The title is doing a lot of work here. What resonated with me is the shift from “writing code” to “steering systems” rather than the hype framing. Senior devs already spend more time constraining, reviewing, and shaping outcomes than typing syntax. AI just makes that explicit. The real skill gap isn’t prompt cleverness, it’s knowing when the agent is confidently wrong and how to fence it in with tests, architecture, and invariants. That part doesn’t scale magically.
I think there are two groups of people emerging. deep / fast / craft-and-decomposition-loving vs black box / outcome-only.
I've seen people unable to work at average speed on small features suddenly reach above average output through a llm cli and I could sense the pride in them. Which is at odds with my experience of work.. I love to dig down, know a lot, model and find abstractions on my own. There a llm will 1) not understand how my brain work 2) produce something workable but that requires me to stretch mentally.. and most of the time I leave numb. In the last month I've seen many people expressing similar views.
That's kind of the point here. Once a dev reached a certain level, they often weren't doing much "relaxing code typing" anyways before the AI movement. I don't find it to be much different than being a tech lead, architect, or similar role.
Ya know, I have to admit feeling something like this. Normally, the amount of stuff I put together in a work day offers a sense of completion or even a bit of a dopamine bump because of a "job well done". With this recent work I've been doing, it's instead felt like I've been spending a multiplier more energy communicating intent instead of doing the work myself; that communication seems to be making me more tired than the work itself. Similar?
You’re possibly not entering into the flow state anymore.
Flow is effortless. and it is rejuvenating.
I believe:
While communication can be satisfying, it’s not as rejuvenating as resting in our own Being and simply allowing the action to unfold without mental contraction.
Flow states.
When the right level of challenge and capability align and you become intimate with the problem. The boundaries of me and the problem dissolve and creativity springs forth. Emerging satisfied. Nourished.
Nah, I don’t miss at all typing all the tests, CLIs, and APIs I’ve created hundreds of times before. I dunno if I it’s because I do ML stuff, but it’s almost all “think a lot about something, do some math, and and then type thousands of lines of the same stuff around the interesting work.”
It's difficult to steer complex systems correctly, because no one has a complete picture of the end goal at the outset. That's why waterfall fails. Writing code agentically means you have to go out of your way to think deeply about what you're building, because it won't be forced on you by the act of writing code. If your requirements are complex, they might actually be a hindrance because you're going have to learn those lessons from failed iterations instead of avoiding them preemptively.
The stereotype that writing code is for junior developers needs to die. Some devs are hired with lofty titles specifically for their programming aptitude and esoteric systems knowlege, not to play implementation telephone with inexperienced devs.
This is pretty recent - the survey they ran (99 respondents) was August 18 to September 23 2025 and the field observations (watching developers for 45 minute then a 30 minute interview, 13 participants) were August 1 to October 3.
The models were mostly GPT-5 and Claude Sonnet 4. The study was too early to catch the 5.x Codex or Claude 4.5 models (bar one mention of Sonnet 4.5.)
This is notable because a lot of academic papers take 6-12 months to come out, by which time the LLM space has often moved on by an entire model generation.
Depends on the participants. If they're cutting-edge LLM users then yes, I think so. If they continue to use LLMs like they would have back in the first half of 2025 I'm not sure if a difference would be noticeable.
I'm not remotely cutting edge (just switched from Cursor to Codex CLI, have no fancy tooling infrastructure, am not even vaguely considering git worktrees as a means of working), but Opus 4.5 and 5.2 Codex are both so clearly more competent than previous models that I've started just telling them to do high-level things rather than trying to break things down and give them subtasks.
If people are really set in their ways, maybe they won't try anything beyond what old models can do, and won't notice a difference, but who's had time to get set in their ways with this stuff?
we've never seen a profession drive themselves so aggressively to irrelevance. software engineering will always exist, but it's amazing the pace to which pressure against the profession is rising. 2026 will be a very happy new year indeed for those paying the salaries. :)
We've been giving our work away to each other for free as open source to help improve each other's productivity for 30+ years now and that's only made our profession more valuable.
