshitting or going down a wrong path, or don't know the domain well enough to use the right keyword to get it to cough up something useful. I've found domain knowledge essential for deciding when it's doing something obviously wrong instead of saying "I don't know" or "This is the wrong approach to the problem".
For the correct self-contained class or block of code, it is much faster to specify the requirements and go through a round or two of refinement than it is to write it myself. For the wrong block of code it's a complete waste of time. I've experienced both in the last few days.
Obviously LLMs in this situation will still be insanely helpful, but in the same way that Google searches or stack overflow is insanely helpful.
AI assisted development is no different from managing an engineering team. "How can you trust outsourced developers to do anything right? You won't understand the code when it breaks"... "How can you use an IDE, vim is the only correct tool" etc etc etc.
Nothing has changed besides the process. When people started jumping on object orientation they called procedures the devil itself, just as procedures were once called structured programming and came to banish away the considered harmful goto. Everything is considered harmful when theres something new around the corner that promises to either make development more productive or developers more interchangeable. These are institutional requirements and will never go away.
Embrace AIOP (AI oriented programming) to banish copy and paste google driven development which is now considered harmful.
Having LLMs like 2.5 now are total game changers. I can basically flow chart a program and have Gemini manifest it. I can break up the program into modules and keep spinning up new instances when context gets too full.
The program I am currently working on is up to ~5500 LOC, probably across 10ish 2.5 instances. It's basically an inventory and BOM management program that takes in bloated excel BOMs and inventory, and puts it in an SQLite database, and has a nice GUI. Absolutely insane how much faster SQLite is for databases than excel, lol.
One is a automatic electronics test system that runs tests and collects measurements (50k+ readings across 8-12 channels)(GPT-4, now with a GUI and faster DB thanks to 2.5). One is a QC tool to help quickly make QC reports in our companies standard form (3.7). And the last is a GUI CAD tool for rendering and quickly working through ancient manufacturing automation scripts from the 80's/90's to bring them up to compatibility with modern automation tooling (3.7).
I personally think that there is a large gap between what programs are, and how each end user ultimately uses them. The programs are made with a vast scope, but often used narrowly by individuals. The proprietary CAD program that we were going to use originally for the old files was something like $12k/yr for a license. And it is a very powerful software package. But we just needed to do one relatively simple thing. So rather than buy the entire buffet, buy the entire restaurant, Claude was able to just make simple burger.
Would I put my name on these and sell to other companies? No. Am I confident other LLM junkies could generate similar strongly positive outcomes with bespoke narrow scope programs? Absolutely.
And if something's not obvious I can always fetch the specifics of any particular calls. But at least I didn't have to find the name of that call in the first place.
Thanks for the comment. You articulated how I feel about this situation very well.
Honestly, I suspect the people who would prefer to have someone or something else do their coding, are probably the devs who are already outputting the worst code right now.
I don't know if I'm a minority but I'd like to think there are a lot of folks like me out there.
You can compare it to someone who is writing assembly code and now they've been introduced to C. They were happy writing assembly but now they're thrilled they can write things more quickly.
Sure, AI could lead us to write buggier code. Sure, AI could make us dumber because we just have AI write things we don't understand. But neither has to be the case.
With better tools, we'll be able to do more ambitious things.
(The hype merchant, LinkedIn influencer, Twitter thread crowd are super noisy but tend to stick to their own echo chambers, it's rare to have them engage in a forum like Hacker News directly.)
No, there's plenty of top-class engineers who love coding with AI. e.g. Antirez.
The others, who are not like us? They've got other priorities. If you hate coding but you love AI, you're probably into software engineering because of the money, not love of technology. If you love coding and you hate AI, you're probably more committed to some sort of ideology than you are the love of technology. If you hate coding and you hate AI, well, I hope you throw your cellphone into the river and find a nice cabin in the woods somewhere to hide in.
As someone that you may characterize as one of these people, I can share some perspective.
First, I would question the premise that “love of technology” is not itself an ideology.
I do love technology, but not for its own sake. I love solving problems, I love tinkering, and I love craftsmanship and invention.
But technology can also be dangerous, it can set us backwards and not forwards, and its progress is never as inevitable as its evangelists claim. You need to view technology with a critical eye, and remember that tools are tools, and not panaceas.
So I guess I’d ask you — what’s so wrong with choosing to live in a cabin in the woods without a cellphone?
Would that I could...
I hate the reality of our current AI, which is benefitting corporations over workers, being used for surveillance and censorship (nevermind direct social control via misinformation bots), and is copying the work of millions without compensating them in order to do it.
And the push for coders to use it to increase their output, will likely just end up meaning expectations of more LoC and more features faster, for the same pay.
But FOSS, self-hosted LLMs? Awesome!
How are self-hosted LLMs not copying the work of millions without compensating them for it?
How is the push for more productivity through better technology somehow bad?
I am pro FOSS but can't understand this comment.
I'm not sure why you took the very general statement about AI being corp-over-worker to mean paid models vs free models? The technology itself heavily favors corporations, because the resources needed to create and operate the technology is massive, and is largely not available to individuals. Most of the freely downloadable models (and certainly the most popular ones) were trained by corporations. And there are many more models that are not available to individuals, only to corps.
> I work with AI every day and sum total of my token spend across all providers is less than a single NVidia H100 card I'd have to buy (from a pretty big corporation!), at the very least, for comparable purpose?
You don't need an H100 to run SLMs. You don't need LLMs that require commercial-grade memory capacities.
> How are self-hosted LLMs not copying the work of millions without compensating them for it?
Most are, especially when they're training data is closed-source. The ones that have open-source training data tend not to contain infringed-upon copywritten data. There is a huge issue right now with ML models being falsely called "open source", when in fact the source material needed to recreate them is not even known, much less provided publicly, which is probably the cause of the confusion.
> How is the push for more productivity through better technology somehow bad?
It's not, inherently. In practice though, it almost always means that workers are expected to be additionally productive, without being additionally compensated.
Secondly, you are not writing anything you get from an LLM. You prompt it and it spits out other people's code, stripped of attribution.
This is what children do: Ask someone to fix something for you without understanding the result.
No one objects to a human writing code and selling copies.
Apart from that, this is the commercial Picasso who loved money. His early pre-expressionist paintings are godlike in execution, even if someone else has painted a Pierrot before him.
Do you feel the same way when you delegate assignments to more junior developers and they come back with code?
> a far higher intensity
I'm not sure what this is supposed to mean. The code that I've gotten is riddled with mistakes and fabrications. If I were to use it directly, it would significantly slow my pace. Likewise, when I use LLMs to offer alternative methods to accomplish something, I have to take the time to sit down and understand what they're proposing, how to actually make it work, and whether that route(s) would be better than my original idea. That is a significant speed reduction.
The only way I can imagine LLMs resulting in "far higher intensity" is if I was just yolo'ing the code into my program, and then doing frantic integration, correction, and bugfix work afterwards.
Sure, that's "higher intensity", but that's just working harder and not smarter.
You may get to the same destination, but it is not the same activity
It's definitely a personality thing, but that's so much more productive for me, than convincing myself to do all the work from scratch after I had a design.
I guess this means I hate coding, and I only love the dopamine from designing and polishing my work instead of making things work. I'm not sure though, this feels like the opposite of hate coding.
Or are you calling an LLM a "clone" of you? In that case, it's more, "if you create a flawed enough starting premise, anything is possible".
That's where we start to disagree what future looks like, then.
It's not there yet, in that the LLM-clone isn't good enough. But amusingly a not nearly good enough clone of me already made me more productive, in that I'm able to deliver more while maintaining the same level of personal satisfaction with my code.
If I want to spend my time refactoring and bugfixing and rewriting and integrating, rather than writing from scratch and bugfixing, I can definitely achieve that by using LLM code, but the overall time has never felt different to me, and in many cases I've thrown out the LLM code after several hours due to either sheer frustration with how it's written, or due to discovering that the structure it's using doesn't work with the rest of the program (see: anything related to threading).
