Software engineering may no longer be a lifetime career

> Yes, about 2-5% of the time.

There are also those for whom that percentage is higher, let’s say 6-50%.

> I understand things and then apply my ability to formulate solutions

The AI is coming for that too.

You might just be lucky to be in circumstances that value your contributions or an industry or domain that isn’t well represented in the training data, or problem spaces too complex for AI. Not everyone is, not even the majority of devs.

People knocking out Jira tickets and writing CRUD webapps will end up with their livelihood often taken away. Or bosses will just expect more output for same/less pay, with them having to use AI to keep up.

I dunno, man. I've been doing this for 20+ years and I think we're at a really important fork in the road where there are two possibilities.

The first is that AI is achieving human-level expertise and capability, but since they're now being increasingly trained on their own output they are fighting an uphill battle against model collapse. In that case, perhaps AI is going to just sort of max out at "knowing everything" and maybe agentic coding is just another massive paradigm shift in a long line of technological paradigm shifts and the tooling has changed but total job market collapse is unlikely.

The other possibility is that we're going to continue to see escalating AI capability with regard to context, information retrieval, and most importantly "cognition" (whatever that means). Maybe we overcome the challenges of model collapse. Maybe we figure out better methodologies for training that don't end up just producing a chatbot version of Stack Overflow + Wikipedia + Reddit. Maybe we actually start seeing AI create and not just recreate.

If it's the latter, then I think engineers who think they are going to stay ahead of AI sound an awful lot like saddle makers who said "pffft, these new cars can only go 5 miles per hour."

I normally say that I have zero concerns regarding AI in terms of employment. At most I am concerned in learning the best practices on AI usage to stay on top of things.

It's ability to write code is alright. Sometimes it impresses me, sometimes it leaves me underwhelmed. It certainly can't be left to do things autonomously if you are responsible for its output.

Moderately useful tool, but hellishly expensive when not being subsidized by imbeciles that dream of it undrrmining labor. A fool and his money should be separated anyway.

What I am really concerned about the incoming economic disaster being brewed. I suspect things will get very ugly pretty soon.

Pure wage workers should consider dropping the attitude about how tech progress will just make their inferiors in the same line of work be out of a job (hrmph good riddance etc.). Because this pseudo-progress could creep up on them as well.

Then you won’t have this just world of the deserving workers at all. Just formerly deserving workers and idiot billionaires like Musk (while the robots do all of the work).

Not sure where I first heard this, but I say it to my team all the time: "Programming is thinking, not typing"

What you described are senior developers and system architects.

Junior developers spend most of their time writing code (when they're not forced to attend pointless standups, because Agile/blah/blah)

> The developers who still think their job is about writing code will perhaps not have a job in the future.

So you're saying the same thing everyone else is saying. SWEs won't go away, but they will be greatly reduced, because those whose job is about writing code -- junior devs -- will be replaced.

(How will Sr Devs in the future be created? That's the question, isn't it.)

Only 5% of your time is spent writing code? That sounds like a low estimate for most software engineers I work with.

May I ask if you could estimate how you spend the other 95% of the time?

Saying being a programmer is about writing code is a bit like saying being an artist is about drawing lines on a canvas.

Yeah technically drawing lines on canvases may be an very important part of being a painter, but it is hardly the core of what makes or breaks great art.

Because that classifies in "developers" and "software engineers". And software engineering isn't going to disappear anytime soon

This is a bit of glib answer. Most of the time is spent coding which encompasses typing, retyping, and retyping again. It also includes banging your head against the wall while trying to get one of your rewrites to work against and under-documented API.

OP's formulation makes SWE sound like a purely noble enterprise like mathematics. It's more like an oil rig worker banging on pieces of metal with large hammers to get the drill string put together. They went in with a plan, but the reality didn't agree and they are on a tight schedule.

>- I understand things and then apply my ability to formulate solutions

  - Well, and AI can do part of that too, maybe more of it soon.
  - ...
  - Besides, you don't need 10 guys in a team to do that. A couple of them will do, then AI will do the coding. What will happen to the rest?
  - ...

You don't think AI is going to be able to understand things and apply their ability to formulate solutions better than you, in the near future?

Note that just because you know the job is understanding things, the manager who'll boot you and leave you without income probably doesn't. They'll just get their political cookie points for saving money by replacing you with AI.

I think the future is pretty up in the air in this respect, but my guess is that AI will just lead to another shift in the set of knowledge that a 'real programmer' is expected to have. I'm old enough to remember when people would make fun of web developers for 'programming' using HTML and JavaScript. And of course, back in the day, you couldn't be a real programmer unless you wrote assembly language. In a few years' time, being able to write (as opposed to read) source code in any specific programming language will probably become a niche skill. The next generation will be able to read Python to about the same extent that I can read x86 assembly.

Perceptions of what knowledge counts as 'low level' are constantly shifting. These days, if you write C, you're a low-level, close to the metal programmer. In the 70s, a lot of people made fun of Unix for being implemented in a high-level programming language (i.e. C) rather than assembly.

You’re a ”developer“, i guess, but not a coder (anymore), which is what your interlocutors are probably asking about. You’ve migrated to a middle manager job, not something they probably can just start doing competently. Essentially you’re agreeing with their initial sentiment, that coders will be made irrelevant.

The true argument is about quantity - of people, not code. All qualitative arguments are missing the point.

  - Compilers will make developers irrelevant
  ...
  - Compilers can write assembly language code

  - Compilers have -O3 now

etc...

Maybe we should rejoice. I remember dreading writing documentation, and now I would happily hand that off to AI.

You miss the major factor in your compensation: pricing pressure due to supply/demand.

By removing all the junior engineers, you've fundamentally changed the market forces longer term and most people expect that to negatively impact you in the supply demand curve regardless of whether or not the statements you've made above are true, which they most likely are for senior engineers.

Isn't the long term trend just that we don't need as many engineers, not that there will no more software engineers?

Theres another, different loop I keep seeing which is:

  - Company A lays off engineers citing AI efficiencies
  - People say its because of over hiring during 2020
  - Company B lays off engineers citing AI efficiencies
  - People say its because it was never a good business
  - Company C lays off engineers citing AI efficiencies
  - People say its because theres a recession

I guess to cite a counter example, unemployment is still super low, software jobs are still holding up, but the bear case is that eventually 5% of people will be able to do what people do today, and the demand for software won't grow at the same pace.

