Coding was incredibly fun until working in capitalist companies got involved. It was then still fairy fun, but tinged by some amount of "the company is just trying to make money, it doesn't care that the pricing sucks and it's inefficient, it's more profitable to make mediocre software with more features than really nail and polish any one part"
Adding on AI impacts how fun coding is for me exactly how they say, and that compounds with company's misaligned incentives.
... I do sometimes think maybe I'm just burned out though, and I'm looking for ways to rationalize it, rather than doing the healthy thing and quitting my job to join a cult-like anti-technology commune.
For me I’m vaguely but persistently thinking about a career change, wondering if I can find something of more tangible “real world” value. An essential basis of which being the question of whether any given tech job just doesn’t hold much apparent “real world value”.
AI is just one of those arms races that we imposed on ourselves, with desire to dominate others, or to protect ourselves from such domination. It is irreversible, just like the other things. It survives by using the same tactic of a cheap salesman - tell the first buyer that they can dominate the world, and then tell next buyers that they need to protect themselves from the first one.
We transformed our lifestyles to live with those unnecessary, business/politics driven "advancements". The saga continues.
BTW, electronic calculators, when they came up, did a similar thing, erasing the fun out of calculations by hand.
What's beautiful is complexity, what's ugly is the destruction of complexity. That's why we find the destruction of forests to be repellent. Because we appreciate the more complex over the less complex. Possibly because complexity is the universe's way of observing itself. None of that means that our own complexity is necessarily wicked or irrelevant. It may just be a natural stage in the evolution of a planet. Grassland had 3 billion years to change, and it largely stayed the same. What's a couple thousand years of us blowing shit up, really?
I'd argue you didn't lose the joy of coding, you lost the illusion that coding made you real, that it made you you.
It is never everything, but it should also never be nothing.
What plagues me about LLMs is that all that generated code is still around in the project making reviews harder as well s understanding the whole program source. What is in there that makes you prefer this mechanism instead of the abstractions that have been increasingly available since forever?
The compiler produces a metric shit ton of code that I don't see when I'm writing C++ code. And don't get me started on TypeScript/Clojure - the amount of code that gets written underneath is mindbogglingly staggering, yet I don't see it, for me the code is "clean".
And I'm old enough to remember the tail end of the MachineCode -> CompiledCode transition, and have certainly lived through CompiledCode -> InterpretedCode -> TranspiledCode ones.
There were certainly people who knew the ins and outs of the underlying technology who produced some stunningly fast and beautiful code, but the march of progress was inevitable and they were gradually driven to obscurity.
This recent LLM step just feels like more of the same. *I* know how to write an optimized routine that the LLM will stumble to do cleanly, but back in the day lots of assembler wizards were doing some crazy stuff, stuff that I admired but didn't have the time to replicate.
I imagine in the next 10-20 years we will have Devs that _only_ know English, are trained in classical logic and have flame wars about what code exactly would their tools generate given various sentence invocations. And people would benchmark and investigate the way we currently do about JIT compilation and CPU caching - very few know how it actually works but the rest don't have to, as long as the machine produces the results we want.
Just one more step on the abstraction ladder.
The "Mars" trilogy by Kim Stanley Robinson had very cool extrapolations where this all could lead, technologically, politically, social and morally. LLMs didn't exists when he was writing it, but he predicted it anyway.
What I worry about is that my list has gotten shorter not because everything is as it should be but because I have slowed down.
Quite a lot of things on that list were of the "The future is here but it's not evenly distributed" sort. XP was about a bunch of relatively simple actions that were force multipliers with a small multiple on them. What was important was that they composed. So the benefit of doing eight of them was more than twice the benefit of doing four. Which means there's a lot of headroom still from adding a few more things.
If AI is writing all the code, how do we keep the quality good? It's so obvious with the current GenAI tools that they're getting great at producing code, but they don't really understand the code.
We don't really know how this story unfolds, so it's good to keep a positive mindset.
Maybe I was lucky. For me, the joy was the power of coding. Granted, I'm not employed as a coder. I'm a scientist, and I use coding as a problem solving tool. Nothing I write goes directly into production.
What's gone is the feeling that coding is a special elite skill.
With that said, I still admire and respect the real software developers, because good software is more than code.
I experimented with GPT-5 recently and found its capabilities to be significantly inferior to that of a human, at least when it came to coding.
