LLMs are eroding my software engineering career and I don't know what to do

> I still have one pillar standing, though: code quality and software architecture - what's now being reduced to being called "taste".

Genuine question: what exactly is "quality"?

It's something I've been trying to understand for a very long time. It seems like it's entirely contextual, and it has both subjective and objective facets (the latter only for quantifiable things, and still entirely contextual).

Author says Claude now one-shots distributed systems bugs that used to take him two days but most top comments here are still playing down frontier model capabilities.

Are we collectively in denial? It's understandable as the craft as we knew it is being disrupted by tools that have improved at an astonishing pace.

Yes, Code Monkey jobs are gone... I can assure you though that there are plenty of hard problems that reduce human suffering which still need humans to solve them.

> All my finance and payment domain expertise, all the debugging intuition and distributed system knowledge earned through hours of sweat and tears, is now promptable.

Is it really though? Access to information is quicker, but you still need to know what ‘good’ looks like to leverage it effectively. I can prompt my way to a medical diagnosis, but I’d still want to run it by a doctor.

What I tell my team to do is to drop using so many cloud saas apps, and build more themselves using LLMs.

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.

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.

I think that the domain knowledge still matters: if for nothing else, then at least it can make the communication both with savvy AI tools and savvy humans more effective compared to "outsiders": acquired vocabulary, truly grokked concepts in the field of target expertise etc… -- that all seem like a huge competitive advantage over folks having to learn all that "on the go", constantly struggling to pick the right nomenclature or using wrong or vague terms. It's mostly that domain knowledge what makes experts understand problems faster or at all, even.

I don't believe agents care less about architecture than us. Badly architected code has the same effect on them as on us, namely to slow them down and degrade the quality of their output. Which translates to the same thing as well, loss of revenue.

Coding agents are driving up the value of architectural skills to the detriment of more specialized/technical skills.

I code myself now and have given up on LLMs, no matter what, they eventually make a codebase unmaintainable. The uncertainity of LLM generated code has been screwing up with my peace and guarantee I have when I wrote code myself. LLMs are not AI they are Jack. Jack of all trades, Master of None.

Jobs have always been a bad deal, especially for most people. Very unfair. Less unfair is entrepreneurship. LLMs (VLMs) etc. should make that more feasible for a broader range of people.

Engineering hasn't gone away, you're now just directing things at a higher level. You are now a architect & manager (but you're managing agents not people).

Who sometimes has to deep dive & mentor a agent on solving the right problem.

AI is beat thought of as an exoskeleton, you'll be at a huge advantage if you learn how to use it properly, and you will, unfortunately fall behind if you don't. I still think we're going to need people who can reason about code, and the amount of code to reason about is exploding in volume. Think of it as doctors having access to better drugs and techniques - they can can cure more illness, but the bar and expectation of what they can do will just raise. And doctors are still well paid, because what they do is important and needs doing well.

Well, not a single 20th-century science fiction novel features programmers; instead, there are platonologists, biologists, and linguists. Humanity is twenty years behind in development because the previous twenty years were spent solely on e-commerce.

>Agents do a really bad job at keeping codebases organized. If you do a disciplined way of development with agents by keeping all Documentation in markdown format, repo structure, Decision records and architecture, they do absolutely organized. Every new module should be documented and the editor configuration and coding patterns can be given as reference. this worked well for me. and it make enhancements, extensions development without any big troubles.

Use the LLMs to improve your career as software engineer

I’m just continuing to get paid as long as I can, while also going back to school part time to train in a role that’s insulated from AI. Having a backup plan at least makes me feel better day to day.

I am mostly worried about the current AI use in management. I’ve met a few with ”AI hubris” making poor managerial decisions that stem from their poor usage of ChatGPT (not understanding the importance of context, model sycophancy, etc).

Coding taste and good architecture are the final pillars because AIs are trained on a ton of bad examples that are presented as good examples. That pillar will stand until AIs are able to reconsider and re-evaluate the material they've been trained on.

The last sentence in the article is correct:

"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 can synthesize the domain knowledge so long as it's within their training data. At some point, blindly trusting the decisions they make becomes gambling.

I used to be in the "AI will soon do all your thinking for you" camp, but I was overlooking a scenario: sometimes the gap between what you understand and what you're trying to achieve is so wide that no prompt can bridge it. Simply asking "what's the right question to ask?" doesn't feel enough, no matter how advanced LLMs become.

It feels like it's time to start turning the screws on regulation of software engineering.

If productivity is really getting better, regulation can force that productivity to go into increasing software quality.

Even if the model can replace a domain expert on the software side, you still need a human who can decide if the technical solution actually meets the business needs and that would require a human with domain expertise.

Software engineers with low self-esteem who built their entire identity as mechanical cognitive workers are having an identity crisis and spreading FUD.