And most of the time the statistical aspect of LLMs result in a less creative solution that is more expensive to run and harder to maintain. LLMs at this stage are good at scaffolding, generating the boilerplate you do not want to write and glue things together quickly. It just makes engineers faster.

That doesn't hold because the goal for executives is to increase revenue and the main sales pitch of Anthropic et al is to pay for agents instead of paying for engineers. That means 80% of the workforce is out no matter what. Whether or not one belongs to the remaining 20% is a different story, but obviously not all of us will be there.

> I understand things and then apply my ability to formulate solutions

AI is coming for that too. Don't be naive

I remember being that kid in high school who ran math and logical problems hard which contributed to me being very technical and to learn to push through painful mental challenges on the regular. Out of most of my graduating class there were not many of us that went on to become engineers for a reason because it isn't easy work by any means and I'm guessing is quite draining for people who don't use their brain like we do.

So while AI will change the industry I don't see any reputable company firing the smartest ones in the room for junior level intelligence.

Even with it advancing someone has to be responsible for when it screws up which we know it will.

Something missed in that computer science was a highly theory driven discipline where people were taught how to think critically about solving complex problems. Industry complained they weren’t teaching enough programming skills, so they dumbed down the thinking part and emphasized the vocational part. Now the vocational part is virtually useless, and the grounding of theory applied to complex problems is suddenly really relevant again. Schools will take time to retool their programs, teaching staff, and two generations if not three graduates will have entered into a work environment that doesn’t need what they learned.

As someone 35 years into my career I agree this is the most exciting part of my career. I love programming and I do it all the time but I do it by reading code and course correction and explaining how to think about the problems and herding cats - just like working with a team of 100 engineers. But the engineers I’m working with now by and large listen, don’t snipe me on perf reviews, aren’t hallucinating intent based on hallway conversations with someone else, etc. This team of AI engineers I have can explain to me their work, mistakes, drift, etc without ego and it’s if not always 100% correct it’s at least not maliciously so. It understands me no matter how complex the domain I reach into, in fact it understands the domain better than I do, so instead of spending a few months convincing people with little knowledge or experience that X is a good idea, I can actually discuss X and explore if it’s a good idea or not and make a better informed decision. I’ve learned more in these discussions than I’ve learned in decades of convincing overly egoistic juniors and managers to listen to me about something I’m an industry authority on.

However I see very clearly we will need very few of the team of 100 human engineers I can leave behind in my work. Some of will be there in a decade, but maybe less than 1:10. This is going to be a more brutal time than the Dotcom bust for CS grads, and I don’t think it will ever improve. Mostly because we simply won’t need the “my parents told me this makes money” people, just the passionate folks remain. But even then, we face a situation where the value of any software developed is very low because so much software is being developed. It’s going to turn into YouTube where software that is paid for is very small relative to the quantity of software developed. We already see this in the last few months with the rate of GitHub projects created. If the value of any software created is low, the compensation of the creator will be low unless they’re very rare talents.

> Business owners who think they can do without developers because they think LLMs replace developers are fine by me too. Natural selection will take care of them in due course.

Thing is, natural selection will take care of you at the same time. Because you'll also come to rely on products they make, or services they offer, either directly or indirectly. So eventually, you too, will suffer the consequences of the enshloppification.

This is exactly it. The speed of light has not changed: we're limited by our ability to understand the system, and make decisions about what to do next. AI will speed that up, but the core work is the understanding and decision-making.

Saying otherwise is sort of like reducing the task of writing a novel to typing.

The "apply my ability" is doing a lot of work, so to speak, in the above exchange. Work that might eventually well be automated away.

This is maybe a bit myopic.

Dude - look what happened in the last 2 years on software.

Now project out another 10.

I totally agree with you 'as of now, in the current paradigm'.

But that could very well change.

> Yes, about 2-5% of the time. Less now.

I spent 2nd half of my 30y career fixing organizations and process where this was the case. so many things are wrong in places where this is the case (or alternatively you need a different job title :) )

> Multiple times per week I have the same conversation.

Really? I mean, good on you if it's true and you like the attention but that's sounds like an implausible amount of interest in someone and their relatively mundane profession.

The problem is people think AI can replace the 95-95% that isn't code too. That's where we end up with massive unusable codebases that no one understands.

In my community almost all problems are political. "Problem solving ability" matters if you are HFT, but everything else? Math can't tell you the best way to use land, educate a kid, what to pay for healthcare and how, how to prioritize biotech research, set a minimum wage, decide congressional maps, all sorts of stuff that actually I pay for or care a lot about. in fact I think you are totally misinterpreting what people are saying to you, you are 200% wrong: the 2-3% of your time spent coding was the valuable part, and your so called problem solving ability rarely solved any real problems.

This is a valid perspective, but I don't think a useful one.

Being able to produce code is a huge unlock for many non-programmers. So in a way, it doesn't matter how much time existing developers spend on coding. It's about helping anyone become a developer.

The perspective here is "lifetime career", so you need to project out 30 years here, for a meaningful argument.

I think, much sooner than that, you'll have AI pumping out practically complete implementations that meet the requirements of function, set by the people who desire that function. THOSE people will be the developers, and will be more akin to technical "creatives", more on the product side, than the developer side.

If you’re a developer and you’re writing code 2% of your time pre-Claude, that’s 9 minutes a day, you will and should be fired.

This answer makes two big assumptions that haven't been proven out yet.

- Understanding code without writing it is as viable as understanding code that you've worked with directly or indirectly

- Businesses care that you understand code

I really doubt the first one. Traditionally, understanding a code base in large part came from working with it intimately and building that muscle memory. The idea that understanding code by reading it is as good as understanding it from writing it, in my opinion, is not realistic.

Whether businesses care that their engineers (which they are increasingly viewing as monkeys at LLM typewriters) to understand the code remains to be seen. I don't think they particularly care whether their code runs slow and is buggy so long as it works just enough to churn out features and continue to pull income.

This an example of survivor bias dressed up as general advice that doesn't consider the entire ecosystem. And we need look no further than what's happened in Hollywood with writing in particular.

The general progression of a Hollywood writing career is from PA (production assistant), which often starts off as a volunteer "intern" position, to writer's assistant. Assistant here usually means doing any meanial task anyone wants from fetching drycleaning to taking a dog for a grooming appointment. When you're a writer's assistant, you will oten spend time in a writer's room. You will see how the process works. You probably won't contribute anything but you may get feedback on tehings you've written from whomever you're working for.

