Ask HN: With all the AI hype, how are software engineers feeling?
61 cpt100 103 8/11/2025, 4:20:30 AM
I'm just wondering what the morale is with AI doing 30-50% of your work? Is your company hiring more/ have they stopped hiring software engineers? Is the management team putting more pressure to get more things done?
AI is sometimes a productivity booster for a dev, sometimes not. And it's unpredictable when it will and won't be. It's not great at giving you confidence signals when you should be skeptical of its output.
In any sufficiently complex software project, as much of the development is about domain knowledge, asking the right questions, balancing resources, guarding against risks, interfacing with a team to scope and vet and iterate on a feature, managing resources, analyzing customer feedback, thinking of new features, improving existing features, etc.
When AI is a productivity booster, it's great, but modern software is an evolving, organic product, that requires a team to maintain, expand, improve, etc. As of yet, no AI can take the place of that.
If you say AI does 0% of your work, I'd say you're either a genius, behind the curve or being disingenuous.
AI was doing 0% of my work 10 years ago too, why should I be any less effective without it now?
You think I'm behind the curve because I'm not buying into the AI craze?
Ok. What's so important about being on the curve anyways, exactly? My boss won't pay me a single cent more for using AI, so why should I care?
But when you're being graded on a curve, standing still can still mean falling behind.
Which isn't to say that AI is definitively ahead of the curve; I think we're a bit early for that. But as actual answers to your actual questions - it's important because if everyone else gets ahead of you, your boss will STOP paying you
(and if you're "good at AI", you can at least make bank until the bubble bursts)
There are reasons that seasoned OSS developers reject AI PRs: https://news.itsfoss.com/curl-ai-slop/ (like the creator of curl). Additionally, the only study to date currently measuring the impact on LLMs on experienced developers found a modest 19% decline in productivity when using an LLM for their daily work.
https://metr.org/blog/2025-07-10-early-2025-ai-experienced-o...
Now we can ponder behind the reasons that the study showed experienced developers get a decrease of productivity, and you anecdotally experience a boost of "productivity", but why think about things when we can ask an LLM?
- experienced developers -> measured decrease of productivity
- you -> perceived increase of productivity
Here is what ChatGPT-5 thinks about the potential reason (AI slop below):
"Why You Might Feel More Productive
If senior developers are seeing a decline in productivity, but you are experiencing the opposite, it stands to reason that you are more junior. Here are some reasons why LLMs might help junior developers like you to feel more productive:
Lower Barrier to Entry
- LLMs help fill in gaps in knowledge—syntax, APIs, patterns—so you can move faster without constantly Googling or reading docs.
- Confidence Boost You get instant feedback, suggestions, and explanations. That can make you feel more capable and reduce hesitation.
- Acceleration of Learning You’re not just coding—you’re learning as you go. LLMs act like a tutor, speeding up your understanding of concepts and best practices.
- More Output, Less Friction You might be producing more code, solving more problems, and feeling that momentum—especially if you are just starting your coding journey."
Now that we can use Copilot, we have a new CIO and I don’t hear about it so much. There is still some AI hype, but it’s more about how it’s being used in our products, rather than how to use it internally to do the work.
Apparently sometime in the next year we’re getting a new version of Jira with some AI that can do user stories on its own, but I don’t see that changing much of anything.
The bottleneck has rarely been the actual writing of code, it’s been people making decisions and general bureaucracy. AI isn’t solving that. Copilot has also not impressed anyone on my team. As far as the code we work on, it’s pretty bad. There are a few niche things it helps with, mostly writing queries to pull values out of complex json. That saves a little time, but hardly 30-50%. More like 1-2%.
Management stopped giving us new people, while pressuring us to do more, for many years now. This was a trend long before AI and I haven’t noticed any major change. I’d say it’s been this way for over 10 years now, ever since they had the realization that tasks could be automated.
My suspicion is that it's a reflection of how people like Altman want to be treated. As an European who worked with US companies, my experience with work communication there can only be summed up as being heavily biased towards toxic positivity. Take that up another 3 egotistical notches for CEOs and you get the ChatGPT tone.
I've once heard the company mandated more positive tone. To avoid words like "issue".
Not an issue, it's an opportunity! Okay, we have a critical opportunity in production!
My organization would still hire as many software engineers as we could afford.
- Stack Overflow has to be actually dead at this point. There's no reason to go there, or even Google, anymore.
- Using it for exploratory high level research and summarization into unfamiliar repos is pretty nice.