Currently, LLMs are nothing more than amplification tools that require significant steering. If you think your job is mainly to take input from POs or managers, translate it into if/else statements and loops, and review PRs, then you never really understood your role. Software engineering—for those who went to university and studied it—is fundamentally about complexity management and cognitive automation. People in the field, or at least those with some math background who studied software engineering properly, understand that it's all about managing complexity; current tools are nowhere near replacing a software engineer. What they call "taste" is imagination, creativity, embodiment, a more intuitive understanding of context, and yes, superior intelligence compared to current AI. However, AI and LLMs are excellent at mechanical work and mimicking human intelligence, so use them for what they are, and stop whining.

Going forward, the world is ever-growing in complexity, and automation will become widespread everywhere. LLMs just unlocked another level. So basically, cognitive work will be automated—perhaps up to 90%—until the next breakthrough (if ever). You can sit and cry, or you can learn the tools and help shape the future.

Software engineers can automate the entire economy now, including the executives, yet they just sit there whining and crying. This is a self-esteem, confidence, and identity issue more than anything else.

What work remains valuable when implementation becomes cheap? How about moving closer to ownership?

I think that in a product-centric or mission-centric perspective, effective automation is good, because it frees you up to do other important things. E.g., in gardening, time spent weeding, is time not spent surviving slug armageddon.

This post is sad. Hacker news is turning into /cscareerquestions as someone who's watched this for last 15 years it's going downhill.

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.

looks like you just need a bit of harness for your AI: https://leestack.dev/writing/nasa-rules-for-code-that-cant-f...

I wonder how do people use LLMs so it does not hallucinates. Like 90% of the time the code is impeccable, but the remaining 10%... Let's say I determine the expertise by how well do people act of these 10%. For me, the first pillar is still there, but not in a good condition

It's not just our careers. In the hunks versus nerds wars, it is now clear who has won. The nerds have made themselves obsolete and put the continued evolution of homo sapiens to an abrupt halt.

The market still seems to be hot for roles that provide leverage like platform engineers and Staff+ engineers

I am kind of like of in the same place though roughly 5 years more than author.

I thought about going back to college, learning Math, Statistics, advanced Machine Learning and applying for research role at a frontier lab.

That's a super silly take. As much as I did math and even course on machine learning back in the days and I was making basic perceptron in code at university - to get back and be able to do so on frontier level that's years I don't have anymore.

Anthropic is doing all that also with their LLMs so that ship sailed.

Big thing is — business people are not going to spend time prompting LLM to make an application. If they do then they will become "programmers" and we all (experienced developers) know — you touch it you own it — they (business) will not bother running or taking responsibility.

Right now on r/sysadmin there was bunch of posts where admins have "vibe coded apps" requested to be "productionized". Those business types requesting don't know yet — you touch it you own it — they think they can vibe code app drop it at ops and it is all fun and games. When people will start requesting features, start nagging about bugs, start cursing on whatever changes they introduced it will be back to "hey maybe we will just get someone to do that for us".

  You might not need as deep software dev knowledge but with deep software dev knowledge you still will be faster operating LLM to build systems than non-dev

The company is hiring; the author mentioned they are talented and unemployed for the past 8 months. Why not remind the company to re-hire them?

"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

LLMs mean less devs are needed, not no devs. even after serveral more decades, they'll need steering. I've seen agents stuck chasing one issue, when to me the issue was obvious, but I can see how the model would rule out the obvious easily and move on, but my instinct/experience tells me that's where I need to focus time on. This translates into costly token-waste. Secondly, it isn't simply "quality", the LLM might generate something that's good quality from its perspective, but it simply won't consider things unless it's explicitly told to in excruciating detail, and even then! understanding things from a simian point of view can't be perfected without that simian experience as part of its training. It can come very close but not quite.

Think of it this way, who needs engineering managers, project managers, scrum masters,etc.. if they're employable then surely actual devs that can tell what good architecture is vs bad, good code vs potentially bug code is are also employable.

But the number of devs needed, that demand will obviously decline dramatically. At the same time though, there are other careers that require programming and software dev as part of your skill set. Simply integrating LLM-enabled solutions into real world workflows is a new area that's very young and immature.

Let's not act like we're suddenly in some sort of post-scarcity utopia where all problems are solved by LLMs, where tech can solve problems, there is demand for those who can use technology to do so. However, I see a lot of people attacking the technology and resisting change a lot, and to those I suggest they look up every single technological revolution and see about the fate of such people.

This person was hired, from the beginning, to be a meat shield. To be responsible for decisions they won't be allowed to make.

> And we all know the demand is drying up.

I don’t think the data really supports this? Last I checked at least.

Software engineers are fungible commodities, in the wake of the LLM.

Agents may have made 80% of your experience go to $0, but the other 20% is exponentially more valuable now. This outweighs your other losses.

The ability to orchestrate intelligence is a magnificent power that few have, and while barriers to entry will be eroded, it will take time and they won't be eroded fully. This is your edge.

Reads like “AI is inevitable” propaganda to me

It's not just about it taking the technical competence away from our job, it's taken away the joy [1] which I wrote about.