The next step is as a staff writer. You will be paid to produce scripts and stories for a TV show, for example. That writer's room will have a head writer. On a TV show the head writer is almost always the showrunner. The showrunner is effectively the leader of the entire project and is responsible for breaking up a season intoo storylines and making sure those scripts make sense as a collective. They might one or more of those scripts or maybe not. The showrunner will hire directors for each episode.

The path from staff writer to showrunner often goes through being a producer. Producers are responsible for a lot of the logistics of filming a show. Hiring extras, finding locations, coordinating stunts and costumes and making sure the director has everything they need.

As part of all this, in the 22 episode TV era, writers would often end up spending time on set while the show is being filmed. They'd learn from the process.

Every part of this was necessary. Those writers on set are your future producers and showrunners.

So what's happened in the streaming era is that writer's rooms got smaller (so-called "mini writer's rooms"), maybe only the showrunner is ever on set, the writers have stopped working by the time filming even begins and you might only be doing 8-12 episodes. On a 22 eipside season, that one job could support you. 8-12 episodes can't.

But you see how this all breaks down when writers can no longer support themselves, they're no longer being trained to be future producers and showrunners, there's no feedback from set back to the writer's room and you end up with 3 year gaps between seasons. The only reason for all of this is because it's cheaper.

So, you may be a staff engineer who tech leads dozens of other engineers. You're not formally a manager or director but you have a lot of influence about the entire project. But how did you get there? You started as a junior engineer being told what to do. You got to see how other leaders operated. You became responsible for more and more things. You might start fixing bugs under supervision to managing a feature then an entire project and so on.

So what's going to happen here is (IMHO) we will have years of the software engineer space shrinking. There'll be very little entry-level hiring. Layoffs will reduce the entire workforce and there'll be a few tech leaders who hang on because they still produce value. Some of them will probably discover they don't produce enough value and they'll go too.

But where do the future tech leaders come from in this scenario? AI is being used as an excuse to kill the entry-level pipeline and if you go around and say "git gud" [sic] then I'm sorry but you just don't understand the impact of what's happening or you don't care because, at least for now, you're simply not affected.

You see the same thing with people who espouse the myth of meritocracy. Well, if a given workforce shrinks by 50%, half those people are, by definition, not going to survive. An individual may be about to reskill or skill up to survive but not everyone can. And that's how people end up in Amazon warehouses. At least until they're no longer needed there ether.

I agree in principle, but I think the 2-5% estimate is extremely low. I could be sold on most developers spending ~25%, up to 40% of their time on code. But very few people are spending 2% of their time on it. Unless you're some sort of super senior staff / advisor to the CTO at a gigantic company, which has already placed you on rare terrain.

Usually that means you're already a senior developer, understanding things and formulating solutions is part of work delegation.

Now those juniors whose job is to implement those solutions, they will have a hard time.

On my 50s, I also don't write as much code as I used to, even less nowadays with serverless, managed services, low code/no code tools, agent orchestration workflows, and with it I keep seeing development teams getting smaller.

Yeah coding speed was almost never the bottleneck I found. AI now does the typing and (some) of the thinking. It doesn’t figure out what needs to be built and how it all plays together (yet).

Anyone read posts like this and picture someone who doesn’t actually do anything all day besides posture in meetings? Probably with a super inflated title and salary.

I doubt this is what the OP does, but there’s tons of developers like what I described and they seem actively proud at not actually building anything and playing politics all day.

> I'm getting old and I value my remaining time on the planet.

It's an interesting sentiment. I, too, am getting old and value my remaining time on the planet, and so I code by hand every chance I get. :) Luckily I'm in a position to be able to do that.

We switched to 'software engineer' to encapsulate that, I think. You can receive requirements and churn out code or you can go up a level and think about the solution. Go another level up and think about the problem. Another level and it's the context of the problem. Further than that and it's the priority of it. And even higher up is how it fits in the product roadmap and the architectural decisions.

At some point you stop developing and start weighing up the requirement against your understanding of the system and the environment it works in.

There's an old Chemistry joke, that I've reapplied to Software Engineering, and it goes something like:

A New Engineer (NE) shows up on their first day on the job, notebook in hand ready to learn. They get assigned to shadow an Experienced Engineer (EE) for their first day.

EE: Now, the thing is, for any project on our team, you only need to change about 3 lines of code. NE, preparing to write down notes: Which 3? EE: Well, it depends.

(Originally about Material Safety Data Sheets, and there only being 3 relevant lines on them).

I think this is what people miss about Software Development.

On one of my very first jobs in around 2000 I got paired with a much more experienced software engineer. He’d been a pro since the early 70s. I was stoked to learn from him.

On like my fourth day he said “now I’m going to teach you the thing that helped me the most in my career…” I waited, ready for the received wisdom. And he said “always number your punch cards so if you drop them they will be easy to put back into order”. I was upset. We were long past the point where punch cards were in use. And then he said “I said what would help _me_ the most, not what would help _you_. Software is always changing”.

I’ve thought about that a lot lately.

LLMs also can “understand things and apply their ability to formulate solutions”. There is nothing that will inherently limit AI from doing all knowledge work (and all physical work once robotics is good enough).

Of course developers could just move up the “next level of abstraction” and become managers of agents who write the code, but eventually AI becomes a better manager of agents than even the best humans, at which point there is no contribution a human can make that an AI model or system of models couldn’t do better.

I think similarly. To me value of the "programmer" is not "I love Rust", "I am React expert" etc. That "love" is for sure replaceable.

Engineering in a nut shell... What did we do before computers??? Halls full of draftsmen...

> Natural selection will take care of them in due course

Wonderful articulation. There's a plethora of prognostication about how AI will change everything in software and beyond and the thing I keep thinking is, well, when will the talk stop and the demonstration of results commence. It doesn't seem to have as yet.

If it works, it'll work. The methods will spread and quickly be accessible to everyone, and progress will go on. That's great.

If it doesn't work, we'll also see that in the absence of real results. And simply stating you are seeing it doesn't qualify. It must be something we can all see and use that is unavoidably, undeniably real.

> Natural selection will take care of them in due course.

or you.

Well said, the only flaw is the unfortunate realization that "I understand things and then apply my ability to formulate solutions" is rarely required, how many zombie corps are still roaming these days?

Judging by how many day to day tech products in my life are buggy, slow or user-hostile there can't be more than 50-100 tech companies actually innovating, right?

I had a professor at my CS university (one of the greatest I had) who used to say (in 2008): "a developer should write no more than 5 lines of code a day"

> Natural selection will take care of them in due course.