- Very rarely does AI write code that I feel would last a year without needing to be rewritten. That makes it good for things like knocking out a quick script or updating a button color.
- None of them actually follow instructions e.g. in Cursor rules. Its a serious problem. It doesn't matter how many times or where I tell it "one component per file, one component per file", all caps, threaten its children, offer it a cookie, it just does whatever it wants.
I wonder if we are going to pay for that, as a society. The number of times I went there, asking some tricky question about a framework, and have the actual author or one of the core contributors answer me was astonishing.
I think that a certain kind of craftsmanship will be lost.
I used to answer a lot of the basic questions just to help others as I've felt I had been helped, the moderation shift applying more and more rules started to make me feel unwelcomed to ask questions and even to answer. I do understand why it happened, with the influx of people trying to game the platform to show off in their resumés they were at the "top" of whatever buzzword was hot in the industry at the time but it still affected me as a contributing user out of kindness.
By 2018 I would not even login to vote or add comments, and I feel it was already going on a slow downhill path, and LLMs will definitely kill it.
We will definitely suffer, SO has been an incredible resource to figure out things not covered well in documentation, I remember when proper experts (i.e. maintainers of libraries/frameworks) would jump in to answer about a weird edge case, or clarify the usage of a feature, explain why it was misuse, etc.
Right now I don't see anything else that will provide this knowledge to LLMs, in 10-20 years time there will be a lot missing in training datasets, and it will be a slow degradation of knowledge available in the open for us all to learn from.
- Made people treat it like a contest and tried to game it
- Obscure, difficult questions, with obscure, difficult answers barely being valued, while 'How do I make a GET request in node' going gangbusters.
If, like the meme, you just copied from SO without using your brain then yes AI is comparable.
If you appreciate SO for the discussion (peer review) about the answers and contrasting approaches sometimes out of left field, well good luck because AI can't and won't give you that.
If people can seriously have an AI do 50% of their work, that's usually a confession that they weren't actually doing real work in the first place. Or, at least, they lacked the basic competence with tools that that any university sophomore should have.
Sometimes, however, it is instead a confession "I previously wasn't allowed to copy the preexisting solutions, but thanks to the magic of copyright laundering, now I can!"
So generally the people getting the most use out of LLMs are people who are using these higher levels of abstractions. And I imagine we will be building more abstractions like HTML to get more use out of it.
Strongly agree here. I am extremely skeptical of anyone reporting this kind of productivity gain.
As of AI, I've been asked to test a partial rewrite of the current UI to the new components. For a few weeks I've been logging 10+ bugs a day. The only explanation I have, they use AI tool to produce nicely looking code which does not work properly in a complex app.
Mostly of having to try and explain to people why having an AI reduce software development workload by 30-50% doesn't reduce headcount or time taken similarly.
Turns out, lots of time is still sunk in talking about the features with PM's, stakeholders, customers etc.
Reducing the amount of time a dev NEEDS to spend doing boilerplate means they have more time to do the things that previously got ignored in a time poor state, like cleaning up tech debt or security checks or accessibility etc etc
I'm tired of having to try and explain that AI isn't remotely reducing my workload by 30-50%, and in fact it often probably slows me down because the stupid AI autocomplete gets in the way with incorrect suggestions and prevents me from getting into any kind of flow
It’s mostly seen as a force multiplier. Our platform is all Java+Spring so obviously the LLMs are particularly effective because it’s so common. It hasn’t really replaced anyone though, also because it’s Java+Spring so most of our platform is an enormous incomprehensible mess lol
Overall, it sped up my learning greatly, but I had to verify everything it said and its code was a mess. It's a useful tool when used appropriately but it's not threatening my job anytime soon.
So in the end I use it fairly often when setting up new things (new infra, new files, new tools, new functions, etc). Although the time it saves is not coding time, but googling/boilerplating time. But in practice I work in a well established project where I rarely do this kind of thing (I don't think I even created a new file in the project last week).
If I am already familiar with the tool/library I almost always skip it (occasionally autocomplete is useful, but I could easily live without it). Occasionally I used for small self-contained snippets of code (usually no more than a single function). Last one I remember was some date formatting code.
Doesnt mean it wont get there - just that it isnt there yet
Letting it condense something like a paper and checking it afterwards might be a good learning exercise.
Tired of leadership who think productivity will raise.
Tired of AI summaries sent around unreflected as meeting minutes / action items. Tired of working and responding on these.
- A lot of our code base is very specialized and complex, AI still not good enough to replace human judgement/knowledge but can help in various ways.
