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

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.

My career path is suprisingly similar to the author's. Weirdly enough, what he takes as the first pillar to fall is the one I see most undamaged currently.

LLMs routinely fail at our business specifics: Local tax regulations, particularities of the accounting process, specifics of our ledger implementations. They're great at refactoring, translating between languages, tracing bugs on existing code even, but there is always many things subtly wrong iterating and expanding our domain.

This might be because the companies I worked for happen to be tackling complex domains precisely for moat-building reasons. They stay in business explicitly because there's not a book out there you can read to build a clone, the knowhow stays inside.

Also, a fintech whose managers recommend speeding up design docs with AI sounds way too careless to be in the money handling business. It's way, way too easy to end up with millions incorrectly allocated, particularly if you deal with high volumes of small transactions. These bugs are always a bitch to deal with because correcting the logic is just step one, you then have to correct all the wrongly calculated data in immutable DBs, move around the red tape and client comms, and your fix is bound to become a gotcha that new features and observability have to take into account ("remember that there's a bump in the data in february 2 because we had incident X".)

> 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.

I’ve been using Claude Code with Opus 4.7; it’s not that the code it produces is wrong, it simply tends to write too much of it. In my opinion it’s still worth thinking about a particular feature and finding the best way to fit it into your code because Claude will often just pick a layer of the stack (maybe presentation), and jam it in there. A couple weeks later you need this data somewhere else and Claude can’t reuse the code (maybe in the service layer) so it kind of “ports” it over. Unless a person is paying attention we now have the double the amount of code and duplicate logic. I don’t see AI tools like Claude getting better at this anytime soon.

Where I work there’s already pressure to use Opus 4.7 less to save money, someone mentioned using a smaller model for “simple bug fixes”. This might work sometimes but how often do we really know it’s a simple bug fixe ahead of time? I suspect as costs go up we’ll see interest in using these tools to write “all the code” go down. As people migrate to cheaper and less effective models I suspect we’ll see the pressure to skip reviewing that code dissipate as well.

We’ll see where we land, maybe it won’t as dramatically different as the author of this post fears.

> 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.

There's a certain irony in masters of automation lamenting that their roles are being automated. I wonder whether the jobs their efforts eroded in the past ever got the same thoughts...

Programming, logic, etc are skills and toolkits. The optimal state of society is everybody being able to apply them, not just the enlightened compsci caste. There was a time in the past where scribes were paid nice cash for their efforts, too.

I guess the lesson to learn here is treating a toolkit as an identity and job for life. By virturee of the essence of the job itself - if the tool gets cheaper and more widespread, it's aactually success, not betrayal.

Yeah the writing is on the wall. Not just for knowledge work, but for jobs in general, as I've been saying in other comments. The era of wage labour, and this dominant economic system, is coming to an end. There's no way it can coexist with AI, but it also needs to continuously push for better AI, which means there's no stopping it. The only thing to do really is brace for the disruption - which will likely be pretty rough - and hope governments play their role properly to ease the transition.

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.

This doesn’t read to me as someone who is sincerely impressed or rather surprised what ai is capable off.

This reads like someone is trying to convince me, that ai is just this good, and that the author is telling me to use more ai.

To me this sounds like: Trust me, it’s really bad, i know what I’m talking about. Just lean into it, or change profession.

> 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.

I think the author downplays how much of that knowledge is used on knowing what to zoom in on, what to prompt, or what to look for.

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.

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.)

This is good. We want less barrier to entry and more competition in software.

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 think this is the first time I saw someone describe so clearly my concerns and experience with LLMs.

I have little to add to it, except that I agree completely. Not sure what’s next

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.

>Of course, I'm still employable because someone has to review the code and steer the robot...

We will work for the robots, steering them to steer us.

I've consulted with some big companies on AI strategy. I tell them there are two approaches to AI.

1) Train AI to replace human work. This gives you 50% quality for 10% cost. 2) Train AI to assist human workers. This gives you 200% quality for 110% cost.