While you are seemingly not at the moment, some day you might be at the receiving end of that "natural selection" in ways that seriously impact your remainint time on the planet.

In that case you might reconsider your stance, and especially question how natural is the selection of a few powerful rich people depriving others of their way to earn a living and their way to draw meaning from their lives.

The AI revolution keeps getting compared to the industrial revolution, but people keep forgetting the consequences of that one.

10% writing code. 90% reading and understanding code

This is a bit of a strawman. When people say "writing code", they don't necessarily mean [pressing the keys on the keyboard that produces the necessary bytes in a text file].

I agree in some ways, but I think this also overlooks that your job might be like that, but most decidedly “developer” jobs are not all like what you say which is more Engineering. Many people are able to have a career making basic HTML website changes. Are they not developers? Will their job not potentially be replaced by an AI that can make that change in seconds?

It’s weird that people always seem to argue the extremes when reality is jumbled mess in the middle. Will developers lose jobs to AI? Without question. Will many “developer” jobs be eliminated because of that? Without question. Is it probably a really bad time to think you can go from your retail job to fixing people’s website as a lifetime career move? Yeah, probably not the best idea. Would it be smarter to focus on becoming a “Software Engineer” instead of a “Developer”? Yes usually. Does that mean it is a bad idea for EVERYONE to choose to become of developer? No, and that would be a dumb thing to argue.

We’re still going to need developers and definitely engineers, we are just going to need less of them in their current form, just like we needed less saddle makers, farriers and blacksmiths. We didn’t stop needing Horse Mechanics, we just needed less of them because we needed Car Mechanics. Some of those skills transferred, some didn’t.

> The developers who still think their job is about writing code will perhaps not have a job in the future.

The Jira ticket munchers represent a good chunk (if not, most) of the workforce in case you haven't noticed.

Also, just because you will still have a job somewhere not too far from a codebase, it doesn't mean that it will be a worth job having. Think how awful human made legacy codebases can be. Now imagine a codebase 100x bigger without the human friction of generating code (think of all the execution paths that will never be hit but will neverthless be there in big quantities increasing the time you need to understand the codebase). Now imagine that most jobs involve dealing with such codebases.

Good look, keeping your dev job and spending the rest of your career trying to understand AI generated codebases.

But when a senior can do the job of 6 coworkers, what do you suppose will happen to the coworkers?

In farming, those who were replaced by tractors did not keep their jobs. What is different now?

For me - I'm 43, and used to be an extremely productive Java/Swing developer after 15 years of experience, and I knew all my tools inside and out. But I no longer work at that company (which doesn't exist any more), and it takes me a lot longer to learn how to be effective with the new tools I'm using simply because I haven't had a decade to learn the ins and outs of the new environments I'm working with.

So AI saves me immense amounts of time figuring out how to write proper syntax, remembering the ins and outs of unit testing frameworks, etc. If I stick around for a year or three I'm sure I'll get much much faster and learn these tools better.

Stop with the anthropomorphizing, stop playing house. There is no team of agents, they are just tools and processes running in a computer for Christ’s sake. Blow away that one senior engineer and you have nothing. Better to have a team of 6.

> Part of the practical degradation of traditional programmers over time has always been concentration and deep calculation, just like in chess.

I don't know if I agree that this is the bottleneck.

What I can agree on is that as I have aged I now simply REFUSE to learn programming knowledge that has a half-life.

Phone programming? Nope. Front-end web programming framework? Oh, hell, no. Build system of the month? Piss right off. etc.

AI lets me fill in that kind of programming with "acceptable" (read: super crappy but I didn't have to think about it) results because that code won't exist in 5 years anyway due to its half-life.

> The senior that before could lead a team of 6 is now leading a team of agents

you just confirmed the point that the author is making in the article:

the team of 6 is no longer needed,

and, logically, is therefore eliminated by the company

So yes, SWE still exists as a career for some, but their numbers might be reduced by 85%.

> Part of the practical degradation of traditional programmers over time has always been concentration and deep calculation, just like in chess.

Fortunately SWEs have the architect path, which frequently rewards having lots of deep intuition even as the details of calculation continue to change. So one question that's urgent but unknowable until we get there is.. are we going to get good architects if they don't come up through the trenches? I'm not sure. All I know is that everyone has a war story about the least qualified ones that got the role without that experience.

Since intuition is what LLMs do more than calculation, it's worth mentioning that this is true but different. They have the collective unconscious of the internet, which isn't taste that comes from good/bad experience. Besides intuition what comes to mind is "good taste".. the actual foundation of good review and really the main job of senior positions in any technical field.

> The senior that before could lead a team of 6 is now leading a team of agents, and reviewing their code just as before.

I don't see this in practice. Senior engineers can prompt Claude just as fast as junior engineers can. Claude can debug broken code at roughly the same speed regardless of who's pressing Enter.

In fact, I've basically stopped using agents for most of my work. It's far more valuable for me to help the junior engineers develop a better sense of what's good and right, than it is for me to sit and review Claude commits all day.

> My mom is a (US public school) high school teacher, and she vents to me about the number of students who just take “Google AI overview” as an absolute source of truth.

I notice many of the adults in my life are doing this now as well.

> Professionally, I see people largely falling into two camps: those that augment their reasoning with AI, and those that replace their reasoning with AI. I’m not too worried about the former, it’s the latter for whom I’m worried.

Related recent article posted on HN - https://news.ycombinator.com/item?id=47913650

I work with people who generate solutions without really looking at what was produced (group A). They click around the app or run some tests and decide if they're content with the result, then ship it. You can see Claude's fingerprints all over the PR and it's safe to assume they didn't change much of anything.

Then I have coworkers who work through the problems, build harnesses to test the changes and verify results, work through multiple solutions, synthesize ideal outcomes into a single one, benchmark, refine, test the result thoroughly, and provide sane verification processes in the PR. This is group B.

They're entirely different versions of using AI. One seems passable for now (look how fast we're going!), and the other is arguably a new version of what's possible (in a given time frame at least) and defines a totally new normal for software engineering that I virtually never saw outside of exceptionally professional contexts. You don't move as quickly as group A, but you still move faster and produce better software than most people have in virtually every company I've worked for.

I see group A being totally pushed out of the field fairly quickly. LLMs let you work incredibly effectively if you care to learn how. That kind of rigor is going to be the default (group B), and might become the only way humans can still be a useful component in the loop. Group A is likely to become replaceable with frontier models before very long.

