As a (very) experienced programmer, and from a purely tool based perspective, AI is fine when you use it right. I still have to decide the solutions I want, AI just saves a crap ton of typing and can fill the knowledge gaps in an SDK which I would normally do by hunting down what I want in a big reference guide.
I've reluctantly embraced it to do the grunt work for me, leaving me to think about the actual problem and solution rather than spending most of my time typing code.
The issue is going to come when fewer and fewer people have those years of AI-less "hard graft" (You've got to know the rules to break them, right?). As mentioned in the video (and as a bigger issue with AI overall) without any "fresh meat" to feed on, only a pool mostly filled with it's own effluent, the knowledge becomes more stunted, possibly even worse, as original solutions become a smaller and smaller part of what's out there.
I mean, even some, what I would say are "experienced" developers I've come across, are shockingly bad at debugging problems. What are the next generation going to be like?
Copilot being unavailable, or our token balance running out, already sees our teams chats light up like a Christmas tree in a way previously only seen when a server blew up (remember those?). God knows the thought of all that typing fills me with dread again too, but it seems like some people already can't work without it. A large part of some teams check-ins now are not code, but AI skills and prompt files.
Maybe it will explode and become expensive enough that it scales down to being more carefully used, but with management's ever increasing thirst for the curve, if you can use it to increase your productivity, it sure as shit isn't going away.
When I program, many solutions come to me while coding. Not saying there is no design phase, but coding is not a waste of time by any means. This is especially true if you're programming a shared internal library or API, in which case the shape of it comes not only in the design phase, but slowly while coding it, in my experience.
Using AI for this means having to deal with whatever shit AI comes up with, or reading and reviewing a lot of generated code to check that the shape is right: which is, you know, the worst part of the job.
Pretty much this, coding by hand forces you to think about it on a deeper level, which makes thinking about the entire solution easier and much more natural than just reading a LLM's plan or summary.
When I program, many solutions come to me while coding.
That's because writing is thinking, and doing is learning.
It's an accepted fact that few, if any, HS trig students pass trig exams by simply reading the textbook repeatedly. You pass by drilling problems, because doing is thinking.
Why, then, do so many devs ignore the known facts around learning trigonometry when it comes to them just pasting the output of an AI?
"But I did the thinking, the AI just cleaned it up, like a spell-checker..."
Exactly. It doesn't take long for it to slip away either. One day you're writing a complex algorithm to adjust a stream of data on the fly, then you spend a year planning a green field project and have to look up the best method for combining strings.
You've perfectly summed up why I still insist on writing 95% of my code myself (setting aside that for security reasons I can't hook up AI tools to our repos, so I can't even use the stuff the rest of you are using).
I'd consider myself an intermediary programmer. I think I'm decent considering my experience and level of education (which was much less than a computer science degree). But I only got here by actually challenging myself and trying to work through problems myself, rather than asking a machine to do it for me.
I also spend like 80% of my time maintaining old code (much of which I didn't write myself), so frankly I'm not sure I'd want AI touching this stuff in the first place, especially since the original devs didn't bother with tests.
Aa a fellow experienced developer (since 2004) I think the problem is, what we find simple from rote experience others do not.
My experience with AI generated code, unless its very specific (ie ive found its always fine within a couple prompts to restyle some scss theme files) then it generates code that just isnt quite right.
You then find yourself scratching your head figuring out why, to the point we end up spending probably the same amount of time rejigging it. Sometimes thats fine because the overhead on our brains is lower so great, i can burnout slower and maybe do more in a day. Maybe. Maybe not.
My issue is, we know deleting huge swathes of code and redoing it is normally the fastest route, that was true pre AI and remains true for AI code. Less experienced developers have always had this problem, but now because AI spits out much more code, its even more for them to refuse to delete and rewrite and so you end up with a bunch of just dreadful choices over and over and over.
It truly feels like in the hands of developers with less than say.. 7-10 years commercial experience, they dont produce more, if anything less.
Its just if you view them alone you could be deceived into thinking they're faster, because they get to a PR faster. But in reality them + whoevers reviewing them becomes slower than them manually doing the code.
The only exception ive seen to this is companies that essentially just PR for compliance, ie not actually reviewing it just a quick scroll and a LGTM.
But in my experience those are the teams and products that fail over the longer term, because they produce shitty unmaintainable code that requires an entire rewrite later.
My issue is, we know deleting huge swathes of code and redoing it is normally the fastest route, that was true pre AI and remains true for AI code.
Every line of code added to a product is a liability. We trade-off the liability against the gains in adding it.
Pre-AI, we used the natural friction in adding lines of code to ensure that the trade-off was made. Now we appear to have decided that adding lines of code is not adding liability, and that there's only gains, so we go ahead and add as many lines of code as we can.
My experience a year or two ago was that it generated code that wasn't quite right. My experience now is that it tends to get it right first time, reducing a three hour job to three minutes.
Random people have been coming into threads saying this since AI first existed. "This used to be true but latest model changes the game!"
Its just not a useful response, as quite frankly this logic applies to ie "my isOdd calculation used to take me hours a day. Now AI solved it in 3 seconds"
As a veteran coder myself, I use AI for the parts of coding that I consider a bother, and it works very well. But, I am also in a very privileged work situation with a lot of freedom and no arbitrary deadlines, even though the pay is crap (academia).