- Not yet clear (to me anyways) how much of a productivity gain we're getting.
- We've always had more things we want to do than what we could get done. So if we can get more productivity there's plenty of places to use it. But again, not clear that's actually happening in any major way.
I think the jury is still out on this one. Curious what others will say here. My personal opinion is that unless AI gets smart enough to replace more experienced developer completely, and it's far from that, then I'm quite sure there's not going to be less software jobs. If AI gets to a point where it is equal to a good/senior developer we'll have to see. Even then it might be that our jobs will just turn into more managing AI but it's not a zero sum game, we'll do more things. Superintelligence is a different story, i.e. AI that is better than humans in every cognitive aspect.
With AI, the future seems just so much worse for me. I feel that productivity boost will not benefit me in any way (apart from some distant trickle down dream). I expect the outsource, and remote work in general to be impacted negatively the most. Maybe there's going to be some defensive measures to protect domestic specialists, but that wouldn't apply to me anyway unless I relocate (and probably acquire citizenship).
>Is your company hiring more/ have they stopped hiring software engineers
Stopped hiring completely and reduced workforce, but the reasons stated were financial, not AI.
>Is the management team putting more pressure to get more things done
with less workforce, there is naturally more work to do. But I can't say there is a change in pressure, and no one forces AI upon you.
And yes, I did test ChatGPT, claude, cursor, aider... They produce subpar code, riddled with subtle and not so subtle bugs, each of my attempts turned out to be a massive waste of time.
LLM is a plague and I wish it had never showed up, the negative effects on so many aspects of the world are numerous and saddening.
I'm wearing glasses that tell me who all the fucking assholes and impostors are.
In the psychological sense, I'm actually devastated. I'm honestly struggling to be motivated to learn/create new things. I'm always overthinking stuff like:
- "Why would I learn mobile app dev if in the near future there will be an AI making better UIs than me?" - "Why would I write a development blog?" - "Why would I publish an open-source library on GitHub? So that OpenAI can train its LLM on it?" - "Why would I even bother?"
And then, my motivation sharply drops to zero. What I've been up to lately is playing with non-tech related hobbies and considering switching careers...
On the other hand I find it super useful for debugging. I can paste 500k tokens into Gemini with logs and a chunk of the codebase and ask it what’s wrong, 80% it gets it right.
I don't think I'm being paid to 1:1 convert a dumb crud app or rest api from one language to another, although of course you do that once a decade in a typical job.
It's definitely the most consistent topic but there's a lot of other stuff.
I agree that there's a lot of other stuff though, even on the worst days.
I don't know any developers who use AI to that large extent.
Myself am mostly waiting for the hype to die out so we can have a sober conversation about the future.
AI helps here and there but honestly the bottleneck for output is not how fast the code is produced. Task priorization, lacking requirements, information silos and similar issues cause a lot of 'non-coding work' for developers (and probably just waiting around for some who don't want to take initiative). Also I think the most time consuming coding task is usually debugging and AI tools don't really excel at that in my experience.
That being said, we are not hiring at the moment but that really doesn't have anything to do with AI.
In terms of hiring- I co-own a small consultancy. I just hired a sub to help me while on parental leave with some UI work. AI isn’t going to help my team integrate, deploy, or make informed decision while I’m out.
Side note, with a newborn (sleeping on me at this moment), I can make real meaningful edits to my codebase pretty much on my phone. Then review, test, integrate when I have the time. It’s amazing, but I still feel you have to know what you are doing, and I am selective on what tasks, and how to split them up. I also throw away a lot of generated code, same as I throw away a lot of my first iterations, it’s all part of the process.
I think saying “AI is going X% of my work” is the wrong attitude. I’m still doing work when I use AI, it’s just different. That statement kind of assumes you are blindly shipping robot code, which sounds horrible and zero fun.
When code autocomplete first came out everyone thought software engineering would become 10x more productive.
Then it turned out writing code was only a small part of the complex endeavor of designing, building, and shipping a software system.
Google AI summaries and ChatGPT have almost halved my traffic. They are a scourge on informational websites, parasites.
It’s depressing to see the independent web being strangled like that. It’s only a matter of time before they become the entire internet for many, and then the enshittification will be more brutal than anything before it.
I will be fine, but I have to divert 6-10 months on my life to damage control[0] instead of working on what matters to my audience. That happened by chance; other websites won’t be so lucky.
So yeah, morale is low. It feels like a brazen consolidation play by big tech, in all aspects of our lives.