I feel like many of my peers are beating around the bush on this topic and in denial. Even if you accept it can do a large portion of the technical part of our work, we are just supervisors at this point making sure it doesn't do any stupid shit. What is the point? Where is the fun in this? Where is the challenge? At least I have enjoyed building my career over the last 20+ years and building software, but find little joy in the work I'm doing now.

I think we're going to see a massive exodus of folks leaving the profession and a huge mental health crisis, long before the folks working in other sectors realise what's hit them.

[1] https://deanclatworthy.com/2026/02/09/the-joy-of-programming...

I read all the posts in this thread - but no one has a good idea to avoid software developer obsolescence. My guess is this profession has 5 more years. It was a good run while it lasted.

All the other white collar workers are in the same boat. A pillar of the economy is going to be destroyed with no obvious replacement in sight.

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'm just another off-the-shelf engineer now

You're wrong there. You are capable of judging the outcome of the llm.

> But I don't know what to think about the long-term.

Don't you think it all has taken long enough. When I look back at the beginning of my career and compare what we do now ... I cannot shake the feeling we're essentially still solving he same problems and we have accepted that as being normal. Complexity skyrocketed, (abstraction) layers got added but the needle didn't move exponentially together with that. I think the IT industry as a whole gets what it deserves, thinking that we would remain the maze masters of the mazes we create.

> Maybe I should consider transforming my woodworking hobby into a profession...

I'm looking for 8 (affordable) oak panel doors with the exact same measurements as my current doors so I can replace them. That shouldn't be too hard to find you'd think right?

I don't know how else to say this but LLMs are just word calculators. They are becoming better for sure but at this point even Claude 4.8 is absolute shit at any complex task in a not so common field. I have been working on terrain contour matching algorithms for the last few days and, oh boy are the predictions about AI taking over the world wrong. Its the highest level of bullshit I have ever come across in my life. I ended up writing 100% of the actual algorithm myself. It's a productivity mess.

I think this experience is universal. The answer is the same as always has been - develop skills that are becoming most important. Right now that is (at least from what I can see): - Data analysis, data pipelines, models, etc. - Tacit business knowledge - architecture and design patterns (always has been, but now the scale os larger so this is even more important)

It's harsh but nobody cares if a model or a human made a system.

The "good" bits are that now automating anything and providing value from software is much easier. If I have an idea or a nitpick somewhere, I can just do it, up to a limit (which is quickly rising).

I have always been a generalist and generally interested in a very wide array of things, and this period has been the most exciting in my engineering career (13y now). Learning about anything is so frictionless, looking back at my first learning experience - picking up a fat C++ book and spending days/weeks debugging, while I can romanticize that, I would never go back.

I can also now write software solo or with an extremely small team at a huge scale in comparison, and that is super exciting.

A lot of skills that took sleepless nights to acquire, they are "gone", but I still don't regret anything or wouldn't go back. Their "usefulness" has degraded, true, but this has always been the case with engineering.

We are now able to spend much more time thinking about utility rather than low level implementation and imo that's great.

We have many challenges ahead of us, and there are seriously bad things, the biggest one I have experienced is the hours are increasing and mental load is vastly increasing as well. As capacity, speed and leverage increases, so do expectations and hours, and that is probably a social problem.

Sorry for the unstructured stream of thoughts, and this is just an opinion (quite an unpopular one I believe), I hope your distress decays away for a new excitement and new opportunities.

Thanks for the article .

This reads like a self thought ecommerce/small company employee finding its place in the tech world. These people were erased first, understandably. I am meeting more and more of the same type of people.

I had a friend in LA who was sure that CSS and HTML were enough for her to be a "Senior frontend developer". This year she moved to Tennessee and is trying to find a rich husband because she can't find a single job.

One other thing I find it is bound to happen is that this domain knowledge you speak of is just going to shift towards LLM domain knowledge.

Look at prompt engineering, and how quickly it became a hot thing. Does everyone know to steer their AI well? There's only so much a harness can do for you once you start attempting to one shot with a single sentence of 4 words.

As others said, "write a Rust compiler make no mistakes" can only work if you overfit a harness to that single prompt. Nobody is going to do that.

So the part you mentioned about the knowledge you accumulated around how to know that "trade-offs between implementations" and "idempotency to prevent double-charges" is just moving to the domain of the english language and tokenizers. One could argue here that this is far more interesting as it requires you to explore deeper into how we communicate and describe the world around us. Reminds me of physics and math.

I think there's an optimism lenses to it if you can grasp it as an opportunity rather than an inevitable doomsday apocalypse.

The reason that I’m looking for an out is that it’s turned everyone I work with into imbeciles.

Nobody wants to think anymore. Coworkers are now just intermediaries for their LLMs. Talking to them is just talking to the LLM - sometimes directly copied and pasted, sometimes minimal effort to conceal what they’re doing. It is so disheartening.

And the sad part is, LLMs are incredible and can enable you to do much better work if you can stay in the loop, and stop focusing only on shipping speed. But from what I have observed, very few people care to do this. Who cares about substance when middle management thinks your productivity is 10x?