> Maybe I should consider transforming my woodworking hobby into a profession...
Whatever your feelings on the future of the industry are, it's hard to imagine you'll find more professional success in artisan woodworking than artisan software.
"Maybe I should consider transforming my woodworking hobby into a profession."
As an AI optimist, I think all forced labor should eventually be done by AI. People can then spend their time pursuing their own hobbies. Just as many people still play Go after AlphaGo appeared, because they genuinely love the game.
In the future, coding may return to being an art form. People will no longer focus on utility alone, but instead on the enjoyment of the process of writing code itself.
"Except that nobody cares anymore." Noone (from mid-management) cared about it also before. You hit the deadline, get promoted and leave the technical debt to the next one. Even if you're the one to deal with it, you set up the next project, get the budget, prioritize the issues etc. Not much changed in this regard with LLMs
The glory days are over. In the future, one software engineer will be able to support multiple product areas much like how one HR team can support 1,000's of employees.
LLMs have made domain knowledge and reasoning "cheap"; it doesn't matter if the output is lower quality - look around you for countless examples of where cheap wins and "cheap" continues to improve.
I secretly wish LLMs take my job away because I'll get about two years of unprogrammed rest, which I absolutely will not take of my own accord. But it's unlikely to happen.
To me looks like, if we're not collectively careful, civilisation will soon be on a path to an evolutionary dead-end.
Anything that can replace a deeply experienced s/ware engineer can replace anyone in the employment stack, meaning that only the owners of capital will be left, and they too will soon fade as the economy falls off a cliff and money has no value, because the only value that money has is the value of a human backing that, with thought, with ideas, with human output.
Whether you like it or not, "Economic output" is just a different phrase for "Human output that is valuable". When all human output is valued at the fractions of a penny per month of work, there is no future.
> The company is now hiring again for a few roles and domain familiarity is not a strong differentiator anymore. We used to list "Software Engineer - Area". Now it's just "Software Engineer" and the team assignment comes after the offer is accepted.
> Of course, this is good for brilliant engineers that never had the chance to get deep into the domain and now have better chances at getting a job, but it's also sad to think that other brilliant engineers that spent their lives collecting domain knowledge are now competing on the same lane.
If the author's vision of the future is correct, then competent software engineers are safe. Domain knowledge can be learnt much quicker than how to apply good engineering principles.
Engineers whose main competitive advantage is domain knowledge are probably not that brilliant at engineering. They might still find employment in other areas of the industry where they accumulated domain knowledge.
It's crazy the crazed anti-AI people yelling with foam with their mouth that it's useless, meanwhile Claude for me at work oneshots complex bugs in a massive project with a 95% success rate. And the customer happiness survey has never been as good as it's now btw
Wut? I pilot LLMs all day but there's no way in hell I'd agree to be at the helm of a finance product. That first pillar is still there. Maybe the author isn't aware of the impact they have, but I know, with the evidence of reverted PRs, that when I step outside my area of deep knowledge I can no longer call BS on the agents. Our most capable agent, with access to the same kind of distributed systems the author talks about, is regularly wrong, frequently myopic, and just outright dumb constantly. It's the expertise of engineers on the team that push it back on track.
An LLM agent will only be as good as the environment it operates in.
If you build your environment to be specification based, you have to make sure you have good specifications. If your "memory solution" uses freeform markdown notes, you already lost from the start.
Also choose languages with good unit testing built-in, and languages with unified code styles, and unified toolchains. If you use C++, assume that there's a million ways to build your algorithm. If you use JS, assume 10 different build pipelines. If you use java, assume bloat by dependency hell.
LLMs mimic the ecosystem's variety and variadicity(?). Languages like Go shine so well because it's a very opinionated language, where there's only one proposed way on how to implement things. And that's a good harness to begin with. LLMs are like children on the playground. You have to build better rulesets and fences to make them behave how you expect them to.
Also, check out qwen3.6 coder and heretic models. 30b is the sweet spot for coding and unit testing. For planning and designing, gemma4 is pretty good.
The direction I'm given is to take humans out of the loop. As much as possible. Everything AI. Automate everything. If you are in the loop you are overhead.