I see little proof open source has resulted in higher wages and not the fact that everything is being digitized and the subsequent demand for such people to assist in such.
I'm not sure how I can prove it, but ~25 years ago building software without open source sucked. You had to build everything from scratch! It took months to get even the most basic things up and running.
I think open source is the single most important productivity boost to our industry that's ever existed. Automated testing is a close second.
Google, Facebook, many others would not have existed without open source to build on.
And those giants and others like them that were enabled by open source employed a TON of people, at competitive rates that greatly increased our salaries.
Indeed it did; I remember those times. All else being equal I still think SWE salaries on average would of been higher if we kept it like that given basic economics - there would of been a lot less people capable of doing it but the high ROI automation opportunities would of still been there. The fact that "it sucked" usually creates more scarcity on the supply side; which all being equal means higher wages and in our capitalist society - status. Other professions that are older as to the parent comment already know this and don't see SWE as very "street smart" disrupting themselves. I've seen articles recently like "at least we aren't in coding" from law, accounting, etc an an anecdote to this.
With AI at least locally I'm seeing the opposite now - less hiring, less wage pressure and in social circles a lot less status when I mention I'm a SWE (almost sympathy for my lot vs respect only 5 years ago). While I don't care for the status aspect, although I do care for my ability to earn money, some do.
At least locally inflation adjusted in my city SWE wages bought more and were higher in general compared to others in the 90's-2000's than on wards (ex big tech). Partly because this difficulty and low level knowledge meant only very skilled people could participate.
I don't think that's certain. I'm hoping for a Jevons paradox situation where AI drives down the cost of producing software to the point that companies that previously weren't in the market for custom software start hiring software engineers. I think we could see demand go up.
Also it really baffles me how many are actually in on the hype train. Its a lot more than the crypto bros back in the day. Good thing AI still cant reason and innovate stuff. Also leaking credentials is a felony in my country so I also wont ever attach it to my codebases.
I think the issue is folks talk past each other. People who find coding agents useful or enjoyable are labeled “on the hype train” and folks for which coding agents don’t work for them or their workflow are considered luddites. There are an incredible number of contradicting claims and predictions out there as well, and I believe what we see is folks projecting their reaction to some amalgamation of them onto others. I see a lot of “they” language, and a lot of viral articles about business leadership “shoving AI down our throats” and it becomes a divisive issue like American political scene with really no one having a real conversation
I think the reason for the varying claims and predictions is because developers have wildly different standards for what constitutes working code. For the developers with a lower threshold, AI is like crack to them because gen ai's output is similar to what they would produce, and it really is a 10x speedup. For others, especially those who have to fix and maintain that code, it's more like a 10x slowdown.
Hence why you have in the same thread, some developer who claims that Claude writes 99% of their code and another developer who finds it totally useless. And of course others who are somewhere in the middle.
There's also the effect of different models. Until the most recent models, especially for concise algorithms, I felt it was still easier to sometimes do it myself (i.e. a good algo can be concise/more concise than a lossy prompt) and leave the "expansion/repetitive" boilerplate code to the LLM. At least for me the latest models do feel like a "step change" in that the problems can be bigger and/or require less supervision on each problem depending on the tradeoff you want.
Its all a hype train though. People still believe in the AI gonna bring utopia bullshit while the current infra is being built on debt. The only reason it still exists is that all these AI companies believe in some kind of revenue outside of subscriptions. So its all about:
Owning the infrastructure and enshittify (ads) once enough products are based on AI.
.env files are used to develop as well, for some things like PayPal u dont have to change the credentials, you just enable sandbox mode. If I had some LLM attached to my codebase, it would be able to read those credentials from the .env file.
This has nothing to do with deployment. I never talked about deployment.
You know what. After seeing all these articles about AI/LLM for these past 4 years, about how they are going to replace me as software developers and about how I am not productive enough without using 5 agents and being a project manager.