Most companies will go with option 1, and it's a race to the bottom. Eventually, someone will go with option 2 and gather up all of the pieces and take over the market.

don't worry, soon there will be no "software engineering" careers anymore.

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.

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.

> 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.

>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.

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.

> when I step outside my area of deep knowledge I can no longer call BS on the agents

It's still funny that 4 years into this mania the models can hallucinate basic ground truths, humans are increasingly not reviewing the output, and misusing LLMs where simple automation would suffice.

My wife does project management and works with a lot of tech leads. They came to her with a project plan deck, and she started questioning some weird dates.

The LLM was able to pull artifacts out of their issuer tracker, but it just.. hallucinated some of the dates in the process of creating a project plan deck out of the underlying data. These guys didn't care to review and notice, and who knows what else it hallucinated content wise. They were happy to send this project plan multiple levels up the food chain with hallucinated unreviewed dates.

5 years ago they would have just written a script and had none of this mess.

I still struggle to accept this when my colleagues are producing implementations with AI assistance that are consistently broken and don't do what they think they do. As yet I can't square this circle, no one is better at their job than they were before.

I feel that I am faster and better, sure, but trusting self perception would be an absurd thing to do.

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.

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

> 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).

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.

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 are good at general solutions but not specific solutions. As industries evolve and laws, regulations, and practices change LLMs will struggle because those things are not included in its training set yet. We'll always need humans to push companies in new directions in order to compete, unless we eradicate capitalism altogether and then we're all out of luck. No competition means no incentive to try and be better than the next guy which means no new products and services for humans to develop that AI hasn't seen already.

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

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.

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

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.

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

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...

While LLM's are beyond junior level at this point, they're still just that. I don't really agree that the first two pillars have been affected.

I've shared a story before that between now and 2 years ago a developer who solely relied on AI has produced the same hot garbage instancing system within the same time period. For example back in my day in 2 years I went from writing a system that struggled with few hundred players to one that could handle thousands and far beyond that. The person using AI 2 years ago wrote a system that didn't work and wrote a system 3 months ago that doesn't work.

Everyone is saying how great AI is, but they're missing that the driver is just as important AI wouldn't be able to achieve any of this without capable (often seniors) using it and giving it guidance. It's really a difference between "it works" and "it works without flaws".

Of course AI can produce things that also "work without flaws" with solved problems and someone "recreating" something that already exists with AI is not that special, a junior developer could accomplish the same thing given the time.

But I do agree that AI becoming part of performance reviews and all that is producing more productive developers which is going to drive the cost way down. In a way AI is stealing from a developers salary and giving it to the AI companies which is pretty ironic considering how cold developers seem towards artists.

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?

So blog with single post hyping LLMs. Oh and the domain name "human-in-the-loop". Call me suspicious.

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 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 .

> Of course, I'm still employable because someone has to review the code and steer the robot. But I'm just another off-the-shelf engineer now. I have no domain expertise that another Sr. engineer steering an LLM cannot match. 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.

Ownership and responsibility are the new currency for the engineering staff. Willingness to implement these tools and then own the consequences of their use is what leadership is looking for. They want their cake while they eat cake, and they will keep those around who enable something approaching that experience. Owning the side effects of LLM use is more challenging than our own natural output because of the radical volume increase and unfamiliarity with low level details. However, I argue it is still possible. It has always been significantly more expedient to poke holes in someone (something) else's work than it is to perform that same work. And, the executives know this. They leverage this capability too.

The relationship between the business and the development team has been tenuous at best. I've rarely seen a technology team that was properly subservient to the business that ultimately signed their paychecks. I every case I have personally experienced, it is was like a hostage situation where the business owners are in constant terror of the technology people screwing them over in some infinitely nuanced way they or their lawyers could never understand. Many business owners are looking at this technology as a way out of the hostage situation. They noticed a window that was left unlocked. They are going for it right now. Whether or not they will succeed in their escape is a separate matter. Whether or not them being held hostage was justified is also a separate matter. It really helps to keep these things in their own lanes.