I am also feeling anxious. I lucked out by having natural inclination towards software development, career which can provide good upper middle class life to anyone. But I feel like writing is on the wall. If I don’t find a way to pivot to something else, I might experience class migration, but in the opposite direction this time.
Same boat here, just a couple years more experience.
Current LLMs are still kind of shit at actually programming so many jobs do still care to have professional programmers. However, I think it's evident that if things stand where they are, employers will care to have far fewer of them, at least of highly paid highly experienced programmers. If this is the state we're in with LLM adoption when they can't help but create the same helper functions 15 times, god knows we're screwed.
So we should probably work on clearing out our debts and figuring out what else we might want to do with our time, I reckon.
I'm still going to try to do a good job. I'm still trying to learn the best effective ways to apply current LLMs (Right now I still prefer to mostly write code myself but have been using LLMs to bang code into shape via iterative code review; this is a way to exploit LLMs to make better code, especially applicable if your velocity was already good.)
He says that taste doesn't matter and it hasn't in the past. However, in an era of "extruded code product" (by analogy to https://tvtropes.org/pmwiki/pmwiki.php/Main/ExtrudedBookProd... ) automatically generated by the truckload at negligible cost, the differentiator for software developers will necessarily be the ability to create a product that doesn't reek of extruded code product, i.e. the things like quality that he labels taste.
(Whether any one reading this, myself included, survives in the industry long enough to reach the other side of that transition is a different question.)
[EDIT] The reason I use books as an example is that 4.2 million books were published in 2025 (https://ideas.bkconnection.com/10-awful-truths-about-publish...); 3.5m self published (with most likely LLM assisted or wholly generated) and the remainder traditionally published. (That's ~9,600 new self-published books a day.) Who actually still sells enough copies to make money in this paradigm and why offers hints as to where the software industry is likely headed.
This anonymous article is likely more FUD from the AI industry. "Just give up,you can't beat the machine. Please go quietly, we want to take your place and it's easier for everybody if you don't resist because you believe it's pointless"
Code quality and architecture still matter, because they also make it easier for LLMs to reason about the system.
That said, Opus 4.8 and Codex 5.5 both can write code that is higher quality than your average engineer. They are not quite there yet in terms of code re-use, but I think that's a solvable problem.
I sympathise with the author being in the same boat, largely.
I just want to emphasise a point... Calculators give 100% correct answers and yet we still hire accountants; for the simple fact that we don't want all to be accountants.
People will hire software engineers for the simple fact that they do not want to be software engineers.
Realistically, what should we have done instead? Not invent LLMs? What happens when a couple thousand people invent the next disruptive technology and even more of the population loses their jobs?
It seems like new tech is something most of us have to lie down and accept as the new reality each time it's invented, barring full-scale rioting. Much as with the Cold War.
There’s one force where software engineering is being automated by LLMs, but the other force is that there isn’t really much more software that needs to be built. Even before AI coding became big, back in 2021, we were already in late stage SaaS territory where each new idea was an increasingly minor variation of an existing idea. There were no new GitHubs, Herokus, Stripes, Salesforces, Instagrams, Reddits, just variations of those for more specialized markets.
It’s really unfortunate that AI hasn’t raised the ceiling on the space of possibilities as much as it’s raised the floor on how much can be automated, we’re all getting squeezed in the space between.
I don't know, I can think of lots of new ideas that haven't been executed yet. I think there's always more to explore. It's also a bit of creativity and out-of-the-box thinking
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[ 5.4 ms ] story [ 134 ms ] thread:-(
I have little to add to it, except that I agree completely. Not sure what’s next
Whatever your feelings on the future of the industry are, it's hard to imagine you'll find more professional success in artisan woodworking than artisan software.
We will work for the robots, steering them to steer us.
"Maybe I should consider transforming my woodworking hobby into a profession."
As an AI optimist, I think all forced labor should eventually be done by AI. People can then spend their time pursuing their own hobbies. Just as many people still play Go after AlphaGo appeared, because they genuinely love the game.
In the future, coding may return to being an art form. People will no longer focus on utility alone, but instead on the enjoyment of the process of writing code itself.
LLMs have made domain knowledge and reasoning "cheap"; it doesn't matter if the output is lower quality - look around you for countless examples of where cheap wins and "cheap" continues to improve.