I. Don't. Care.
I don't even care about those debates outside. Debates about do LLM work and replace programmers? Say they do, ok so what?
I simply have too much fun programming. I am just a mere fullstack business line programmer, generic random replaceable dude, you can find me dime a dozen.
I do use LLM as Stack Overflow/docs replacement, but I always code by hand all my code.
If you want to replace me, replace me. I'll go to companies that need me. If there are no companies that need my skill, fine, then I'll just do this as a hobby, and probably flip burgers outside to make a living.
I don't care about your LLM, I don't care about your agent, I probably don't even care about the job prospects for that matter if I have to be forced to use tools that I don't like and to use workflows I don't like. You can go ahead find others who are willing to do it for you.
As for me, I simply have too much fun programming. Now if you excuse me, I need to go have fun.
I simply will not spend my life begging and coaxing a machine to output working code. If that is what becomes of this profession, I will just do something else :)
Until you realize you're just begging and coaxing a human to better beg and coax a machine to output working code - when you could just beg and coax the machine yourself.
It would definitely be the profession if we stopped developing things today. Think about the idea of coding agents 2 years ago, I personally found them very unrealistic and am now coding exclusively with them despite them being either a neutral or net negative to my development time simply because I see the writing on the wall that in 6 mos to a year they will probably be a huge net positive and in 2-3 years the dismissive attitude towards adoption will start to look kind of silly (no offense). To me we are _just_ at the inflection point where using and not using coding agents are both totally sensible decisions.
Hear hear. I didn't spend half my life getting an education, competing in the corporate crab bucket, retraining and upskilling just to turn into a robot babysitter.
Why? It is a matter of values. Fun can be a driving force just like money and stability is. It is simply a matter of your values (and your sacrifices).
Like I said, I am just a generic replaceable dime a dozen programmer dude.
That’s not how LLMs work, it’s part of the reinforcement learning or SFT dataset, data labelers would have written or generated tons of examples using this and other patterns (all the emoji READMEs for example) that the models emulate. The early ones had very formulaic essay style outputs that always ended with “in conclusion”, lots of the same kind of bullet lists, and a love of adjectives and delving, all of which were intentionally trained in. It’s more subtle now but it’s still there.
Maybe I was being imprecise, but I’m not sure what you mean by “not how LLMs work” - discovering patterns of how humans write is exactly the signal they are trained against. Either explicitly curated like SFT or coaxed out during RLHF, no?
It could even have been picked up in pretraining and then rewarded during rlhf when the output domain was being refined; I haven’t used enough LLMs before post training to know what step it usually becomes noticeable.
Idk, I still mostly avoid using it and if I do, I just copy and paste shit into the Claude web version. I wont ever manage agents as that sounds just as complicated as coding shit myself.
It's not complicated at all. You don't "manage agents". You just type your prompt into an terminal application that can update files, read your docs and run your tests.
As with every new tech there's a hell of a lot of noise (plugins, skills, hooks, MCP, LSP - to quote Kaparthy) but most of it can just be disregarded. No one is "behind" - it's all very easy to use.
I've seen people unable to work at average speed on small features suddenly reach above average output through a llm cli and I could sense the pride in them. Which is at odds with my experience of work.. I love to dig down, know a lot, model and find abstractions on my own. There a llm will 1) not understand how my brain work 2) produce something workable but that requires me to stretch mentally.. and most of the time I leave numb. In the last month I've seen many people expressing similar views.
Flow is effortless. and it is rejuvenating.
I believe:
While communication can be satisfying, it’s not as rejuvenating as resting in our own Being and simply allowing the action to unfold without mental contraction.
Flow states.
When the right level of challenge and capability align and you become intimate with the problem. The boundaries of me and the problem dissolve and creativity springs forth. Emerging satisfied. Nourished.
But it does feel less fulfilling I suppose.