"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

LLM is a powerful tool but it still doesn’t have the context that a person would have. A million tokens is a drop in the bucket compared to the overall context that the person guiding the LLM needs to keep it on track and being productive.

If you’re not a good engineer and you don’t have the domain knowledge, your token costs will be very high for whatever gets shipped, because you won’t be able to provide the context necessary to prompt machine efficiently.

Claude will still very often hallucinate bugs, explanations, domain requirements, that have no basis in reality. It will offer fixes and improvements that are pretty standard but not optimal. This is correctable if you catch it, but you need to review every line of code and comment, because in addition to being obviously wrong, it is often very subtle in the wrongness. For every bit of “slop” there is almost microslop, the places where it just kind of confidently guesses… and doesn’t tell you… but sometimes is correct anyway.

The “problem” is there’s less low hanging fruit. You have to know a lot to add value beyond being a middleman gating the slop. You have to really pay attention to the details to find some of the errors that it’s making.

I'm not worried. You cannot hold a machine accountable and there's no way OpenAI, Anthropic, etc. are going to take on that kind of liability if some code resulted in a major outage or a lawsuit. Perhaps that's the signal I'd be looking for: so much confidence in the product that they put their money where their mouth is.

Besides, you can look at the websites/apps/software you use everyday and evaluate whether or not the agentic era has produced better results. Personally, there's still plenty of bugs and annoyances. Banks still using SMS 2FA, library breakages in minor version bumps, inconsistent UIs between web and mobile, etc.

If all that was a hurdle before... because humans, regulations, or something else... then surely these magical machines that can supposedly replace us and do it much faster would've handled it by now? And they wouldn't introduce more bugs[0], would they? ;)

0: https://www.0xsid.com/blog/meta-account-takeover-fiasco

move yourself to regenerative ag. take a look.

> 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've wondered about this a lot. I am brand new to software engineering, fully powered by AI coding. Traditional software engineers have to pivot hard or the are going to be left in the dust. The slow, methodical, take two days to put a change on a production site approach are over. I'm shipping exponentially faster than a co-worker who hasn't embraced AI yet.

If corporations really thought LLMs were a great cost-savings tool, then the obvious target for replacement are not the lower-paid staff, but the higher-paid staff - the ‘product managers and stakeholders’. That justifies token burn, replacing the 7- and 8-figure people, right?

But that’s not the real goal, is it? The goal is to inflate the stock value, take the cream off the top, and dump the whole business on the pension funds, maybe creating a too-big-to-fail scenario where the government steps in an bails out the industry as with the airlines during Covid.

This is why all the testimonials and narratives are so suspect - nobody knows what fraction of online posts were created simply to sell the narrative that LLMs are this incredible disruptive tool that will change the world, solely in order to create FOMO in the investor class.

In this particular case, I’d like to see links to samples of LLM created codebases for “PCI compliance, double-entry ledgers, escrows, reconciliation, payment lifecycles, bank transfer idempotency”. It should be easy to put an open-source LLM-generated version up on github, right? And if not, why not?

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"

'Maybe I should consider woodworking' - Fuck off.

I have no idea what you guys are up to, but it is just a job, it is just a role, it says nothing about you or who you are and it is not tied to your meaning. If you make it so and your perception is aligned with that, then you are not in control of what happens to you. What kind of slavery it is to give other people so much control over you is crazy

There is an element of human nature that is known as self delusion and it is extremely common. Almost everyone on HN is suffering from a form of self delusion.

Usually when a human self deludes they do it when they're identity is under threat. People would rather hold on to identity then face the truth at the cost of their identity. That is what is going on in almost every HN thread that has to do with this topic.

A good example is religion. Someone who is intelligent, but born into a religion, will have a hard time giving up that religion EVEN when presented with logical/rational/realistic arguments for why that religion is false. They will rationalize the most convenient reasoning to maintain their own identity.