Honestly, AI doesn't feel like it's affecting hiring needs from the trenches. We don't have engineers sitting on their hands because AI wrote up everything the leadership could imagine.

Instead, we get an economy that feels like it's on the cusp of a fall or at the very least a roller coaster. Poor tax incentives to hire. ZIRP is long gone. And the hiring managers are overrun with slop.

But bosses are happy to say it's AI because that makes you sound in control.

> Anecdotally, it feels like something materially changed in the US software hiring market at the start of this year to me. It feels like more and more businesses are taking a wait and see approach to avoid over-investing in human capital in the next few years.

My guess is companies overhired in COVID and between that experience and an uncertain market they don't want to make the same mistake twice.

Anecdotally as well, but I believe that US companies are hiring in big waves in India and other developing markets. I know people who went from zero contacts to daily messages from big tech recruiters in these countries. I've seen people saying that is the result of that specific US section that expired last year, but I'm a layman, so I don't have the knowledge to debate the reasons.

every time a person uses the abstraction argument, an angel dies

People always say this but it’s misguided imo. Yes LLMs are not deterministic, but that’s totally irrelevant. You aren’t executing the LLMs output directly, you’re using the LLM to produce an artefact once that is then executed deterministically. A spec gets turned into code once. Editing the spec can cause the code to be updated but it’s not recreating the whole program each time, so why does determinism matter?

LLM's don't have to achieve perfect reliability to replace lots of work. They just have to reach the balance of reliability and cost suitable for a given task. This will depend on the task.

I grant that there's a definition of abstraction that LLMs don't fall into. But people describing LLMs as another abstraction layer aren't all misunderstanding this. Instead, they are using the term ... more abstractly.

EG: How did Mark Zuckerberg make software five years ago?

He's as capable of opening up an editor as I am, but circumstance had offered him a different interface in terms of human resources. Instead of the editor, he interacts with those humans, who produced the software. This layer between him and the built systems is an abstraction, deterministic or not.

Today, you and I have a broader delegation mandate over many tasks than we did a few years ago.

I see what you're getting at, but determinism isn't the right word either. LLMs are fundamentally deterministic -- they are pure functions which output text as a function of the input text and the network parameters[1]. Depending on your views on free will, it could be effectively argued that humans are deterministic as well.

The concept you're touching on is the idea that LLMs (and humans) are functions which are inscrutable. Their behavior cannot be distilled into a series of logical steps that you can fit in your head, there are no invariants which neatly decompose their complexity into a few interpretable states, and the input and output spaces are unstructured, ambiguous, underspecified, and essentially infinite. This makes them just about impossible to reason about or compose using the same strategies and analysis we apply to traditional programs.

[1] Optionally, they can take in a source of entropy to add nondeterminism, but this is not essential. If LLM providers all fixed their prng seeds to a static value, hardly anyone would notice. I can't imagine there are many workflows which feed an LLM the exact same prompt multiple times and rely on the output having some statistical distribution. In fact, even if you wanted this you may just end up getting a cached response.

There's something to be said about the fact that the very people who would use deterministic layers to build stuff are... non-deterministic. We, as humans, have our set of pros and cons, wins and failures. Even the most brilliant coders on earth will make mistakes from time to time. I often fail to see this getting accounted in any conversation when there is a critique towards LLMs, as if we humans are not flawed in our own ways, with a huge degree of variance across individuals. Good and bad code existed prior to LLMs. If you're hiring someone to do code, you're basically using some heuristics to trust this person will do a good job. But nothing is ever guaranteed 100% deterministically ever. Without thinking it that much, LLMs will sometimes produce better code and manage systems that some people who are earning salaries out there. Possibly sub-par developers if we were precise, but professionals in the meaning of the word (that are being paid to do work).

At the end of the day, what matters is how willing the person behind a given task is when it comes to deliver quality work, how transparent and honest they are, to understand requirements, and a pleasure to work with along other humans. AI/LLMs are just extra tools for them. As crazy as it might sound, but not so many people are willing to push boundaries and deliver great work. That is what makes the difference.

Are other layers truly deterministic though? Do I know for sure whether that object has been garbage collected or not? How many cycles this instruction will take to run?

> However, I never read what those careers are or who is going to pay for retraining.

There aren't any careers and if there were, you would have to pay. Corporations certainly won't except under extremely rare situations where they have to to compete.

The same is true of the industries that software disrupted.

The argument is that “that’s what always happened in the past”.

Which is true, but it’s true as long as it’s not true.

The classic example of how drastically this kind of thinking can fail is Malthusian theory, that populations would collapse because food growth was linear while population growth was exponential. This was true for all of history until Malthus actually made this observation.

At a mechanistic level, the “we have always found other jobs” argument misses that the reason we’ve always found other jobs is because humans have always had an intelligence advantage over automation. Even something as mechanical as human inputs in an assembly line was eventually dependent on the human ability to make tiny, often imperceptibly, adjustments that a robot couldn’t.

But if something approximating AGI does work out, human labor has absolutely no advantage over automation so it’s not clear why the past “automation has created more human jobs” logic should continue.

It's not going to happen, just as it didn't happen for skilled industrial workers whose jobs got outsourced to China. The government will pay just enough in welfare to keep the situation manageable. Then they'll demonize you in the culture, as a Luddite, etc.

The second part seems obvious to me: the ones who are getting retrained. If it's some kind of formal education, depending where you are, maybe the state at least for part of it.

Education in what, though? No idea. And if there was one answer, and it's true that there will be fewer software developers, you'd likely be competing with many people for few jobs.

At least in the US, the only major non-AI growth field seems to be healthcare to deal with the swell of baby boomers living longer than people have before.

But if we're waiting to be paid to retrain there, I wouldn't hold our collective breath.

This is the story that's been written since the Luddite revolts, as far as I know. The successors in that case were the capitalists who spent a significant amount of time and money convincing the constabulary and political figures to side with them. People were shot and jailed in the worst cases. The best case, workers were left without work or sent off to work-houses where they became indentured servants to the state.

The last work-house closed in the 1930s.

That all started not because people were afraid jobs were going to be replaced by the new loom. People had been using looms for centuries. They were protesting working conditions: low wages, lack of social protections when people were let go, child labor, work houses, etc. There were no labor laws at the time to protect workers... but there were these valuable new machines that the capital owners valued greatly. The machines were destroyed as leverage: a threat.

Since the capitalists ultimately "won" that conflict it has been written, by technocrats, that technological progress is virtuous and that while workers will initially be displaced the benefit to society will be enough such that those displaced will find productive work else where.