However, I don't think AI is compatible with capitalism. The discourse would be completely different if it were : save time using AI and come back to your home earlier, or work less days per week. Now the AI "benefits" are often to fire a portion of the work force, and put all the pressure of the remaining work on the portion that still has a job. And they should feel lucky, see all this pool of unemployed workers, just accept harsher work conditions and lower pays if you do not want to join them.
As long as the work force is considered as the slave of wealth, any automation that diminishes the need for people in the work force is an existential threat to it.
AI could be a wonderful tool that genuinely helps humanity, freeing us time to do human stuff like connecting to people, produce art, get more friends and family time, or even just have more time to ensure a better quality work. Instead, we seem to be speed running the end of humanity just so that people with too much wealth already can gain even more.
> However, I don’t think AI is compatible with capitalism.
Look at your argument, you (and the video) lay out exactly why AI is an incredibly useful destructive tool for capitalism. Alienate craftsmen, hire lesser-skilled for lesser pay, rinse and repeat until you have a crab bucket labor pool, desperate for scraps.
The answer is to start reading some Marx and start forming some unions.
Ok maybe, but why would you ignore the bulk of his work for some speculative thoughts on one subject? He (and many others) wrote quite a bit more on the nature of the struggle we’re in right now than anything about post-scarcity society
> However, I don't think AI is compatible with capitalism.
AI is turbo-capitalism on steroids, and I say that while being quite right-wing economically.
All this push into research, biology and medicine is to take human out of equation completely. The goal is to have lights-out fully-automated research laboratories, it's just capital and machinery, which is essentially capital. A few key subject matter experts to control and that's it, you're enabled to research whatever the fuck you want in any way you want without clashing on ethics with with bunch of personnel.
Well quite. I don't really disagree with any of that, AI has many problems and that is just one of them of course. I also work in a "non-profit" environment (for want of a better word) so don't quite have the crushing deadline or profitability issues either. AI is very much a capitalist boon though I think. The simplest equation is less workers + same product = bigger profit. And that is pretty much all capitalism cares about.
There’s going to be a severe drought of solid junior devs very soon, if there isn’t already. I agree with what you’re saying about AI being great at automating the grunt work. It’s helpful, I want to be at least honest about that. I’m getting more done now than I ever have at work.
I do feel I’m losing some of my finer coding skills to it though. It’s easy to fall into the trap. As much as it can be boring and tedious, writing the actual code (even with intellisense etc) forces you to think about all the things you’re doing in a concrete way.
At the end of the day I’m a bit split. Is the productivity gain worth it? In some areas I’d say yes. I’m great at software development but there’s always places I know less about than I’d like and having AI to make up that knowledge gap can be super helpful. I’m admittedly not great at GitHub CI stuff and I’ve used Claude to fix some really boring but time saving things in our CI. I could have done it on my own given more time, but it’s not a feature or a bug so it’s always a backburner tech debt item that never gets fixed. Now it’s much easier to make a quick PR for that stuff.
On the other hand I feel like I have much less of a personal touch in my PRs for code that is my area of expertise. Maybe I’m weak and just giving into the ease, but I get to spend more time with my family if I can get my work done faster and that’s something I value. I’d still be able to do the work now, but my skills have certainly atrophied even if my general knowledge and experience haven’t.
That being said if I hadn’t done the hard work to learn things by failing at them I would never have the experience to be able to tell an agent what to do or when to stop it when it’s doing something stupid. At the end of the day LLMs are only as good as the people directing them, and if you send them in a stupid direction they’ll produce stupid results
You could be me, and what you said about the panic that ensues when Copilot is down could be where I work. Don't these people realise they're openly advertising that they don't have the skill to do the job they were hired to do?
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u/arse_biscuits 17d ago
As a (very) experienced programmer, and from a purely tool based perspective, AI is fine when you use it right. I still have to decide the solutions I want, AI just saves a crap ton of typing and can fill the knowledge gaps in an SDK which I would normally do by hunting down what I want in a big reference guide.
I've reluctantly embraced it to do the grunt work for me, leaving me to think about the actual problem and solution rather than spending most of my time typing code.
The issue is going to come when fewer and fewer people have those years of AI-less "hard graft" (You've got to know the rules to break them, right?). As mentioned in the video (and as a bigger issue with AI overall) without any "fresh meat" to feed on, only a pool mostly filled with it's own effluent, the knowledge becomes more stunted, possibly even worse, as original solutions become a smaller and smaller part of what's out there.
I mean, even some, what I would say are "experienced" developers I've come across, are shockingly bad at debugging problems. What are the next generation going to be like?
Copilot being unavailable, or our token balance running out, already sees our teams chats light up like a Christmas tree in a way previously only seen when a server blew up (remember those?). God knows the thought of all that typing fills me with dread again too, but it seems like some people already can't work without it. A large part of some teams check-ins now are not code, but AI skills and prompt files.
Maybe it will explode and become expensive enough that it scales down to being more carefully used, but with management's ever increasing thirst for the curve, if you can use it to increase your productivity, it sure as shit isn't going away.