I was trying to give it an optimal environment, so I set it to work on a small JavaScript/HTML web application, and I divided the task into small steps, as I'd heard it did best under those circumstances.
I was impressed overall by how far the technology has come, but it produced a number of elementary errors, such as putting JavaScript outside the script tags. As the code grew, there was also no sense that it had a good idea of how to structure the codebase, even when I suggested it analyze and refactor.
So unless there are far more capable models out there, we're not at the stage where generative AI can match a human.
In general I find current model to have broad but shallow thinking. They can draw on many sources, which is extremely useful, but seem to have problems reasoning things through in depth.
All this is to say that I don't find the joy of coding to have gone at all. In fact, there's been a number of really thorny problems I've had to deal with recently that I'd love to have side-stepped, but due to the currently limitations of LLMs I had to solve them the old-fashioned way.
GPT-5 what? The GPT-5 models range from goofily stupid to brilliant. If you let it select the model automatically, which is the case by default, it will tend to lean towards the former.
I also briefly tried out some of the other paid-for models, but mostly worked with GPT-5.
The models are one part of the story. But the software around it matters at least as much: what tools does the model have access to, like bash or just file reading or (as in your example!) just a cache of files visited by the IDE (!). How does the software decide what extra context to provide to the model, how does it record past learnings from conversations and failed test runs (if at all!) and how are those fed in. And of course, what are the system prompts.
None of this is about the model; its all "plain old" software, and is the stuff around the model. Increasingly, that's where the quality differences lie.
I am sorry to say but Copilot is just sort of shoddy in this regard. I like Claude, some people like Codex, there are a bunch of options.
But my main point is - its probably not about the model, but about the products built on the models, which can vary wildly in quality.
The technology is progressing very fast, and that includes both the models and the tooling around it.
For example, Gemini 2.5 was considered a great model for coding when it launched. Now it is far inferior to Codex and Claude code.
The Githib Copilot tooling is (currently) mediocre. It's ok as a better autocomplete but can't really compete with Codex or Claude or even Jules (Gemini) when using it as an agent.
I think we should step back and ask: do we really want that? What does that imply? Until recently nobody would use a tool and think, yuck, that was inferior of a human.
I find the LLMs struggle constantly with languages there is little documentation or out of date. RAG, LoRA and multiple agents help, but they have their own issues as well.
This is a particular sweetspot for LLMs at the moment. I'll regularly one-shot entire NextJS codebases with custom styling in both Codex and Claude.
But it turns out the OP is using Copilot. That just isn't competitive anymore.
Still an infinite amount to learn and do. It's still not hard to have more skill than an AI. Of course AI can solve all the dumbbell problems you get in school. They're just there to build muscle. Robots can lift weights better than you, too, but that doesn't mean there's no value in you doing it.
If you find coding boring, explore the frontiers. You will find a lot of coding wilderness where no AI has trod.
this, AI is nothing without data set
so if you working in bleeding edge technology where your tools is only have 3 contributor and a way to access them via IRC channel once a day, things get interesting
This assumes that companies care about "code quality" and customers care about bugs.
> If you find coding boring, explore the frontiers. You will find a lot of coding wilderness where no AI has trod.
There are a lot of software engineers and not a lot of frontier.
In each of these cases, lots of relatively low-value jobs were no longer needed and a few very-high-value jobs sprang into existence.
The author of the article loves coding. But software is about solving problems efficiently, not punching the keyboard. The other parts of the job might not be as fun for everyone, but they are even more valuable than typing code. Great programmers could always do both. Now they can focus on the higher value work more by leveraging tools that can do the lower-value work.
Work is not supposed to be fun. That’s why they pay you to do it. If it was fun, you would have to pay your employer. (Tongue in cheek advice).
They still need someone with higher reasoning skills (eg humans) to verify what they cough up. This need is likely to continue for quite some time (since LLMs simply aren't capable of higher reasoning).
Learning to code effectively using LLMs is probably the best path forward, from a career standpoint.
Sadly, there's very little I can do now. I don't have the financial means to meaningfully change careers now. Pretty much the only thing I could do now that pays somewhat well and doesn't require me to go to university again is teaching. I think I will ride this one out and end it when it ends.
Of course in reality there’s weird economical mechanics where making the most money and building something that benefits the world don’t necessarily collide, but theres always demand for and joy in solving complex problems, even if its on a higher abstraction level than coding with your favorite language.