On the bright side, it does make coding a bit easier. It spits out small bits of code and saves me a lot of API docs round trips. I can focus on business logic instead of basic code. AI is also a phenomenal writing tool. I use it for trying different phrasing options, reverse word and express search, and translation nuances. It does enable me in that way.
[0] https://nicolasbouliane.com/blog/health-insurance
I am under MUCH more pressure to deliver more in shorter periods of time, with just me involved in several layers of decision making, rather than having a whole team. Which may sound scary, but it pays the bills. At one company I contract with, I now have 2 PMs; where I am the only dev on a production app with users, shipping new features every few days (rather than weeks).
It feels more like performance art, than it even feels like software development at this point. I am still waiting for some of my features to come crashing prod down in fantastic fashion, being paged at 3am in the morning; debugging for 12 hours straight because AI has built such a gigantic footgun for me.... but it has yet to happen. If anything I am doing less work than before - being paid a little more, and the companies working with me have built a true dependency on my skills to both ship, maintain and implement stuff.
I’m wondering how did you land your current gigs?
Thank you.
Are you using agentic features, given that you have not just one but two PMs?
It can kickstart new projects to get over the blank page syndrome but after that there's still work, either prompting or fixing it yourself.
There are requirements-led approaches where you can try to stay in prompt mode as much as possible (like feeding spec to a junior dev) but there is a point where you just have to do things yourself.
Software development has never been about lines of code, it has always required a lot of back and forth discussion, decisions, digging into company/domain lore to get the background on stuff.
Reviewing AI code, and lots of it, is hard work - it can get stuff wrong when you least expect it ("I'll just stub out this authentication so it returns true and our test passes")
With all that in mind though, as someone who would pay other devs to do work I would be horrified if someone spent a week writing unit tests that I can clearly see an AI would generate in 30 seconds. There are some task that just make sense for AI to do now.
It is doing 0% of my work and honestly I am tired of 80% of HN posts being about it in one way or another.
As a person I'm increasingly worried about the consequences of people using it, and of what happens when the bubble bursts.
I just simply don't get it. Productivity delta is literally negative.
I've been asking to do projects where I thought "oh, maybe this project has a chance of getting an AI productivity boost". Nope. Personal projects all failed as well.
I don't get it. I guess I'm getting old. "Grandpa let me write the prompt, you write it like this".
I find it wastes my time more than it helps
Everyone insists I must be using it wrong
I was never arrogant enough to think I'm a superior coder to many people, but AI code is so bad and the experience using it is so tedious that I'm starting to seriously question the skills of anyone who finds themselves more productive using AI for code instead of writing it themselves
perhaps 1% of the time I've asked an LLM to write code for me, has it given me something useful and not taken more time than just writing the thing myself.
It has happened, but those instances are vastly outnumbered by it spewing out garbage that I would be professionally embarrassed to ever commit into a repo, and/or me repeatedly screaming at it "no, dumbass, I already told you why that isn't a solution to the problem"
The main thing that changed is that the CTO is in more of a "move fast, break things"-mood now (minus the insane silicon valley funding) because he can quickly vibe-code a proof-of-concept, so development gets derailed more often.
Also from my experiences with agents, and given that I have been around computers since 1986, I can clearly see where the road is going.
Anyone involved with software engineering tasks, should see themselves becoming more of a technical architect for their coding agents, than raw coding, just like nowadays while Assembly is a required skill for some fields, others can code without ever learning anything about it.
Models will eventually become more relevant than specific programming languages, what is worth discussing X or Y is better, if I can generate any that I feel like asking for. If anything newer languages will have even harder time getting adopted, on top of everything that is expected, now they also have to be relevant for AI based workflows.
what sucks though is that its super inconsistent whether the thing is gonna throw an error and ruin the flow, whether thats synchronous or async.
I like that it makes it easy to learn new things by example.
I don't like that I have no idea if what I'm learning is correct (or at least recent / idiomatic), so everything I see that's new, I have to validate against other resources.
I also don't really know if it's any different from "tutorial hell".
Hiring is as haphazard and inadequate as it has been in the last 25 years, no change there.
AI usage is personal, widespread and on a don't ask don't tell basis.
I use it a lot to:
- Write bullshit reports that no one ever reads.
- Generate minimal documentation for decade old projects that had none.
- Small, low stakes, low complexity improvements, like when having to update this page that was ugly when someone created it in 1999, I'll plop it on aistudio to give it a basic bootstrap treatment.