But I think even capitalist economists such as Keynes found the idea a bit preposterous. He wrote about how the gains in productivity from technological advances aren't being distributed back to workers: we're not working less, we're working more than ever. While it isn't about displacement of workers, it is displacement of value and that tends to go hand in hand.

I think asking, "Where do I go?" is a valid question. One that workers have been trying to ask since the Luddites at least. Unfortunately I think it's one that gets brushed under the rug. There doesn't seem to be much political will to provide systems that would make losing a job a non-issue and work optional.

That would give us the most leverage. If I didn't have to work in order to live I could leave a job or get displaced by the latest technological advancement. But I could retrain into anything I wanted and rejoin the work force when I was good and ready. I wouldn't have to risk losing my house, skipping meals, live without insurance, etc.

The most future-proof “career” right now is having money. At least multiple million dollars. That’s a skill that is very much in demand.

Also, it's not necessarily true that there will be other great careers available. This seems to just be an assumption people are making.

Of course, there are jobs that will still require human labour for some time yet, but in reality a lot jobs that require physical human labour are now done in other parts of the world where labour is cheaper.

Those which cannot be exported like plumbing or waitressing only have limited demand. You can't take 50% of the current white-collar workforce and dump them in these careers and expect them to easily find work or receive a decent wage. The demand simply does not exist.

Additionally, at the same time as white-collar jobs are being lost an increasing number of "low-skill" manual labour jobs are also being automated. Self-checkout machines mean it's harder to get work in retail, robotaxis and drone delivery will make it harder harder to find work in delivery and logistics, robots in warehouses will make it harder to find warehouse jobs.

It seems to me there is an implicate assumption that AI will either create a bunch of new well-paid jobs that employers need humans for (which means AI cannot do them) and jobs which cannot be exported abroad for cheaper. What well-paid jobs would even fit the category of being immune to AI and immune to outsourcing? Are we all going to be really well paid cleaners or something? It makes no sense.

A lot of the advice we're seeing today about retraining in construction worker or plumber seems to assume that there's an unlimited demand for this labour which there simply is not. And even if hypothetically there was about to be a huge increase in demand for construction workers, it would take years to even have the machinery, supply chain and infrastructure in place to support the millions of people entering construction.

The most likely scenario is that people will lose their jobs and will be stuck in an endless race to the bottom fighting for the limited number of jobs that are left in the domestic economy while everything else is either outsourced or done by robots and AI.

The better advice is to start preparing for this reality. Do not assume the government will or can protect you. When wealth concentrates corruption because almost inevitable and politicians have families to look after too.

Please take this seriously. Even if I'm wrong it's better to prepare for the worse rather than to assume everything will be find and you'll be able to retrain into a new well-paid career.

I think the idea of being an employee is fundamentally changing. Not saying its good or bad but it's shifting to a more entrepreneurial phase where people have to step out of their 9 to 5s and find ways to deliver value that others want to pay for.

We saw this pre-ai with uber and door dash. I think as AI automation dies down and most companies are competing at a near optimal level with the new tools we'll need humans again in more traditional roles to build the next generation of innovations. And then the whole cycle will repeat.

Yeah, that's just a copium answer from people who simply want to hand wave away the issue instead of admitting they have no good answers.

Like a politician who's asked about this in a town hall, but thinks that "our plan is to do absolutely nothing" doesn't sound very appealing.

AI cannot create art by itself.

> I never read what those careers are

Exactly. I have yet to read a single logically sound argument that even gives a hint of what those professions/jobs might be (remember, they have to be plentiful enough to employ large numbers of people, so "I quit my corporate job and making more as a TikTok influencer" doesn't count). Remember that a new profession has to open up new hitherto unknown revenue streams otherwise there are no companies who will pay you.

Software developers are more architechs than plain programmers. You wouldn't make an architech lift heavy things, you want they to design how those heavy things are used.

Also worth noting that, so long as it's reasonable, lifting heavy objects makes you stronger, whereas the current hypothesis on using AI is approximately the opposite.

why is the LLM-compiler analogy flawed? Is it only because LLM output is non deterministic?

My concern would be whether creating that software pays enough to keep up with skyrocketing costs of living. In the past, the jobs created by automation have generally been lower paid with less autonomy.

We are experiencing what Civil Engineers experienced going from slide rules to calculators. Or electrical engineers going from manual circuit path drawing to CAD tools.

The interesting thing to me is that, Software Engineering will have to evolve. Processes and tools will have to evolve, as they had evolved through the years.

When I was finishing university in 2004, we learned about the "crisis of software " time, the Cascade development process and how new "iterative methods" were starting.

We learned about how spaghetti code gave way to Pascal/C structured prpgramming, which gave way to OOP.

Engineering methods also evolved, with UML being one infamous language, but also formal methods such as Z language for formal verification; or ABC or cyclomatic complexity measurements of software complexity.

Which brings me to Today: Now that computers are writing MOST of the code; the value of current languages and software dev processes is decreasing. Programming Languages are made for people (otherwise we would continue writing in Assembler). So now we have to change the abstractions we use to communicate our intent to the computers, and to verify that the final instructions are doing what we wanted.

I'm very interested to see these new abstractions. I even believe that, given that all the small details of coding will be fully automated, MAYBE we will finally see more Engineering (real engineering) Rigor in the Software Engineering profession. Even if there still will be coders, the same way there are non-engineers building and modifying houses (common in Mexico at least)

s/software engineer/secretary/

s/creating software/typing correspondence/

In a world where software programming/architecting is solved by AI, value will accrue to people with expertise in other domains (who have now been granted the power of 1000 expert developers), not the people whose skillsets have been made redundant by better, faster and cheaper AI tools.

In 2020, there are two companies that are competitors with each other. They each employ 100 programmers to do their job, and we all know how those organizations operated; perpetually behind, each feature added generating yet more possible future features, we've all lived it and are still largely living it today.

In 2026, both companies decide that AI can accelerate their developers by a factor of 10x. I'm not asserting that's reality, it's just a nice round number.

Company 1 fires 90 of their programmers and does the same work with 10.

Company 2 keeps all their programmers and does ten times the work they used to do, and maybe ends up hiring more.

Who wins in the market?

Of course the answer is "it depends" because it always is but I would say the winning space for Company 1 is substantially smaller than Company 2. They need a very precise combination of market circumstances. One that is not so precise that it doesn't exist, but it's a risky bet that you're in one of the exceptions.