Can I just about corral the LLM into producing working output? Yea, sometimes. From a technology perspective, that’s pretty cool!
But is it a productivity boost? Absolutely not. Like not even close. Every time it would have been faster for me to just write the code myself.
I really don’t know how to square the vast gulf between my experiences and many other peoples’.
You don't need a multi-million dollar LLM to give you slightly different boilerplate snippets when you already have a text editor on your computer to save them.
it's not about having the LLM write some "starter pack" toy scaffold. i means when i implement functionality across different classes and need to package that up and adapt, i can just tell the LLM how to approach it and it can produce entire sections of code that would literally just be adaptations of certain things. or to refactor certain pieces that would just be me re-arranging shit.
maybe that's not "boilerplate", but to me it's a collosal waste of my time that could be spent trying to solve a new problem. you can't package that up into a "code snippet" and it's not worth the time carefully crafting templates. LLM can do it faster, better, and cost me near nothing.
> LLM can do it faster, better, and cost me near nothing.
And this is one the thing I'm skeptical about. The above use case is a symptom of all code and no design. It is a waste of time because you're putting yourself in a corner, architecture wise. Kinda like building on a crooked foundation.
I've never done refactoring where I'm writing a lot of code, it's mostly just copy-paste and rebuilding the connection between modules (functions, classes, files, packages,...). And if the previous connections were well understood and you have a clear plan for the new design, then it's a no-brainer to get there. Same when adapting code, I'm mostly deleting lines and renaming variables (regex is nice).
Maybe I'm misunderstanding things, but unless it's for small scripts or very common project types, I haven't seen the supposed productivity gain compared to traditional tooling.
1) refactoring. copy paste, re-arrange, extract, delete and rebuild the connection. i have the mental model and tell the LLM do do it across multiple files or classes. does it way faster and exactly how i would do it given the right prompt which is just a huge file that dictates how things are structured, style, weird edge cases i encountered as time goes on.
2) new features or sections based on existing. i have a service class and want to duplicate and wire up different sections across domains. not easy enough to just be templated, but LLM can do it and understand the nuances. again, generate multiple files across classes no problem.
i can do all these things "fast". i can do them even faster when using the LLM, it offloads the tediousness and i save my brian for other tasks. alot of times i'm just researching my next thing while it chugs away. i come back, lint and review and i'm good to go.
i'm honestly still writing the majority of the code myself, esp if it's like design stuff or new features where the requirements and direction aren't as clear, but when i need to it gives me a huge boost.
keeps me in the flow, i basically recharge while continuing to code. and it's not a small script but a full fledged app, albeit very straightforward architecture wise. the gains are very real. i'm just surprised at the sentiment on HN around it. it's not even just skepticism but outright dogging on it.
I do see more people who seem to be using it to replace coding skill rather than augment it, and I do worry about management's ability to differentiate between those versus just reverting to LoC. And whether it will become a demand for more code, for the same pay.
It’s when you try to use an exotic language, you realize the amount of work that has been done to minimize dev time in more mainstream languages.
> This comment section really shows the stark divide between people who love singing and thus hate AI-assisted singing, and people who hate singing and thus love AI-assisted singing.
> Honestly, I suspect the people who would prefer to have someone or something else do their singing, are probably the singers who are already outputting the worst singing right now.
The point is: just because you love something, doesn't mean you're good at it. It is of course positively correlated with it. I am in fact a better singer because I love to sing compared to if I never practiced. But I am not a good singer, I am mediocre at best (I chose this example for a reason, I love singing as well as coding! :-D)
And while it is easier to become good at coding than at singing - for professional purposes at least - I believe that the effect still holds.
And I think we do tend to (rightfully) look down on e.g. singers who lip-sync concerts or use autotune to sing at pitches they otherwise can't, nevermind how we'd react if one used AI singing instead of themselves.
Yes, loving something is no guarantee of skill at it, but hating something is very likely to correspond to not being good at it, since skills take time and dedication to hone. Being bad at something is the default state.
Another analogy would be with sound engineering. I've met sound engineer who hate their job as they would rather play music. They are also the ones whose jobs are likely to be replaced by AI. And I would argue that the argument stand stills. AI Sound Engineers who hate working on sound are often the bad sound engineers.
I tried to cover this particular case with:
> And while it is easier to become good at coding than at singing - for professional purposes at least - I believe that the effect still holds.
---
> Yes, loving something is no guarantee of skill at it, but hating something is very likely to correspond to not being good at it, since skills take time and dedication to hone. Being bad at something is the default state.
I tried to cover this particular case with:
> It is of course positively correlated with it.
---
> Being bad at something is the default state.
Well, skill-wise yes. But being talented at something can happen, even when you hate something.
Autotune is de rigueur for popular music.
In general, I'm not sure that I agree with looking down on people.
AI is like jet fuel for me. It’s the translation layer between specs and code I’ve always wanted. It’s a great advisor for implementation strategies. It’s a way to try new strategies in code quickly.
I don’t need to get anyone else to review my code. Most of this is for personal projects.
I don’t really write professionally, so I don’t have a ton of need for it to manage realities of software engineering (large codebases, peer reviews, black box internal systems, etc). That being said - I do a reasonable amount of embedded Linux work, and AI understands the Linux kernel and device drivers very well.
To extend your metaphor: AI is like a magic microphone that makes all of my singing sound like Tony Rice, my personal favorite singer. I’ve always wanted to sound like him - but I never will. I don’t have the range or the training. But AI allows my coding level to get to that corresponding level with writing software.
I absolutely love it.
Do you love coding, or do you love creating programs?
It seems like the latter given your metaphor being a microphone to make you seem like you could sing well, i.e. wanting the end state itself rather than the achievement via the process.
"wanted to sound like him" vs "wanted to sing like him"
The code is a tool. Nothing more.
I love the shed I built for my family. I don’t have a single feeling for the hammer I used to build it.
For the record: I can sing well. I just can’t sound like Tony Rice. I don’t have his vocal cords or training.
I made a cyber deck several months back, and I opted to carve the case from wood rather than 3d printing or using a premade shell. That hands-on work is something I'm proud of. I don't even use the deck much, it was for the love of building one.
To be fair, I don't have any problem with people who do their jobs for the paycheck alone, because that's the world capitalism has forced us into. Companies don't care about or reward you for the skills you possess, only how much money you make them (and they won't compensate you properly for it, either), so there's no advantage to tying your self-worth up in what you produce for them.
But I do think that it's sad we're seeing creative skills, whether writing coding composing or drawing, be devalued by AI as we are.
> For the record: I can sing well.
That is awesome! It's a great skill to have, honestly. As someone whose body tends to be falling apart more than impressing anyone, I envy that. :)
My experience with LLMs leads me to believe that it's more likely that the magic microphone in this case makes you sound still very, very bad, but being that you're not a good singer you can't tell the difference between very, very bad and Tony Rice's singing. You sang the song, though, i.e. the solution was reached.
I can't reconcile this with my own view of things but I think "for professional purposes at least" is doing a lot of work in your sentence and I get the feeling you intend to say "good enough" by adding that bit.
Most programmers are very bad at programming (and problem solving) and only if they were compared to absolute beginners with zero insight could they be said to be "good" (and most of that comes down to them at least knowing the names of maybe a couple of concepts, etc., which makes for at least a partial map of the knowledge space). Most of them will never become good at what they do either, but will stay middling because they basically just glue libraries together and learn surface level things over and over.
If all you've ever done is learn a language, a backend framework in that language, learn how to use SQL, learn JavaScript, learn a couple of frontend frameworks for JavaScript, you've just basically learned a bunch of trivia that at best could be considered table stakes for a certain part of the industry.
If you're not actually doing free form problem solving, implementing things from scratch, reading code you didn't have to read and building and reinforcing your own fundamentals in other ways you won't ever be a good programmer.
I've worked with people who've spent 10+ years in the industry only to be essentially useless without frameworks and libraries and it regularly showed in how poor their output was. It wasn't any better when they did have frameworks and libraries to use, but they could pretend it was because at least a solution was reached. The truth is that in most of those cases a much better version could've been reached by simply re-implementing only the parts that were needed, but these types of programmers don't have the capability to do so.
