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Comment by fooker | Hacker News Reader

If by software engineering, one means typing code character by character into a text editor, sure it's going to be difficult to find someone to pay you for it.

If you mean creating software, well we are creating more software than ever before and the definition of what software is has never been so diverse. I can see many different careers branching off from here.

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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)

Calculators and CAD tools do not give you non-deterministic answers. Both of them simply automate part of the manual work for them without creating anything "new". I haven't used CAD tools but I did use some level editors such as Trenchbroom -- I think what is automated is the 3d shapes that you want to make -- e.g. back in the day of '96, when ID Software is creating Quake, there was very little pre-drawn shapes in the level editor and they have to make the blocks by themselves, thus it is very difficult and time consuming to make complex shapes such as curved walls and tunnels. Then better tools were invented and now it is much easier to create a complex shape. But you don't type "a Quake level with theme A, and blah blah" and then you get a more or less working level -- this is what AI is doing right now.

I think the right analogy to calculators and CAD tools, is IDE with Intellisense for SWE -- instead of typing code one char by one char, we can tab to automate some part of it.

But I agree with your consensus -- SWE is changing, whether we like it or not. We need to adapt, or find a niche and grit to retirement.

> non-deterministic answers

It doesn't make sense to get hung up on this aspect of LLMs. We prefer non deterministic so far because it tends to work slightly better even if it is completely possible to ask for a temperature=0 deterministic answer.

With more scale and research, at some point you'll get results that are both useful and deterministic, if it's not already the case.

It absolute makes sense to get "hung" up on something when it comes to planning society around it JFC. I'm with the other commentator, your understanding of these tools should be taken into question since you seem to be reading the tea leaves of statistical noise.

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.

This resonates strongly with me, in that all that extra margin has to be spent on something other than dividends

Your hypothetical ignores the distribution of programmer talent. Company 1 can pay more per person and hire 10x programmers, who can then leverage AI to produce the same or more as Company 2.

We have seen this in other knowledge industries. U.S. legal sector job count is about the same today as it was 20 years ago. But billing rates have exploded and revenues in the 200 largest firms have increased more than 50% after adjusting for inflation. Higher-end law firms have leveraged technology to be able to service much more of the demand and push out smaller regional competitors.

I think paying significantly more was a very localized thing that happened for AI researchers who were familiar with the alchemy that made GPT4 suddenly work much better than anything else seen before.

Of course it does. It ignores a lot of things. Mostly I just want to present the view that things aren't entirely hopeless and the entire industry is doomed to contract by 90% because of AI. Your legal system point also fits in precisely with what I'm trying to convey, just in a different direction.

The problem with this idea of feature backlog, at least everywhere I've worked, is what you really have is an idea backlog. You have some things people want to build, and maybe a business analyst or product owner has done a first pass. But they're far from the rubber-meets-the-road part where someone needs to write out a detailed spec based on the exact current state of the app/system, and the developers start asking questions as they run into unspecified edge cases--all of which usually means sitting down with the client again over a series of meetings.

AI coding agents help speed up none of that. Meanwhile the developers are either sitting in meetings or working on something else while the product owners hash it out with the client.

And sometimes, after all that, you realize the client can get 95% of what they're asking for if you just tweak some existing feature. Everyone's mostly happy, the app stays less complex.

An incorrect "reply" link, I think?

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.

This problem is not a software engineering problem nor an AI problem but a problem of the balance of power between working hard vs. investing. If the people who believe in working hard organize and slow down the tendency to rig everything for investors, then the markets should stabilize at a more generally prosperous place.

The balance of power is dictated by economic facts, not by organizing or politics. Auto workers in 1950 weren't better organized than auto workers in 2026. They just had more leverage because they weren't competing with auto workers in China. Likewise, Silicon Valley isn't paying people writing web apps $$$ because those workers are organized. They are doing it because they don't have a feasible alternative. If AI enables them to do more with less, they'll take that option.

Are you saying that auto labor unions can't go into other places and organize the people there for higher salaries and less wretched conditions? Or that organizing doesn't increase the power of the hard working people? Economic facts are partially determined by human factors such as the supply curve for labor and information flow amongst sellers or buyers for various goods.

Yes, and by shifting the labor supply curve you can make the laborers worse off, because it will often shift the supply curve of the product they’re making. If labor unions make you pay your workers more, you might need to raise the prices, which will make you less competitive, and reduce your sales, which can result in layoffs, or in preventing new workers from gaining employment.

> My concern would be whether creating that software pays enough to keep up with skyrocketing costs of living.

You might need to relocate to a place with much lower costs of living.

This was the idea behind remote working discussed during COVID-19 times:

- the company can pay less money because the employee is living at a much cheaper place than the expensive city where the company is located

- on the other hand, even with a smaller salary, the employee has more money at the end of the month because of the smaller costs of living

So both sides win.

but moving to a lower COL area can reduce that amount of public and private services one gets access to, no? network connectivity will, for example, likely be worse out in the sticks

Starlink / amazon something etc etc

Ignoring the preference of people generally wanting to live in HCOL areas, this only works if every company hires equally from LCOL areas. One of the benefits of living in a HCOL area is access to the job market it provides. It's much easier to get hired for a software position living in San Francisco than it is living in Deming, New Mexico.

More importantly, in San Francisco, there are a lot more opportunities than in coming. I've never been to either city (i'm not going to come to the conference I was at because I never left the hotel.) however, I can still tell you confidently that if you have a weird hobby, you're much lower than you can find other people with that interest, stores that sell the things you need to complete the hobby, and all those other things in life that you want. If you love doing the types of things people in Deming do, well, it's a great life, I'm sure. However, as soon as you want to do something off the wall, well, you may not even find enough people in Deming to have your cricket team, while I have no doubt that San Francisco has a team that you could join.

For the gilded class everything is available where everything is for sale.

For the not so gilded class that can get a job in a lcol area that allows them to actually own a home and have emergency savings the lack of cricket won't even appear on their mind (~also mark twain convincing others to pay him to paint.)

Re: stores that sell it well there's this thing called amazon.

Anyway. I feel like most people here are just afraid of going down the ladder in term of remuneration... A ladder that starting from the 70s got shittier for most...

First they came for the guy working 11h days working a blue collar job and I didn't say a thing because I was white collar...

Most of the time it's hcol areas because the gentry decided to nimby those who came after them...

And the ones who managed anyway to break through that (because the gentry needed some cash and built some extra expensive houses/ condos to try and keep the riff raff at buy...) Felt they had worked hard and became nimby'ers themselves because housing is not a humane thing ... It's an investment that has to grow grow grow...

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.

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.

It could go either way. Don't forget that LLMs also have expertise in the other domains. Who would do better - the chemist with vibe coded app or the developer with vibe coded chemistry?

My premise is that a vibe-coded app will be indistinguishable from a ‘hand-crafted’ one. So in that scenario the chemist wins, because the developer has no value to add.

It is clear to me that SWE and ML research will be subsumed before other domains because labs are focusing their efforts there, in their quest to build self-improving systems.

Vibe-coded chemistry is absolute garbage right now. The former would do magnitudes better.

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.

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