1) you are using coding assistant too much - you aren't yet ready for the Senior role that requires. Advice: chill out with that and get back to coding solo
or
2) you haven't used coding assistant enough to realize it's an idiot savant grade Junior to Mid programmer. Advice: use coding assistant more and then see #1
Real talk: all moments suck and all moments are wonderful. Source: have lived through few computer moments.
What a time to be alive!
There was a time when you could walk in the door with a handful of proper nouns printed on a piece of paper. The low hanging fruit has all been collected by now. But, there is always fruit available higher up in the tree. It's just harder to get to. Most people don't know how to climb the tree. They say they can, or that they do it all the time, but they're usually full of shit. It takes a lot of practice and discipline to do this safely.
To be clear, the tree is the customer in this analogy. Your tech and tools are only useful in so far as they complete a valuable job for some party. Reselling value-added tools to other craftsmen is also a viable path, but you have to recognize that the most wizened operators tend to use the older and more boring options. Something that looks incredibly clever to a developer with 3 years of experience is often instantly disregarded by someone with 4 years of experience. The rate at which you stop being a noob is ideally exponential.
I often look back on the things I thought were absolutely mandatory from a technology standpoint and feel really silly about much of it. I wish there was a better way to ramp developers without them causing total destruction. Right now it's like we're training electrician apprentices by having them work on HV switch gear at a nuclear power plant.
There is still a huge gap in ideas like apprenticeship in technology. Being able to code is such a tiny piece of the pie. Being able to engage in dialog with the non technical business owners such that your code has effect on target is ~ the rest of the pizza. A laser guided munition delivered from 60k feet will not be very useful if you don't know where it needs to go or how many targets there are. A lot of what I see on the HN front page is tantamount to carpet bombing the jungle non-stop in hopes of jostling an apple out of a tree somewhere.
That being said, we untalented programmers are experiencing what most jobs suffered in the last 2 centuries: massive automation of their everyday activities. I especially identify with these traditional farmers who took their life as their way of life was wiped out by artificial fertilizers, mechanic, chemicals and hyperscaling.
Ericson2314•2h ago
Good things to look forward to are:
- Lean and mathlib revolutionizing math
- Typst replacing latex and maybe some adobe prosuc
- Fuschia/Redox/wasi replacing Unix
- non-professional-programmers finally learning programming en mass
I think the latter is maybe the most profound. Tech may not grow at a break-neck pace, but erasing the programmer vs computer illiterate dichotomy will mean software can way the world in much less Kafkaesque ways.
Pamar•2h ago
I've met lots of "digital natives" and they seem to use technology as a black box and click/touch stuff at random until it sorta works but they do not very good at creating at mental model of why something is behaving in a way which is not what was expected and verify their own hypothesis (i.e. "debugging").
maegul•2h ago
And more so with AI software/tools, and IMO frighteningly so.
I don’t know where the open models people are up to, but as a response to this I’d wager they’ll end up playing the Linux desktop game all over again.
All of which strikes at one of the essential AI questions for me: do you want humans to understand the world we live in or not?
Doesn’t have to be individually, as groups of people can be good at understanding something beyond an individual. But a productivity gain isn’t on it’s a sufficient response to this question.
Interestingly, it really wasn’t long ago that “understanding the full computing stack” was a topic around here (IIRC).
It’d be interesting to see if some “based” “vinyl player programming” movement evolved in response to AI in which using and developing tech stacks designed to be comprehensively comprehensible is the core motivation. I’d be down.
righthand•2h ago
I don’t think this is what you think it is. It’s more like non-professional-programmers hacking together all the applications they wanted to hack together before. The Llm is just the glue.
IMO, they are NOT learning programming.
MiiMe19•1h ago
safety1st•2h ago
In the last few years we've seen first Valve with SteamOS, and now 37signals with Omarchy, release Linux distros which are absolutely great for their target audience and function as a general purpose operating system just fine. Once might just be a fluke... Twice is a pattern starting to emerge.
Are we witnessing the beginning of a new operating system ecosystem where you only have to be a billion dollar company to produce a viable operating system instead of a trillion dollar one?
How many of our assumptions about computing are based on the fact that for 30+ years, only Microsoft, Apple and Google got to do a consumer OS?
And a preponderance of the little components that make up this "new" OS ecosystem were developed by some of the most radical software freedom fighters we've got.
Is this a long shot I'm thinking about, you bet. But the last time I was this excited about the future I was a teenager and most homes still didn't have a PC.
trenchpilgrim•1h ago