Coding is just a means to an end - creating enough business value to convince the company I’m working for to give me money that I can exchange for food and shelter.
If AI can help me do that faster, I’m going to use it. Neither do I want to spend months procuring hardware and managing building out a server room (been there done that) when I can just submit some yaml/HCL and have it done for me in a few minutes.
Just last week it wrote me a whole application and gui to open a webpage at a specific time. Yeah it breaks after the first trigger but it works for what I need.
There's a lot of literature about these concerns and a lot of methodologies to alleviate them. I (and others) are judging LLMs in light of those concerns. Mostly because speed was never an issue for us in prototypes and scripts (and it can be relaxing to learn about something while scripting it). The issue is always reliability (can it do what I want) and maintainability (can I change it later). Performance can also be a key issue.
Aside: I don't know the exact problem you were solving, but based on the description, that could have been done with systemd timers (macOS services are more of a pain to write). Yes, there's more to learn, but time triggering some command is a problem solved (and systemd has a lot more triggers).
I could have used Windows Task Scheduler but having a nice gui with a custom icon is much more pleasant to use.
But the simple fact is I'm much more productive with AI and I believe this is likely true for most programmers once they get adjusted.
So for production, what I love the most doesn't really matter, otherwise I'd be growing tomatoes and guiding river rafting expeditions. I'm resigned to the fact the age of manually writing "for loops" is largely over, at least in my case.
Documentation needs to be by humans for humans, it's not a box that's there to be filled with slop.
This is true for producing the documentation but if there is an LLM that can take said documentation and answer questions about it is a great tool. I think I get the answer far quicker with LLM than sifting through documentation when looking for existence of a function in a library or a property on an object.
(And I don't enjoy the value judgement)
Yes, there are tasks or parts of the code that I'm less interested in, and would happily either delegate or negotiate-off to someone else, but I wouldn't give those to a writer who happens to be able to write in a way that approximates program code, I'd give them to another dev on the team. A junior dev gets junior dev tasks, not tasks that they don't have the skills to actually perform, and LLMs aren't even at an actual junior dev level, imhe.
I noted in another comment that I've also used LLMs to get ideas for alternate ways to implement something, or to as you said "jump start" new files or programs. I'm usually not actually pasting that code into my IDE, though- I've tried that, and the work to make LLM-generated code fit into my programs is way more than just writing out the bits I need, where I need. That is clearly not the case for a lot of people using LLMs, though.
I've seen devs submitting PRs with giant blocks of clearly LLM-gen'd code, that they've tried to monkey-wrench into working with the rest of the program (often breaking conventions or secure coding standards). And these aren't junior devs, they're devs that have been working here for years and years.
When you force them to do a code review, they know it's not up to par, but there is a weird attitude that LLM-gen'd code is more acceptable to be submitted with issues than personally-written code. As though it's the LLM's fault or job to fix, even though they prompted and copied and badly-integrated and PR'd it.
And that's where I think there is a stark divide. I think you're on my side of the divide (at least, I didn't get the impression that you hate coding), it just sounds like you haven't really seen the other side.
My personal dime-store psych theory is that it's the same mental mechanism that non-technical computer users fall into of improperly trusting/ believing computers to produce correct information, but now happening to otherwise technical folks too because "AI" is still a black box technology to most of us, like computers in general are to non-techies.
LLMs are really really cool, and really really impressive to me, and I've had 'wow' moments where they did something that makes you forget what they are and how they work, but you can't let that emotional reaction towards it override the part that knows it's just a token chain. When you do, people end up (obviously on the very extreme end) 'dating' them, letting them make consequential "decisions", or just over-trusting their output/code.
Alright, please stop using SDK's, google, stackoverflow, any system libraries. You prefer to do it for yourself right?
SDKs and libraries are there to provide common (as in, used repeatedly, by many) functions that serve as BUILDING BLOCKS.
If you import a library and now your program is complete, then you didn't actually make a useful program, you just made a likely less efficient interface for the library.
BUT ALSO-
SDKs and libraries are *vetted* code. The advantage you are getting isn't just about it having been written for you, it's about the hundreds of hours of human code review, iteration, and thought, that goes into those libraries.
LLM code doesn't have that, so it's not about you benefitting from the knowledge and experience of others, it's purely about reducing personally-typed LoC.
And yes, if you're wholesale copy-pasting major portions of your program from stack overflow, I'd say that's about as bad as copy-pasting from ChatGPT.
Have we forgotten that we advanced in software by building on the work of others?
People aren't taking LLM code and then thoughtfully refactoring and improving it, they're using it to *avoid* doing that, by treating the generated code as though it's already had that done.
That's why the pro-LLM-code people in this very thread are talking about using it to automate away the parts of the coding they don't like. You really think they're then going to go back and improve on the code past it minimally working?
There will be no advancement from that, just mediocre or bad code going unreviewed and ignored until it breaks.
To clarify my questions: - Who here uses LLMs to generate code for bigger projects at work? (>= 20k lines of code) - If you use LLMs for bigger projects: Do you need to change your prompting strategy to get good results? - What programming languages are you using in your code bases? - Are there other people here who experience that LLMs are no help for non trivial problems?
One thing I forgot to mention is asking LLMs questions from within the IDE instead of doing a web search... this works quite nice, but again, it is not a crazy productivity boost.
The codebase is not too old and has grown without too much technical debt, with complex prompts I never had decent success. Its usefull for quick "what does this do" checks but any real functionality seems to be lacking.
Maybe I'm not refining my prompts good enough but doing so would take longer than implementing it myself.
Recently I tried Jetbrains Junie, which acts like Claude if I understand it correctly.
I had a really refined prompt, ran it three times with adjustments and fine tuning but the result was still lacking. So I tossed it and wrote it myself. But watching the machine nearly getting it right was still impressive.
I've had massive success with java, js/TS, html css, go, rust, python, bitbucket pipelines/GitHub actions, cdk, docker compose, SQL, flutter/dart, swift etc.
Aren't you worried that overtime you'll rely on it too much and your offhand knowledge will get worse?
I do write plenty of things myself. Sometimes, I ignore AI completely and write 100s of lines. Sometimes, I take copilot suggestions every other line, as I'm writing something "common" and copilot can "read" my mind. And sometimes, I write 100s of lines purely by prompting. It is a fine line when to do which; also depends on mood.
I am not worried about that as I spend hours everyday reading. I'm also the type of person who, when something is needed in a document, do not search for it using CTRL+F, but manually look thru it. It always takes more time but I also learn adjacent things to the topic I need.
And I never commit a single line from AI without reading and understanding it myself. So it might come up with 100 line solution for me, but I probably already know what I wanted and off chance it came up with something correct but in a way I did not know, I do read and learn it.
Ultimately, to me, the knowledge that I can !reset null in docker compose override is important. Remembering if it is !null reset or reset !null or !reset null (i.e., syntax) is not important. My offhand knowledge is not getting worse as I am constantly learning things; I just focus less on specific syntaxes or API signatures now.
You can apply the same argument with IDE. Almost all developers will fail to write proper JS/TS/Java etc without IDE help.
Is it possible the person claiming success with all these languages/tools/technologies is just on a junior level and is subjectively correct but has no point of reference how fast coding is for seniors and how quality code looks like?
A. They have no skills/exp to judge AI output
B. They don't learn from sudden magical wall of code output
C. They don't get to explore; thus don't learn.
D. Ultimately, LLMs act as a bad drug to them that keeps them dependent and stagnant.
E. LLMs are really good for higher end of senior devs. This also means, they don't need as many Juniors anymore and they don't mentor juniors much. This is the biggest loss for Juniors.
Anyway, if you want to, LLMs can today help with a ton of programming languages and frameworks. If you use any of the top 5 languages and it still doesn't work for you, either you're doing some esoteric work or you're doing it wrong.