Good luck out there; we will all need it.
Anything that can replace a deeply experienced s/ware engineer can replace anyone in the employment stack, meaning that only the owners of capital will be left, and they too will soon fade as the economy falls off a cliff and money has no value, because the only value that money has is the value of a human backing that, with thought, with ideas, with human output.
Whether you like it or not, "Economic output" is just a different phrase for "Human output that is valuable". When all human output is valued at the fractions of a penny per month of work, there is no future.
> Of course, this is good for brilliant engineers that never had the chance to get deep into the domain and now have better chances at getting a job, but it's also sad to think that other brilliant engineers that spent their lives collecting domain knowledge are now competing on the same lane.
If the author's vision of the future is correct, then competent software engineers are safe. Domain knowledge can be learnt much quicker than how to apply good engineering principles.
Engineers whose main competitive advantage is domain knowledge are probably not that brilliant at engineering. They might still find employment in other areas of the industry where they accumulated domain knowledge.
It's crazy the crazed anti-AI people yelling with foam with their mouth that it's useless, meanwhile Claude for me at work oneshots complex bugs in a massive project with a 95% success rate. And the customer happiness survey has never been as good as it's now btw
If you build your environment to be specification based, you have to make sure you have good specifications. If your "memory solution" uses freeform markdown notes, you already lost from the start.
Also choose languages with good unit testing built-in, and languages with unified code styles, and unified toolchains. If you use C++, assume that there's a million ways to build your algorithm. If you use JS, assume 10 different build pipelines. If you use java, assume bloat by dependency hell.
LLMs mimic the ecosystem's variety and variadicity(?). Languages like Go shine so well because it's a very opinionated language, where there's only one proposed way on how to implement things. And that's a good harness to begin with. LLMs are like children on the playground. You have to build better rulesets and fences to make them behave how you expect them to.
Also, check out qwen3.6 coder and heretic models. 30b is the sweet spot for coding and unit testing. For planning and designing, gemma4 is pretty good.
it only matters what upper management think, and its clear that more and more companies value "good enough" and reducing costs over "good"
Current LLMs are still kind of shit at actually programming so many jobs do still care to have professional programmers. However, I think it's evident that if things stand where they are, employers will care to have far fewer of them, at least of highly paid highly experienced programmers. If this is the state we're in with LLM adoption when they can't help but create the same helper functions 15 times, god knows we're screwed.
So we should probably work on clearing out our debts and figuring out what else we might want to do with our time, I reckon.
I'm still going to try to do a good job. I'm still trying to learn the best effective ways to apply current LLMs (Right now I still prefer to mostly write code myself but have been using LLMs to bang code into shape via iterative code review; this is a way to exploit LLMs to make better code, especially applicable if your velocity was already good.)
(Whether any one reading this, myself included, survives in the industry long enough to reach the other side of that transition is a different question.)
[EDIT] The reason I use books as an example is that 4.2 million books were published in 2025 (https://ideas.bkconnection.com/10-awful-truths-about-publish...); 3.5m self published (with most likely LLM assisted or wholly generated) and the remainder traditionally published. (That's ~9,600 new self-published books a day.) Who actually still sells enough copies to make money in this paradigm and why offers hints as to where the software industry is likely headed.
'Maybe I should consider woodworking' - Fuck off.
That said, Opus 4.8 and Codex 5.5 both can write code that is higher quality than your average engineer. They are not quite there yet in terms of code re-use, but I think that's a solvable problem.
I just want to emphasise a point... Calculators give 100% correct answers and yet we still hire accountants; for the simple fact that we don't want all to be accountants.
People will hire software engineers for the simple fact that they do not want to be software engineers.
It seems like new tech is something most of us have to lie down and accept as the new reality each time it's invented, barring full-scale rioting. Much as with the Cold War.
It’s really unfortunate that AI hasn’t raised the ceiling on the space of possibilities as much as it’s raised the floor on how much can be automated, we’re all getting squeezed in the space between.
I’m not planning on firing people, but I am planning on building more, using more tokens, and less app subscriptions.
One aspect of building that doesn’t erode is human values.
LLMs don’t create software with zero direction and although I do have 12 agents building constantly, I run out of attention to increase that to 100.