The models were mostly GPT-5 and Claude Sonnet 4. The study was too early to catch the 5.x Codex or Claude 4.5 models (bar one mention of Sonnet 4.5.)
This is notable because a lot of academic papers take 6-12 months to come out, by which time the LLM space has often moved on by an entire model generation.
Off your intuition, do you think the same study with Codex 5.2 and Opus 4.5 would see even better results?
If people are really set in their ways, maybe they won't try anything beyond what old models can do, and won't notice a difference, but who's had time to get set in their ways with this stuff?
It takes about 6 months to figure out how to get LaTeX to position figures where you want them, and then another 6 months to fight with reviewers
> Number of Survey Respondents
> Building apps 53
> Testing 1
I think this sums up everybody complaints about AI generated code. Don't ask me to be the one to review work you didn't even check.
I think open source is the single most important productivity boost to our industry that's ever existed. Automated testing is a close second.
Google, Facebook, many others would not have existed without open source to build on.
And those giants and others like them that were enabled by open source employed a TON of people, at competitive rates that greatly increased our salaries.
With AI at least locally I'm seeing the opposite now - less hiring, less wage pressure and in social circles a lot less status when I mention I'm a SWE (almost sympathy for my lot vs respect only 5 years ago). While I don't care for the status aspect, although I do care for my ability to earn money, some do.
At least locally inflation adjusted in my city SWE wages bought more and were higher in general compared to others in the 90's-2000's than on wards (ex big tech). Partly because this difficulty and low level knowledge meant only very skilled people could participate.
Hence why you have in the same thread, some developer who claims that Claude writes 99% of their code and another developer who finds it totally useless. And of course others who are somewhere in the middle.
Owning the infrastructure and enshittify (ads) once enough products are based on AI.
Its the same chokehold Amazon has on its Vendors.
This has nothing to do with deployment. I never talked about deployment.
I. Don't. Care.
I don't even care about those debates outside. Debates about do LLM work and replace programmers? Say they do, ok so what?
I simply have too much fun programming. I am just a mere fullstack business line programmer, generic random replaceable dude, you can find me dime a dozen.
I do use LLM as Stack Overflow/docs replacement, but I always code by hand all my code.
If you want to replace me, replace me. I'll go to companies that need me. If there are no companies that need my skill, fine, then I'll just do this as a hobby, and probably flip burgers outside to make a living.
I don't care about your LLM, I don't care about your agent, I probably don't even care about the job prospects for that matter if I have to be forced to use tools that I don't like and to use workflows I don't like. You can go ahead find others who are willing to do it for you.
As for me, I simply have too much fun programming. Now if you excuse me, I need to go have fun.
I'd at least be more likely to get a boost in impact and ability to affect decision making, maybe.
or something like that
Like I said, I am just a generic replaceable dime a dozen programmer dude.
a job isn't supposed to be fun its nice when it is but it shouldn't be what drives decisions
I meant it can be your (not necessarily your employer) driving decision in life.
Of course, you need to suffer. That's about having tradeoffs.
you can definitely choose not to participate and give the opportunity someone who are happy to use AI and still have fun with it.
(1) already have enough money to survive without working, or
(2) don't realize how hard of a life it would be to "flip burgers" to make a living in 2026.
We live very good lives as software developers. Don't be a fool and think you could just "flip burgers" and be fine.
I also did dry cleaning, cleaning service, deli, delivery guy, etc.
Yup I now have enough money to survive without working.
But I also am very low maintenance, thanks to my early life being raised in harsh conditions.
I am not scared to go back flipping burgers again.
It could even have been picked up in pretraining and then rewarded during rlhf when the output domain was being refined; I haven’t used enough LLMs before post training to know what step it usually becomes noticeable.
Not a statistically significant sample size.
https://www.surveymonkey.com/mp/sample-size-calculator/
As with every new tech there's a hell of a lot of noise (plugins, skills, hooks, MCP, LSP - to quote Kaparthy) but most of it can just be disregarded. No one is "behind" - it's all very easy to use.