My only conditions:
- It must be demonstrated by adding a feature on a bigger code base (>= 20 LOC)
- The added feature cannot be a leaf feature (means it must integrate with the rest of the system at multiple points)
- The prompting has to be less effort/faster than to type the solution in the programming language
You can chose any programming language/framework that you want. I don't care if it is Java, JavaScript, Typescript, C, Python, ... hell, I am fine with any language with or w/o a framework.
It just surprises me, that you write you had massive successes with "java, js/TS, html css, go, rust, python, bitbucket pipelines/GitHub actions, cdk, docker compose, SQL, flutter/dart, swift etc.", if you include the usual libraries/frameworks and the diverse application areas for these technologies, even with LLMs support it seems to me crazy to be able to make meaningful contributions in non trivial code bases.
Concerning SQL I can report another fail with LLMs, in a trivial code base with a handful of entities the LLM cannot come up with basic window functions.
I would be very interested if you could write up a blog post or could make a youtube video demonstrating your prompting skills... Perhaps demonstrating with a bigger open source project in any of the mentioned languages how to add a non trivial feature with your prompting skills?
The stuff I work on for company is confidential and even getting authorization to use AI was such a hassle.
Based on some of your replies, I think you have an impression of current generation AIs that is 100% wrong. I can not blame you as the impression you have, is what the AI companies want you to have, that's what they are hyping.
In another comment, you mentioned someone should demo how AI can add a non-leaf feature to a non-trivial LOC codebase. This is what AI companies say AI can do. But the truth is, (current gen) AIs can not do this except a few rare cases. I can not demo this to you as I can't do this and do not attempt to do it either on day to day tasks.
The issue is context. What you are asking requires AI to have a huge amount of context that it simply is not equipped to handle (at least not right now).
What AIs are really good at is to do small fragment of a task given enough clear requirements.
When I want AI to write a Handler in my Controller, I don't just ask it to "write a function to handle POST call for entity E."
I write the javadoc /* */ comment that defines the signature and explains a little about how the core process of this handling works. I can even copy/paste similar handler from another controller if I think that will help.
Ultimately, my brain already knows the input, output and key transformations that needs to happen in this function. I just write minimal amount (esp comments) and get AI to complete the rest.
So if I need to write a non-leaf feature, I will break it down to several leaf features and then pass it on to AI and if needed, manually assemble them.
I had to write 500LOC bash script to handle a software deployment. This is not the way to do it but I was forced by circumstances created by someone else. Anyways, if I had to write the whole thing by hand, it'd take multiple days as bash syntax is not forgiving and the stuff I needed to do in the script were quite complex/crazy (and stupid).
I think I wrote about 50+ lines of text describing the whole process, which you can think of as a requirement document.
With a few tries, I was able to get the whole script with near accuracy. My reading revealed some issues. Pointed them to AI. It fixed them. Tests revealed some other issues. Again, AI fixed them after pointing out. I was able to get the whole thing done in just an hour or so.
You just described every existing legacy project^^
In my search I just found trivial examples.
My critic so far:
- Examples seem always to be creating a simple application from scratch
- Examples always use super common things (like create a blog / simple website for CRUD)
What I would love to see (see elsewhere): Adding a non trivial feature to a bigger code base. Just a youtube video/demonstration. I don't care about language/framework etc. ...
Fully agreed, that LLMs/assisted coding is nice for these kind of contained tasks.
Programming language / stack plays plays a big role, I presume.
Let's stop pretending or denying it: most of us would delegate our work code to somebody else or something else if we could.
Still, prompting LLMs well requires eloquence and expressiveness that many programmers don't have. I have started deriving a lot of value from those LLMs I chose to interact with by specifying clear boundaries on what's the priority and what can wait for later and what should be completely ignored due to this or that objective (and a number of other parameters I am giving them). When you do that well, they are extremely useful.
I am also barely using LLMs at the moment. Even 10% of the time would be generous.
What I was saying is that I have tried different ways of interacting with LLMs and was happy to discover that the way I describe stuff to another senior dev actually works quite fine with an LLM. So I stuck to that.
Again, if an LLM is not up to your task, don't waste your time with it. I am not advocating for "forget everything you knew and just go ask Mr. AI". I am advocating for enabling and productivity-boosting. Some tasks I hate, for some I lack the deeper expertise, others are just verbose and require a ton of typing. If you can prompt the LLM well and vet the code yourself after (something many commenters here deliberately omit so they can happily tear down their straw man) then the LLM will be a net positive.
It's one more tool in the box. That's all there is to it really. No idea why people get so polarizing.
Honestly you’re trying to prove AI is ineffective by telling us it didn’t work with your ineffective protocol. That is not a strong argument.
* experiment with multiple models, preferably free high quality models like Gemini 2.5. Make sure you're using the right model, usually NOT one of the "mini" varieties even if its marketed for coding.
* experiment with different ways of delivering necessary context. I use repomix to compile a codebase to a text file and upload that file. I've found more integrated tooling like cursor, aider, or copilot, are less effective then dumping a text file into the prompt
* use multi-step workflows like the one described [1] to allow the llm to ask you questions to better understand the task
* similarly use a back-and-forth one-question-at-a-time conversation to have the llm draft the prompt for you
* for this prompt I would focus less on specifying 10 results and more about uploading all necessary modules (like with repomix) and then verifying all 10 were completed. Sometimes the act of over specifying results can corrupt the answer.
[1]: https://harper.blog/2025/02/16/my-llm-codegen-workflow-atm/
I'm a pretty vocal AI-hater, partly because I use it day to day and am more familiar with its shortfalls - and I hate the naive zealotry so many pro-AI people bring to AI discussions. BUTTT we can also be a bit more scientific in our assessments before discarding LLMs - or else we become just like those naive pro-AI-everything zealots.
Either way, when a model starts making dumb mistakes like that these days I start a fresh conversation (to blow away all of the bad tokens in the current one), either with that model or another one.
I often switch from Claude 3.7 Sonnet to o3 or o4-mini these days. I paste in the most recent "good" version of the thing we're working on and prompt from there.
Hard disagree, I get to hyperfocus on making magical things that surprise and delight me every day.
I don’t think this is the case, if anything the opposite is true. Most of us would like to do the work code but have realized, at some career point, that you’re paid more to abstract yourself away from that and get others to do it either in technical leadership or management.
I'll be a radical and say that I think it depends and is very subjective.
Author above you seems to enjoy working on code by itself. You seem to have a different motivation. My motivation is solving problems I encounter, code just happen to be one way out of many possible ones. The author of the submission article seems to love the craft of programming in itself, maybe the problem itself doesn't even matter. Some people program just for the money, and so on.
Laughably narrow-minded projection of your own perspective on others.
Enjoying to code/knit is fine but we can no longer expect to get paid well to do it.
Just because I utilize the services of others for some things does not mean that it should be expected I want to utilize the service of others for all things.
This is a preposterous generalization and exactly why I said the OP premise is laughable.
Further, you’ve shifted OP’s point from subjective enjoyment of an activity to getting “paid well” - this is an irrelevant tangent to whether “most” people in general would delegate work if they could.
Answering your question:
- That there are annoying tasks none of us look forward to doing.
- That sometimes you have knowledge gaps and LLMs serve as a much better search engine.
- That you have a bad day but the task is due tomorrow. Happened to us all.
I am not "laughably projecting on others", no. I am enumerating human traits and work conditions that we all have or had.
OBVIOUSLY I did not mean that I would delegate all my work tomorrow if I could. I actually do love programming.
2. Some of the modern LLMs generate very impressive code. Variables caching values that are reused several times, utility functions, even closure helpers scoped to a single function. I agree that when the LLM code's quality falls bellow a certain threshold then it's better in every way to just write it yourself instead.
It requires magical incantations that may or may not work and where a missing comma in a prompt can break the output just as badly as the US waking up and draining compute resources.
Has nothing to do with eloquence
I saw your objections to other comments on the basis of them seemingly not having a disdainful attitude towards coding they do for work, specifically.