In the time when the acceleration is occurring and we haven't settled in to the new reality yet the Company 1 answer seems superficially appealing to the bean counters, but it only takes one defector in a given market to go with Company 2's solution to force the entire rest of their industry to follow suit to compete properly.

The value generation by one programmer that can be possibly captured by that programmer's salary is probably not going down in the medium and long term either.

Except we are now in the golden age where people with 20 or 30 years of experience know what quality software is - or at least what it is not. So they are able to steer the LLMs. Once this knowledge is gone - the quality could go downhill.

There will be more software in the same way there is more agricultural output today.

The idea that productivity gains which result in more of something being produced also create more demand for labour to produce that thing is more often wrong that true as far as I can tell. In fact, it's quite hard to point to any historical examples of this happening. In general labour demand significantly decreases when productivity significantly increases and typically people need to retrain.

Creating more software does not solve anything if that software is mostly a functional duplicate of other software. Or, in other words, all companies re-invent the wheel many times over. It doesn't matter if you 10x the development of software that brings nothing new besides being written in a shiny new framework.

We should, IMHO, start getting rid of most software. Go back to basics: what do you need, make that better, make it complete. Finish a piece of software for once.

He just means: by this age you've probably found your preferred title and level, unless you want to rise to more C-level / executive positions, which are rarer in any case and most folks don't want.

It's about increasingly being unable to "keep up", as time goes on, not about aging per se.

In the athlete analogy it's the body that's slowing down. In the AI-powered development world, it's the development that's speeding up.

> Haven't most people looked around and asked themselves where are all the 50+ engineers? They basically don't exist in large numbers.

I'm not discounting ageism in the industry, but how popular of a career was it 30+ years ago compared to now?

If you are lucky and got in early, then probably yes, it could be a lifetime career. It's like all careers, when you joined early, you got a lot of opportunities, you also rode the wave, you eventually rose to the top if you grit through.

It's a lot easier to be early than to be smart or quick.

Managers are being slammed - FB, Amazon and recently Cloudflare and Coinbase.

New grads are being slammed, "because LLMs can do that work."

No new folks, no managers, and no olds. What a delightful career we've chosen for ourselves.

I think you missed the part where there were much much less software devs/engineers earlier.

Year after year it was just much more new people joining as things got easier and more accessible.

Now you see 40 or 50 year olds far and between where most guys I see are in their 30s. Ones that are 60 yo diluted in the sea of new entrants.

Ageism didn't came from the top it just happened with flood of young employees, there is just social dynamics where you might get 40yo not being a manager getting along with bunch of 25yolds but that's going to be an exception not the rule.

Every 5 years on average since the late 90s the industry has doubled in size. Add in natural attrition (and the other things you mentioned, ageism, management or other tech adjecent careers, etc.), and even accounting for a modest number of "second career devs" starting later in life rather than out of college, you still have an industry that skews younger simply by virtue of overall growth patterns.

I think that is significantly overlooked when people ask "where are the 50+ engineers?".

I'm a 57-year-old engineer still going strong, and I know plenty of others. This job isn't conceptually that hard if you have the experience to break problems into manageable chunks. I probably can't juggle as many things in my head as when I was 25 and proudly cranking out spaghetti code. But experience makes up for a lot of that.

Now, would I relish looking for a programmer job right now at my age? Hell no.

This happens whenever a disruptive technology is introduced to a field and I will never get over the irony of a software engineer (in a profession whose entire goal is to automate tasks) not noticing the hypocrisy.

It can be incredibly difficult to find opportunities like that

This viewpoint is curdling rapidly. The definition of "reasoning" and "intelligence" will be debated for ages by philosophers and cognitive scientists, but whatever type of logical/critical thinking is going on in the heads of software engineers and mathematicians, frontier LLMs can now emulate to a very high degree. For mathematics in particular, examples like the following will become common place:

https://gowers.wordpress.com/2026/05/08/a-recent-experience-...

My exprience has been that companies actively work to prevent people from becoming more than just code jockeys. For example, most of the places I've worked have viewed code delivered as the ONLY metric used to evaluate performance. Attempts to contribute to roadmaps or strategy are ignored at best and punished at worst.

If AI becomes good enough to easily produce maintainable and high quality software, then I really can't see how demand for software engineers would not plummet. Even lots of non-coding work that software engineers do, such as accurately capturing what client actually wants, will become much less valuable - e.g. currently misunderstanding of client's requirements is catastrophic and can lead to waste of months of labour; with AI it could become matter of max few hours lost. So I can understand argument that software engineering careers might be safe because AI may plateau and we might never reach level where it's actually capable of producing good software. But I absolutely don't buy that software engineering will be safe even if such AI exists. Even if your current work is just 20% actually coding, you must remember about second order effects that will take place once quality code generation is 1000 times faster.

AI can also do alignment and pull from its vast training dataset for design and "thinking" -- because 99% of the problems in this world were already solved, multiple times, maybe not in the exactly same format, but in a very similar format.

I also see that in the future humans will adapt to AI, instead of the opposite. Why? Because it's a lot easier for humans to adapt to AI, than the opposite. It's already happening -- why do companies ask their employees to write complete documentation for AI to consume? This is what I called "Adaption".

I can also imagine that in the near future, when employment plummets, when basic income become general, when governments build massive condos for social housing -- everything new will be required to adapt to AI. The roads, the buildings, everything physical is going to be built with ease-of-navigation by AI in consideration. We don't need a Gen AI -- that is too expensive and too long term for the Capitalist class to consider. We only need a bunch of AI agents and robots coordinated in an environment that is friendly to them.

This can’t be sustainable, there must be a limit in human biology as to how complex jobs we can handle. More and more people will fall under that threshold.

It's not different. If you haven't already, read "Extraordinary Popular Delusions and The Madness of Crowds".

Imagine AI had never happened, but you had set a personal goal to write your last line of code in exactly five years. You can manage coders, you can write a novel about coding, you can run a yoga school for coders. You just can't code anymore. What do you do?

I know nothing about professional sports other than what I learned from Jerry Maguire, in which Rod Tidwell says "I got a shelf life of ten years, tops. My next contract's gotta bring me the dollars that'll last me and mine a long time. Shit, I'm out of this sport in 5 years. What's my family gonna live on? Huh?" That's the sentiment.

I think you need to read the studies linked in the footnotes. This is a well-studied issued.