- Simple automation that wasn't worth it before: Write me a bash script that does this thing that only comes up twice a year but I always hate.
- A couple times I have tried to come up with more complex greenfield stuff to do things that are needed but management doesn't ever acknowledge, but it always falls apart and starts needing actual work.
Morale is quite crappy, as ever, but since some of the above feels like secretly sticking it to The Man, there are these beautiful moments.
For example when the LLM almost nails your bimonthly performance self report from your chat history, and it takes 10 minutes instead of 2 hours, so you get to quietly look out of the window for a long while, feeling relaxed and smug about pocketing some of the gains from this awesome performance improvement.
It's helping with a lot of toil work that used to be annoying to do, PMs can do their own data analysis without having to pull me out of deliverable tasks to craft a SQL query for something and put it up on a dashboard; I don't need to go copy-paste-adapt test cases to cover a change in some feature, I don't need, most times, to open many different sections of documentation to figure out how a library/framework/language feature should be used.
It's a boost to many boring tasks but anything more complex takes as much work to setup and maintain the environment for a LLM to understand the context, the codebase, the services' relationships, the internal knowledge, the pieces of infrastructure, as it does for me to just do the work.
I've been hybridising as much as I can, when I feel there's something a LLM would be good at I do the foundational work to set it up, and prompt it incrementally to work on the task so I can review each step before it goes haywire (which it usually does), it takes effort to read what's been generated, explain what it did wrong so it can correct course, and iteratively build 80% of the solution, most times it's not able to completely finish it since there's a lot of domain knowledge that isn't documented (and there's no point in documenting since it changes often enough). Otherwise it's been more productive to just do the work myself: get pen and paper to think through the task, break it down after I have a potential solution, and use LLMs to just do the very boring scaffolding for the task.
Does it help me to get unstuck when there's some boring but straightforward thing to do? Absolutely. Has it ever managed to finish a complex task even after being given all the context, setup the Markdown documentation, explain the dependencies, the project's purpose, etc.? No, it hasn't, not even close, in many cases it gave me more work to actually massage the code it wrote into something useful than if I had done it myself. I'm tired of trying the many approaches people seem to praise about and see it crumble, I spent a whole week in 2 of our services writing all the Markdown files, iterating through them to fix any missing context it could need, and every single time it broke down at some point while trying to execute a task so, for now, I just decided to use it as a nice tool and stopped getting anxious about "missing out".
All companies will end up with just one employee. If you don't agree with this, you don't know how to prompt.
Baffled because there are too many rank-and-file tech workers who seem to think AI exciting/useful/interesting. It’s none of those things.
Just ask yourself who wants AI to succeed and what their motivations are. It is certainly not for your benefit.
Moving fast in the beginning always has caveats.
In the meantime I'm doubling down on math and theory behind AI.
AI is an irrelevant implementation detail, and if the pace of your work is not determined by business needs but rather how quickly you can crank out code, you should probably quit and find a real job somewhere better that isn't run by morons.
I’m looking for a way out of tech because of it.
I still don’t see this, if only for the Managerial instinct for ass-covering.
If something really matters and a prod showstopper emerges, can those non-technical supervisory managers be completely, absolutely, 100% sure the AI can fix the code and bring everything back up? If not, the buck would surely stop with them and they would be utterly helpless in that situation. The Board waiting on conference call while they stare at a pageful of code that may as well be written in ancient Sumerian.
I can see developers taking a higher level role and using these tools, but I can’t really see managers interfacing directly with AI code generation. Unless they are completely risk tolerant, and you don’t get far up the greasy pole with those tendencies.
That 50% is unit tests.
The AI will replace us all in 2028! For real this time.
But before that, all the mid-managers will be replaced first, then the tech writers, the QA people, the PM, the...
The devs are closing the lights behind...
No comments yet
First you augment, then replace.
Anyone doing simple web design/development work is fairly easily replaceable at this point.
I don't really see it replacing us in the near future though, it would be almost useless if I wasn't there to guide it, write interfaces it must satisfy, write the tests it uses to validate its work etc. I find that projects become highly modularised, with defined interfaces between everything, so it can just go to work in a folder satisfying tests and interfaces while I work on other stuff. Architecting for the agents seems to lead to better design overall which is a win.
I'm just writing crud apps though, I imagine it's less useful in other domains or in code bases which are older and less designed for agents.
My next experiment is designing a really high level component library to see if it can write dashboards and apps with. It seems to struggle with more interactive UI's as opposed to landing pages.