I absolutely do have tasks, coding included, that I don't want to do, and find no joy in. If I can have my manager assign the task to someone else, great! But using an LLM isn't that, so I'm still on the hook for ensuring all the most boring parts of that task (bugfixing, reworks, integration, tests, etc) get done.
My experience with LLMs is that they simply shift the division of time away from coding, and towards all the other bits.
And it can't possibly just be about prompting. How many hundreds of lines of prompting would you need to get an LLM to understand your coding conventions, security baselines, documentation reqs, logging, tests, allowed libraries, OSS license restrictions (i.e. disallowed libraries), etc? Or are you just refactoring for all that afterwards?
Maybe you work somewhere that doesn't require that level of rigor, but that doesn't strike me as a good thing to be entrenching in the industry by increasing coders' reliance on LLMs.
Where I use LLMs:
1. Super boring and annoying tasks. Yes, my prompts for those include various coding style instructions, requests for small clarifying comments where the goal of the code is not obvious, tests. So, no OSS license restrictions. Libraries I specify most of the times I used LLMs (and only once did I ask it to suggest a library). Logging and telemetry I add myself. So long story short, I use the LLM to show me a draft of a solution and then mercilessly refactor it to match my practices and guidelines. I don't do 50 exchanges out of laziness, no.
2. Tasks where my expertise is lacking. I recently used an LLM to help me with making a `.clone()`-heavy Rust code to become nearly zero-copy for performance reasons -- it is a code on a hot path. As much as I love Rust and I am fairly good at it (realistically I'm IMO at 7.5 / 10), all the lifetimes and zero-copy semantics I still don't know yet. A long session with an LLM after, I emerged both better educated and with a faster code. IMO a win-win.
Thanks for the follow-up!
Thought it was obvious.
How do you verify code that you don't have the expertise to write on your own?
Not me. I code because I love to code, and I get paid to do what I love. If that's not you…find a different profession?
Delegating part of that to an LLM so I can code the stuff I love is a big win for my motivation and is making me doing the work tasks with a bit more desire and pleasure.
Please don't forget that most of us out there can't code for money anything that their heart wants. If you can, I'd be happy for you (and envious) but please understand that's also a fairly privileged life you'd be having in that case.
Part of the joy of craft is the actual process of building a thing, even if the thing you're build is itself "boring". One of my clients right now is a React/Next.js app, which in terms of architecture I find deeply problematic (I tend to advocate vanilla JS, web components, close-to-browser-metal approaches, etc.)—but I still find ways to enjoy the work I do and furthermore I'm proud of the work that I do. I find it anathema that I'd offload any of that craft to a synthetic code text extruder.
100% this.
Do you ever read my comments, or do you just imagine what I might have said and reply to that?
Where does that idea that "by definition the models know more than you" come from?
Nothing is truly 100% safe or free of bugs. What I meant with my comment up-thread was that I have enough experience to have a fairly quick and critical eye of code, and that has saved my skin many times.
This isn't how it works, psychologically. The whole time I'm manual coding, I'm wondering if it'd be "easier" to start prompting. I keep thinking about a passage from The Road To Wigan Pier where Orwell addresses this effect as it related to the industrial revolution:
>Mechanize the world as fully as it might be mechanized, and whichever way you turn there will be some machine cutting you off from the chance of working—that is, of living.
>At a first glance this might not seem to matter. Why should you not get on with your ‘creative work’ and disregard the machines that would do it for you? But it is not so simple as it sounds. Here am I, working eight hours a day in an insurance office; in my spare time I want to do something ‘creative’, so I choose to do a bit of carpentering—to make myself a table, for instance. Notice that from the very start there is a touch of artificiality about the whole business, for the factories can turn me out a far better table than I can make for myself. But even when I get to work on my table, it is not possible for me to feel towards it as the cabinet-maker of a hundred years ago felt towards his table, still less as Robinson Crusoe felt towards his. For before I start, most of the work has already been done for me by machinery. The tools I use demand the minimum of skill. I can get, for instance, planes which will cut out any moulding; the cabinet-maker of a hundred years ago would have had to do the work with chisel and gouge, which demanded real skill of eye and hand. The boards I buy are ready planed and the legs are ready turned by the lathe. I can even go to the wood-shop and buy all the parts of the table ready-made and only needing to be fitted together; my work being reduced to driving in a few pegs and using a piece of sandpaper. And if this is so at present, in the mechanized future it will be enormously more so. With the tools and materials available then, there will be no possibility of mistake, hence no room for skill. Making a table will be easier and duller than peeling a potato. In such circumstances it is nonsense to talk of ‘creative work’. In any case the arts of the hand (which have got to be transmitted by apprenticeship) would long since have disappeared. Some of them have disappeared already, under the competition of the machine. Look round any country churchyard and see whether you can find a decently-cut tombstone later than 1820. The art, or rather the craft, of stonework has died out so completely that it would take centuries to revive it.
>But it may be said, why not retain the machine and retain ‘creative work’? Why not cultivate anachronisms as a spare-time hobby? Many people have played with this idea; it seems to solve with such beautiful ease the problems set by the machine. The citizen of Utopia, we are told, coming home from his daily two hours of turning a handle in the tomato-canning factory, will deliberately revert to a more primitive way of life and solace his creative instincts with a bit of fretwork, pottery-glazing, or handloom-weaving. And why is this picture an absurdity—as it is, of course? Because of a principle that is not always recognized, though always acted upon: that so long as the machine is there, one is under an obligation to use it. No one draws water from the well when he can turn on the tap. One sees a good illustration of this in the matter of travel. Everyone who has travelled by primitive methods in an undeveloped country knows that the difference between that kind of travel and modern travel in trains, cars, etc., is the difference between life and death. The nomad who walks or rides, with his baggage stowed on a camel or an ox-cart, may suffer every kind of discomfort, but at least he is living while he is travelling; whereas for the passenger in an express train or a luxury liner his journey is an interregnum, a kind of temporary death. And yet so long as the railways exist, one has got to travel by train—or by car or aeroplane. Here am I, forty miles from London. When I want to go up to London why do I not pack my luggage on to a mule and set out on foot, making a two days of it? Because, with the Green Line buses whizzing past me every ten minutes, such a journey would be intolerably irksome. In order that one may enjoy primitive methods of travel, it is necessary that no other method should be available. No human being ever wants to do anything in a more cumbrous way than is necessary. Hence the absurdity of that picture of Utopians saving their souls with fretwork. In a world where everything could be done by machinery, everything would be done by machinery. Deliberately to revert to primitive methods to use archaic took, to put silly little difficulties in your own way, would be a piece of dilettantism, of pretty-pretty arty and craftiness. It would be like solemnly sitting down to eat your dinner with stone implements. Revert to handwork in a machine age, and you are back in Ye Olde Tea Shoppe or the Tudor villa with the sham beams tacked to the wall.
>The tendency of mechanical progress, then, is to frustrate the human need for effort and creation. It makes unnecessary and even impossible the activities of the eye and the hand. The apostle of ‘progress’ will sometimes declare that this does not matter, but you can usually drive him into a comer by pointing out the horrible lengths to which the process can be carried.
sorry it's so long
The funny thing is I agree with other comments, it is just kind of like a really good stack overflow. It can’t automate the whole job, not even close, and yet I find the tasks that it cannot automate are so much more boring (the ones I end up doing).
I envy the people who say that AI tools free them up to focus on what they care about. I haven’t been able to achieve this building with ai, if anything it feels like my competence has decreased due to the tools. I’m fairly certain I know how to use the tools well, I just think that I don’t enjoy how the job has evolved.
Gone are those days.
Most of AI-generated programming content I use are comments/explanations for legacy code, closely followed by tailored "getting started" scripts and iterations on visualisation tasks (for shitty school assignments that want my pyplots to look nice). The rest requires an understanding, which AI can help you achieve faster (it's read many a book related to the topic, so it can recall information a lot like an experienced colleague may), but it can't confer capital K Knowledge or understanding upon you. Some of the tasks it performs are grueling, take a lot of time to do manually, and provide little mental stimulation. Some may be described as lobotomizing and (in my opinion) may mentally damage you in the "Jack Torrance typewriter" kinda way.