I mean think about it. Even the concept of religion is obviously false. It's not science, it talks about phantasmic beings that OBVIOUSLY don't exist. It's inconsistent among different groups as in there's thousands of religions in the world and nobody thinks the obvious of the fact that if only religion can be correct, then most of the world is fundamentally believing a total lie.

Anyway, the same thing is happening with AI. AI is eroding our identity as software engineers. So you'll see rationalizations in this thread in attempt to protect that identity. The biggest excuse is LLMs are hallucinate and are often wrong and fortunately for humans... this rationalization still works because it's still very true.

However what people are not mentioning is the obvious. People are avoiding it because they are delusional. The topic of this thread is "erosion" of "software engineering career" AND that is utterly true. ADDITIONALLY the error rate of LLMs have been going down. AI in general is improving. The erosion is real and obvious.

But you will see here on this thread that people are not talking about the erosion. They are holding on to the one last rationalization that is a differentiator without ever thinking about how that differentiator is "eroding" even though "erosion" is the LITERAL topic of the conversation.

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.

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.

Good luck out there; we will all need it.

Yes this has been my experience as well.

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

These are the last days of software. Use the AI's and build cool shit NOW.

So instead of a programmer, you become a software designer. I recently came across the idea of building fantasy for the player (in context of games), but now that I think more about it. Onlyfans, is just that. Advertising, Beauty products, novels, games, TV shows, and so on. You're really just creating / selling a fantasy for vast majority of people. Most people will never lose that 30 lbs, but you can sell them all kinds of products to fuel the fantasy of them losing that weight, being beautiful, rich, healthy and so on. So an LLM replacing the need for you to write every piece of code, is actually kind of freeing. You as a a former programmer, should embrace your new creative role. Writing code, at least for me was always slow and tedious. I just want to be able to express the ideas I have, so LLMs just make it possible to build things I never could otherwise.

> But now the market is shaping everyone into becoming a generalist.

This is interesting because in my field of VC everyone says generalists are dying.

Maybe just maybe here in HN we are in an echo chamber that is convincing us that there is a theoretical limit to how far the LLMs can make progress. It’s not unthinkable that LLMs will make better overall architectural decisions or follow the good practices better or understand the problem in bigger picture (more access to company/product context already makes a huge difference)

Lots of jobs have been automated away and careers based on those jobs faded away in history. Maybe in near future there won’t be a ton of opportunities for software engineers in the traditional form. I’m also embracing for that future.

There were people called calculators that did manual calculations in the past. There were people hand weaving all the fabric. There were people painting cars in the factory. All those jobs are gone for the most part.

We are sitting here portending there is going to be demand for software engineers managing those engineer robots but let’s be real. The demand for software is not increasing at the rate software engineering is becoming efficient using those robots. Some (many) of us have to find new careers.

The issue is that the people evaluating you don't know the difference between legit domain expertise and pure bullshit.

computers are made for automation. programmers were always working on automating things, making other things obsolete, and we have been killing jobs for decades. did you really think we would suddenly stop when it's your job? i'm happy this is happening, genuinely giddy

"Except that nobody cares anymore."

:-(

I don't see it as negatively, in that there are specific trade-offs.

For one: LLMs make a lot of mistakes. We all see that when they hallucinate search results and what not. But, possibly even more important than that, you ultimately become dependent on some big company via LLMs. Perhaps that trade-off is worth it for some companies, but I personally don't want to become dependent on these companies. I actually consider it a hostile attack from the USA, and under Trump this is even more obvious.

Another thing that sucks by LLMs is documentation. They generate a lot of crap that is useless. So that's another area where humans could be better.

Admittedly a lot of vibe-coded AI slop is also useful in some ways, but it has started to make me rather angry in general - youtube already spoiled me here. I no longer want to see ANY AI videos at all whatsoever. It just wastes my time. I am not here to empower skynet version 20.2.

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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.