You're misrepresenting the potential problem. It's more along the lines of using AI stops you exercising the cognitive processes you would doing things yourself and those encompass skills, knowledge and brain function that can atrophy. For an extreme example you can look at cognitive decline in the elderly which can be mitigated by taking part in activities that are cognitively stimulating.

Pretty much every study says so, so I guess?

You can definitely feel it when you talk against an AI vs doing the churn yourself. It's comfortable, simple, it doesn't aggravate you.

If you constantly pawn a task or cognitive load onto someone else (AI or not), you'll eventually get worse and worse at that particular type of thinking. Your overall mind doesn't necessarily get weaker, but you definitely start to get worse at anything you don't regularly practice.

Easy, I made the switch in my 30s, now I manage software engineers :)

Software engineering isn't a tool, it's the task.

> No carpenter is a specialist in drills.

There's no category difference between being an expert in carpentry vs masonry and being an expert in drills vs hammers. They are both just areas of expertise.

Going down the path of trying to define what is expert functions and what is "merely" a tool using anything but descriptive technique is nonsense.

Expert functions are just those areas where using a tool is sufficiently difficult to require expertise.

I kind of disagree. You are describing a kind person who is extremely valuable, a person who is proficient in SWE but also has domain specific skills in some niche.

That's great, but its nowhere near the norm, and people have been doing generalist software engineering for decades. There has been a sufficient amount of work for a long time to be performed by generalists that it has been a very reasonable career.

IMO AI is the first thing that has ever actually challenged that.

Software is wood, not drills, and if we somehow invented bacteria that gradually built an ugly but saleable house when fed on water and nutrients and nudged into shape, I bet carpenters (well, framers or whatever they're called in the US) would have an identity crisis too.

It most certainly was a lifelong career.

I’m kind of confused how you might think it wasn’t. Going through a career as a software dev until retirement was very common.

Software engineers didn’t just disappear after age 40.

I think the logical next step is that "XYZ knowledge worker" will become a software engineer of sorts. Not literally writing code, but at minimum encoding processes/workflows into some language.

If you're a paralegal or an accountant who can't manage their workflows with AI, you're going to be way less productive than someone who can.

And if you're a paralegal or an accountant who can manage a lot of your workflows with AI, you don't need custom software (hence less dedicated software engineers).

Id disagree with this analogy: "No carpenter is a specialist in drills." and i think its an interesting lens through which to look at the evolution of our tools.

I think there are trades where tool (or process if i may be allowed to extend the analogy) specialists exist and are highly valued. My dad is a plumber, so ill use that example but id trust similar is true for carpentry. there are specialists by task/output (new construction, repairs, boilers etc) but also tool specialist plumbers and companies for example drain clearing equipment or certain kinds of pipe for handling chemicals other than water are very specialised, and there are roles for them because the thing they enable, and the criticality of the task, and often the cost and complexity of using the tool are high enough to make specialisation valuable.

IMO software has, for the 10 years ive been working in it, been in an unusual position where the tools (languages, engineering practices, tech stacks) were super technical and involved, but also could be applied to a large number of problems. That is the perfect recipe for tool specialists: complex tool with high value and broad domain/problem space applicability.

Because of that tool specialisation, we've separated the application of the tool to a problem/domain from the tool use. reduction of complexity of applying these tools to many problems, means all domain specialists will use them, relying less on tool specialists.

imaging a mcguffin tool for attaching any two materials together, but which took a degree to figure out (loose hyperbole here), that sudenly you could use for 5 bucks and a quick glance at the first page of the manual. An industry that used to have lots of mcguffin engineers, would be mega disrupted, and you could argue that those tool specialists would have to identify more with what they were building than the mcguffin they were using.

I tell my boys (both in HS now), the combination of a specialized skill/knowledge + competent computer programming is the sweet spot. For example, my oldest wants to go into Petroleum Engineering which is great but I told him to still learn software development and get comfortable solving problems with code. Having specialized Petroleum Engineering knowledge combined with being a competent software developer is a powerful combination.

I don’t have anything to add to your comment, but I have no means to bookmark it either other than by replying. You’ve put into words exactly what I think.

> People need to hear that startup success is maximal when the founders are older, not younger. VCs chasing youth are statistics deniers.

For building a successful business, older founders are more likely to succeed. They understand the business and see something that everybody else is getting wrong that they can correct and make money on. They will grind at it and have a profitable business for decades.

This is anathema to VCs.

VC's want a short term lottery ticket. They want your business to go big or go home. They would rather see your business fail quickly than grind profitably for a decade. Youth feeds into this in two ways. First, youth can align with the fad of the moment in the hopes of running a cashout while the iron is hot. Second, youth can be bullied into doing stupid things that a more experienced person will flat out tell you are stupid and refuse to do them.

This is the standard misalignment with founders and VCs.

The interesting question is whether experienced people can leverage AI to construct actual new businesses rather than just AI bandwagoning. The fundamental problem is that most successful businesses have to deal with customer service, and AI doesn't do jack to make that better.

I don't think it's that supprising that software developers would try and make tools to make software development easier.

I've been releasing open source software for ~25 years at this point. The goal of that was always to save other developers time, as part of a collaboration where other open source developers save me time with their own work.

That's worked out pretty great so far!

Software development is not the first profession that has been automated away by programmers...

Absolutely untrue, you could have a solid career writing back office or internal software in financial services, insurance, higher ed, any number of industries. Would they make you a millionaire? No. But they'd pay for a nice house in the suburbs and raising a family.

i'm about 35 and i have made good money but not enough to quit. i plan on just sitting around cashing checks for another decade. with a few liquidity events along the way to sweeten the deal. should pay for my mortgage, some home renos, and fund my 401k etc. i don't foresee myself being out of work (and i don't even use AI to code! i'm just Actually Good!)

I started at age 39 though and did pretty well up until a year or two ago (16 years total).

Like many people I've been sad about the loss of a career I spent years developing skills in and I'm 55 now and won't be quickly retraining for another high paying career. Fortunately I do have other skills I developed earlier in life and low needs so will probably limp by fine but it's still a painful adjustment.

Point being, you could always write code as an older person. Well, back in the old days when we wrote code anyway.

> Why are we upvoting this?

Because people want to discuss about the topic of the headline.

I think you're being a bit harsh here.

Yes, the blog is mostly about AI, and yes, he publishes very frequently. But his articles don't read like AI and he claims not to have used it in his writing (https://www.seangoedecke.com/avoid-ai-writing/). And regardless of how you feel about the content, the community has clearly decided it's worthwhile as a discussion point.