It makes me able to work on the fun parts of my job which possess the qualities the article applauds.
AI had nothing to do with my own loss of engagement, though certainly it won't cure what ailed me. In fact, AI promises to do to all of software development what the mechanized data mining process did to my sense of creative self-expression. It will squeeze all the fun out of it, reducing the joy of coding (and its design) to plug-and-chug, rinse, repeat.
IMHO the threat of AI to computer programming is not the loss of jobs. It's the loss of personal passionate engagement in the craft.
The vast majority of research is funded or incentivized in some way by the big internet companies. The big internet companies have a very narrow scope of problems that they are commercially interested in. They also have so much power and money that getting people to listen to diverse ideas and opinions is incredibly difficult, both commercially and academically because everyone somehow has to cater what they do to be in line with internet company practices.
And of course, the internet companies have found ways to industrialize their core competencies of data warehousing and analytics so that every year, fewer inputs (staff, hardware, software, data) are needed to achieve the same outputs.
I think that people are experiencing a loss of independence, and creative thinking. Not a loss of passion for the craft.
This has always been true in every craft, and it remains true for programmers in a post LLL world.
Most training data is open source code written by novice to average programmers publishing their first attempts at things and thus LLMS are heavily biased to replicate the naive, slow, insecure code largely uninformed by experience.
Honestly to most programmers early in their career right now, I would suggest spending more time reviewing code, and bugfixes, than writing code. Review is the skillset the industry needs most now.
But you will need to be above average as a software reviewer to be employable. Go out into FOSSland and find a bunch of CVEs, or contribute perf/stability/compat fixes, proving you review and improve things better than existing automated tools.
Trust me, there are bugs -everywhere- if you know how to look for them and proving you can find them is the resume you need now.
The days of anyone that can rub two HTML tags together having a high paying job are over.
The one time i pasted LLM code without reviewing it it belonged on accidentally quadratic.
It was obvious at first read, but probably not for a beginner. The accidental complexity was hidden behind API calls that weren't wrong, just grossly inefficient.
Problem might be, if you lose the "joy" and the "flow" you'll stop caring about things like that. And software is bloated enough already.
I don't know the last time I encountered a used (not random hobby projects) FOSS project that wasn't funded and supported by a company (with exceptions maybe only in the GNU software suite, but even then lots of authors there are making submissions using company email addresses).
I think it's totally acceptable to not make open-source contributions to those projects unless someone is paying you to.
This is fine, so long as the community decides what features they actually want to create the "menu" of unfunded objectives donors can sponsor
AI coding is similar. We just had a minor issue with ai generated code that was clearly not vetted as closely as it should have been making output it generated over a couple of months not as accurate as it should be. Obviously, it had to be corrected, then vetted and so on, because there is always time to correct things...
edit: What I am getting at is the old-fashioned, penny smart, but pound foolish.
I taught a lecture in my first-semester programming course yesterday. This is in a program for older students, mostly working while going back to school. Each time, a few students are selected to present their code for an exercise that I pick randomly from those they were assigned.
This guy had fancy slides showing his code, but he was basically just reading the code off the page. So I ask him: “hey, that method you call, what exactly does it do?”.
Um…
So I ask "Ok, the result from that method is assigned to a variable. What kind of variable is it?" Note that this is Java, the data type is explicitly declared, so the answer is sitting there on his slide.
Um…
So I tear into him. You got this from ChatGPT. That’s fine, if you need the help, but you need to understand what you get. Otherwise you’ll never get a job in IT.
His answer: “I already have a job in IT.”
Fsck. There is your vibe coder. You really do not want them working on anything that you care about.
That could be considered malpractice. I know our profession currently doesn't have professional standards, but it's just a side effect of it being very new and not yet solidified; it won't be long until some duty of care becomes required, and we're already starting to see some movement in that direction, with things like the EU CRA.
based on the current state of AI and the progress im witnessing on a month-by-month basis - my current prediction is there is zero chance AI agents are going to be coding and replacing me in the next few years. if i could short the startups claiming this, I would.
I'm willing to bet that in a few years most of the developers you know will be using LLMs on a daily basis, and will be more productive because of it (having learned how to use it).
As an example, just today I was trying to debug some weird WebSocket behaviour. None of the AI tools could help, not Cursor, not plain old ChatGPT with lots of prompting and careful phrasing of the problem. In fact every LLM I tried (Claude 3.7, GPT o4-mini-high, GPT 4.5) introduced errors into my debugging code.
I’m not saying it will stay this way, just that it’s been my experience.
I still love these tools though. It’s just that I really don’t trust the output, but as inspiration they are phenomenal. Most of the time I just use vanilla ChatGPT though; never had that much luck with Cursor.
A couple days ago I was looking for something to do so gave Claude a paper ("A parsing machine for PEGs") to ask it some questions and instead of answering me it spit out an almost complete implementation. Intrigued, I threw a couple more papers at it ("A Simple Graph-Based Intermediate Representation" && "A Text Pattern-Matching Tool based on Parsing Expression Grammars") where it fleshed out the implementation and, well... color me impressed.
Now, the struggle begins as the thing has to be debugged. With the help of both Claude and Deepseek we got it compiling and passing 2 out of 3 tests which is where they both got stuck. Round and round we go until I, the human who's supposed to be doing no work, figured out that Claude hard coded some values (instead of coding a general solution for all input) which they both missed. In applying ever more and more complicated solutions (to a well solved problem in compiler design) Claude finally broke all debugging output and I don't understand the algorithms enough to go in and debug it myself.
Of course I didn't use any sort of source code management so I could revert to a previous version before it was broken beyond all fixing...
Honestly, I don't even consider this a failure. I learned a lot more on what they are capable of and now know that you have to give them problems in smaller sections where they don't have to figure out the complexities of how a few different algorithms interact with each other. With this new knowledge in hand I started on what I originally intended to do before I got distracted with Claude's code solution to a simple question.
--edit--
Oh, the irony...
After typing this out and making an espresso I figured out the problem Claude and Deepseek couldn't see. So much for the "superior" intelligence.
Makes me wonder how many of the people who continue to argue that LLMs can't help with large existing codebases are missing that you need to selectively copy the right chunks of that code into the model to get good results.
What tools are you guys using? Are there none that can interactively probe the project in a way that a human would, e.g. use code intelligence to go-to-definition, find all references and so on?
Our Rust fly-proxy tree is about 80k (cloc) lines of code; our Go flyd tree (a Go monorepo) is 300k. Generally, I'll prompt an LLM to deal with them in stages; a first pass, with some hints, on a general question like "find the code that does XYZ"; I'll review and read the code itself, then feed that back to the LLM with questions like "summarize all the functionality of this package and how it relates to other packages" or "trace the flow of an HTTP request through all the layers of this proxy".
Generally, I'll take the results of those queries and have them saved in .txt files that I can reference in future prompts.
I think sometimes developers are demanding something close to AGI from their tooling, something that would do exactly what they would do (only, in the span of about 15 seconds). I don't believe in AGI, and so I don't expect it from my tools; I just want them to do a better job of fielding arbitrary questions (or generating arbitrary code) than grep or eglot could.
If your codebase is larger than that there are a few tricks.
The first is to be selective about what you feed into the LLM: if you know the work you are doing is in a particular area of the codebase, just paste that bit in. The LLM can make reasonable guesses about things the code references that it can't see.
An increasingly effective trick is to arm a tool-using LLM with a tool like ripgrep (effectively the "interactively probe the project in a way that a human would" idea you suggested). Claude Code and OpenAI Codex both use this trick. The smarter models are really good at deciding what to search for and evaluating the results.
I've built tools that can run against Python code and extract just the class, function and method signatures and their docstrings - omitting the actual code. If you code is well designed and has reasonable documentation that could be enough for the LLM to understand it.
https://github.com/simonw/symbex is my CLI tool for that
https://simonwillison.net/2025/Apr/23/llm-fragment-symbex/ is a tool I released this morning that turns Symbex into a plugin for my LLM tool.
I use my https://llm.datasette.io/ tool a lot, especially with its new fragments feature: https://simonwillison.net/2025/Apr/7/long-context-llm/
This means I can feed in the exact code that the model needs in order to solve a problem. Here's a recent example:
llm -m openai/o3 \
-f https://raw.githubusercontent.com/simonw/llm-hacker-news/refs/heads/main/llm_hacker_news.py \
-f https://raw.githubusercontent.com/simonw/tools/refs/heads/main/github-issue-to-markdown.html \
-s 'Write a new fragments plugin in Python that registers issue:org/repo/123 which fetches that issue
number from the specified github repo and uses the same markdown logic as the HTML page to turn that into a fragment'
AI help me a lot, you don't need search, just ask AI, and it provide the answer directly. After using AI, I have more time used on coding, more fun.
I just wish I saw more people doing this, rather than asking them to 'draw 80% of the owl'.
For being one of the few lucky ones that gets to stay around taking care of the software factory robots, or designing them, while everyone else that used to work at the factory is now queueing somewhere else.
I like programming but I have other hobbies I find fulfilling, and nothing stops me from programming with a pen and paper.
The bad vibes are not caused by lack of programming, they're caused by headsman sharpening his axe behind me.
A few lucky programmers will be elevated to God status and we're all fighting for those spots now.
Not everyone gets a seat at the starship.
The more people in general get disconnect from nature/physical world/reality. via layers of abstraction the more discontent they will become. These layers can be: 1) Automatics in agriculture. 2) Industries. 3) Electronics 4) Software 5) and now AI
Each higher layer depends on lower ones for its functioning without the need to worry about specifics and provides a framework for higher abstraction to work on.
The more we move up in hierarchy the more disconnected we become from the physical world.
To support this I observed that villagers in general are more jolly and content than city dwellers. In metropolis specially I saw that people are more rude, anxious and always agitated, while villagers are welcoming and peaceful.
Another good example is that of an artist finding it boring to guide AI even though he loves making paintings himself/herself.
In my case, I couldn't agree more, with the premise of the article, but my life today, is centered around writing software the very best that I can; regardless of value or price.
It's not very effective, if I were to be trying to make a profit.
It's really hard to argue for something, if the something doesn't result in value, as perceived by others.
For me, the value is the process. I often walk away from my work, once I have it up and shipping. I do like to take my work all the way through shipping, support, and maintenance, but find that my eye is always drawn towards new shores[0].
“A ship in harbor is safe, but that is not what ships are built for.”
–John A. Shedd
A lot of these discussions focus on craft in engineering and there's lots of merit there regarding AI tools and how they change that process, but I've found that folks who enjoy both the product side of things and the engineering side of things are thriving while those who were very engineering focused understandably feel apprehensive.
I will say, in my day job, which is often at startups, I have to focus more on the business / product side just given the phase of the company. So, I get joy from engineering craft in side projects or other things I work on in my own time to scratch the itch.
I cannot imagine why you cannot find flow using an AI assistant. I am definitely somebody who finds bliss in programming; and in my experience, AI assistants increase my bliss. My ideas are expressed in code much more efficiently. I spend less time in miserable documentation sets. I find myself fearlessly adding functionality that I would not have added if I weren't using an AI. And I have not a shadow of a doubt that my productivity has gone up dramatically. If anything, I find that AI assistants keep me in flow sate, particularly in cases where I would previously have had to wade through pages of ancient crusty Unix API documentation.
Maybe you should try a different AI. I found the ChatGPT AIs totally unhelpful, and counter-productive; but would recommend Claude Sonnet 3.7 without hesitation. I'm still working my way through other AIs. Others may be better at present, but so far I haven't found any that are dramatically better. It's hard to keep up with the furious pace of innovation.
It might also take a while to find your fu. I found the benefits to using an AI pretty much immediately; but I'm still discovering new and interesting ways to use my AI assistant.
So it causes developers to regularly fix what chatgpt is wrong about.
Not great.
Flow comes when challenge meets skill
Too much skill and too little challenge creates boredom;
too little skill and too much challenge creates anxiety
AI has reduced the challenge needed for achieving your goal, creating boredom
Remedy: find greater challenges?
From what I've seen using them would lead to more boredom. I like solving problems. I don't like doing code reviews. I wouldn't trust any AI generated code at this stage without reviewing it. If I could swap that around so I write code and AI gives me a reasonable code review and catches my mistakes I'd be much more interested.
My main worry about AI is that people just keep using the garbage that exists instead of trying to produce something better, because AI takes away much of the pain of interacting with garbage. But most people are already perfectly fine using garbage, so probably not much will change here.
https://news.ycombinator.com/item?id=42511441
People are going to be making the same judgements about AI-assisted coding in the near future. Sure, you could code everything yourself for your own personal enrichment, or simply because it's fun. But that will be a pursuit for your own time. In the realm of business, it's a different story: you are either proompting, or you're effectively stealing money from your employer because you're making suboptimal use of the tools available. AI gets you to something working in production so much faster that you'd be remiss not to use it. After all, as Milt and Tim Bryce have shown, the hard work in business software is in requirements analysis and design; programming is just the last translation step.
Companies know that the quality of the software they get back might be lower than if they hired the bestest, smartest developers in the world. But it doesn't matter because keeping the production cost of the asset low means that they can maximize long term profits.
Writing good software is not the same as writing profitable software.
What we really need are more studies on the productivity and skill outcomes of using AI tools. Microsoft did one, with results that were very negative towards AI tools [1]. I would like to see more (and much larger cohort) studies along this line, whether they validate Microsoft's conclusions or oppose them.
Personally I do not find AI coding tools to be useful at all - but I have not put extensive time into developing a "skillset" to use them optimally. Mainly because I believe, similar to what the study by MS found, that they are detrimental to my critical reasoning skills. If this turns out to be wrong, I would not mind evaluating changing course on that decision - but we need more data.
1. https://www.microsoft.com/en-us/research/wp-content/uploads/...
Typing isn't the fun part of it for me. It's a necessary evil to realize a solution.
The fun part of being an engineer for me is figuring out how it all should work and fit together. Once that's done - I already basically have all of the code for the solution in my head - I've just got to get it out through my fingers and slog through all the little ways it isn't quite right, doesn't satisfy x or y best practice, needs to be reshaped to accommodate some legacy thing it has to integrate that is utterly uninteresting to me, etc.
In the old model, I'd enjoy the first few hours or days of working on something as I was designing it in my mind, figuring out how it was all going to work. Then would come the boring part. Toiling for days or weeks to actually get all the code just so and closing that long-tail gap from 90% done (and all interesting problems solved) to 100% done (and all frustrating minutia resolved).
AI has dramatically reduced the amount of time the unsatisfying latter part of a given effort lasts for me. As someone with high-functioning ADD, I'm able to stay in the "stimulation zone" of _thinking_ about the hard / enjoyable part of the problem and let AI do (50-70%, depending on domain / accuracy) of the "typing toil".
Really good prompts that specify _exactly_ what I want (in technical terms) are important and I still have to re-shape, clean up, correct things - but it's vastly different than it was before AI.
I'm seeing on the horizon an ability to materialize solutions as quickly as I can think / articulate - and that to me is very exciting.
I will say that I am ruthlessly pragmatic in my approach to development, focusing on the most direct solution to meet the need. For those that obsesses over beautiful, elegant code - personalizing their work as a reflection of their soul / identity or whatever, I can see how AI would suck all the joy from the process. Engineering vs. art, basically. AI art sucks and I expect that's as true for code as it is for anything else.
1. AI Coding leads to a lack of flow.
2. A lack of flow leads to a lack of joy.
Personally, I can't find myself agreeing with the first argument. Flow happens for me when I use AI. It wouldn't surprise me if this differed developer to developer. Or maybe it is the size of requests I'm making, as mine tend to be on the smaller size where I already have an idea of what I want to write but think the AI can spit it out faster. I also don't really view myself as prompt engineering; instead it feels more like a natural back and forth with the AI to refine the output I'm looking for. There are times it gets stubborn and resistant to change but that is generally a sign that I might want to reconsider using AI for that particular task.
Managers usually can't carve out a full day - but a couple of hours is manageable.
See also this quote from Gergely Orosz:
Despite being rusty with coding (I don't code every day
these days): since starting to use Windsurf / Cursor with
the recent increasingly capable models: I am SO back to
being as fast in coding as when I was coding every day
"in the zone" [...]
When you are driving with a firm grip on the steering
wheel - because you know exactly where you are going, and
when to steer hard or gently - it is just SUCH a big
boost.
I have a bunch of side projects and APIs that I operate -
but usually don't like to touch it because it's (my)
legacy code.
Not any more.
I'm making large changes, quickly. These tools really
feel like a massive multiplier for experienced devs -
those of us who have it in our head exactly what we want
to do and now the LLM tooling can move nearly as fast as
my thoughts!
It's been amazing to spin up quick React prototypes during a lunch break of concepts and ideas for quick feedback and reactions.
They should be managing instead. Not to say that they can't code their own tools, but the statement sounds like a construction supervisor nailing studs or welding steel bars. Can work for a small team, but that's not your primary job.
I've been an engineering manager and it's a lot easier to make useful decisions that your team find credible if you can keep your toes in the water just a little bit.
My golden rule is to stay out of the critical path of shipping a user-facing feature: if a product misses a deadline because the engineering manager slipped on their coding commitments, that's bad.
The trick is to use your minimal coding time for things that are outside of that critical path: internal tools, prototypes, helping review code to get people unstuck, that kind of thing.
You still need to do that if you're using AI, otherwise how do you know if it's actually done a good job? Or are people really just vibe coding without even reading the code at all? That seems... unlikely to work.
I have thousands deadlines which are suddenly coming due and a bunch of code which is broken because some poor soul under the same pressure put something that "works" in. And it worked, until it didn't, and now it's my turn in the barrel.
Is this the joy?
I'm not complaining, I'm doing it for the good money.
Using Aider would probably solve the task in 5 minutes. Coding it in 30 minutes. The former choice would result in more time for other tasks or reading HN or having a hot beverage or walking in the sun. The second would challenge my rusting algorithmic skills and give me a better understanding of what I'm doing for the medium term.
Hard choice. In any case, I have a good salary, even with the latter option I can decide to spend good times.
The rest is glorified boilerplate that I find usually saps me of my energy, not gives me energy. I'm a fan of anything that can help me skip over that and get to the more enjoyable work.
I struggled with this at first too. But it just becomes another kind of joy. Think of it like jogging versus riding a motorcycle. Jogging is fun, people enjoy it, and they always will. But flying down a canyon road at 90MPH and racing through twists and turns is... way more fun. Once you've learned how to do it. But there's a gap there in which it stops being fun until you do.
I would say that programming without an AI is like riding a motorcycle. You’re in complete control and it’s down to your skill to get you we’re your going.
While using AI is like taking a train. You got to plan the route but you’re just along for the ride.
Which I think lines up to the article. If you want to get somewhere easily and fast, take a train. But that does take away the joy of the journey.
Also, stop gatekeeping AI tooling like it’s cheating. We’re not in a craft guild. The software landscape is full of shovelware and half-baked “best practices” that change more often than a JavaScript framework’s logo. I'm not here to honor the tradition of suffering through YAML hell or memorizing the 400 ways to configure a build pipeline. I’m here to make something work well, fast, and that includes leveraging AI like the power tool it is.
So yeah, you can keep polishing the turd pile of over-engineered “real” systems. The rest of us will be using AI to build, test, and ship faster than your weekly stand-up even finishes.
Some countries still treat the title "Engineer" as a protected title. Though I often now see it prefixed with professional or accredited or something so that people know they aren't an "engineer" they're an "Engineer".
I think most people who write software who think of the work they're doing as "real engineering" are like the draftsmen who draw up floor plans for local government approvals in civil engineering offices. If you're doing it over and over again, it's probably not engineering, it's probably just regular skilled Labor.
AI coding preserves flow more than legacy coding. You never have to go read documentation for an hour. You can continuously code.
This sounds a more likely reason for losing your joy if your passion is coding.
Then I shared it on HN and was subject to literal harassment.
Like pronouncing your surname? Holy hell.
Ok, I needed to get that off my chest, will go back to reading the article now.
Don't see any mention regarding this in the post, which is the common objection people have regarding vibe coding.
As a developer I'm bullish on coding agents and GenAI tools, because they can save you time and can augment your abilities. I've experienced it, and I've seen it enough already. I love them, and want to see them continue to be used.
I'm bearish on the idea that "vibe coding" can produce much of value, and people without any engineering background becoming wildly productive at building great software. I know I'm not alone. If you're a good problem solver who doesn't know how to code, this is your gateway. And you better learn what's happening with the code while you can to avoid creating a huge mess later on.
Developers argue about the quality of "vibe coded" stuff. There are good arguments on both sides. At some point I think we all agree that AI will be able generate high quality software faster than a human, someday. But today is not that day. Many will try to convince you that it is.
Within a few years we'll see massive problems from AI generated code, and it's for one simple reason:
Managers and other Bureaucrats do not care about the quality of the software.
Read it again if you have to. It's an uncomfortable idea, but it's true. They don't care about your flow. They don't care about how much you love to build quality things. They don't care if software is good or bad they care about closing tickets and creating features. Most of them don't care, and have never cared about the "craft".
If you're a master mason crafting amazing brickwork, you're exactly the same as some amateur grabbing some bricks from home depot and slapping a wall together. A wall is a wall. That's how the majority of managers view software development today. By the time that shoddy wall crumbles they'll be at another company anyway so it's someone else's problem.
When I talk about the software industry collapsing now, and in a few years we're mired with garbage software everywhere, this is why. These people in "leadership" are salivating at the idea of finally getting something for nothing. Paying a few interns to "vibe code" piles of software while they high five each other and laugh.
It will crash. The bubble will pop.
Developers: Keep your skills sharp and weather out the storm. In a few years you'll be in high demand once again. When those walls crumble, they will need people who what they're doing to repair it. Ask for fair compensation to do so.
Even if I'm wrong about all of this I'm keeping my skills sharp. You should too.
This isn't meant to be anti-management, but it's based on what I've seen. Thanks for coming to my TED talk.
* And to the original point, In my experience the tools interrupt the "flow" but don't necessarily take the joy out of it. I cannot do suggestion/autocomplete because it breaks my flow. I love having a chat window with AI nearby when I get stuck or want to generate some boilerplate.
IDK, there's still a place in society for master masons to work on 100+ year old buildings built by other master masons.
Same with the robots. They can implement solutions but I'm not sure I've heard of any inventing an algorithmic solution to a problem.
There's something great about old technology (though obviously one must be aware of survivorship bias when citing such technology), despite the fact that, logically speaking, new technology should have obviously been better.
Perhaps it's some variant of Jevons' paradox. The better / more efficient things get, the more of an impetus there is to use them in truly crappy ways. And this is how I'm starting to feel about programming with vs without an AI: you can either program manually to create truly creative, functional, elegant stuff, or use AI to produce garbage more efficiently. There just doesn't seem to be an in-between category, at least in terms of demand.
In case you haven't seen this video of a toaster from the 60s before, you're in for a treat: https://www.youtube.com/watch?v=1OfxlSG6q5Y
I'm also reminded of Edsger Dijkstra's quote on elegance: https://platosmirror.com/edsger-dijkstra-elegance-is-not-a-d...
also if you want to see the real cost (at least part of it) of AI coding or the whole fucked up IT industry, go to any mining town in the global south.
Dude's an engineering manager who codes maybe 5% of the time and his joy is decreasing. AI is not the problem, it's being an engineering manager.
But when that last 1% breaks and AI can’t fix it. That’s where you need the humans.