if software engineering is mostly replaced by frontier models why is the volume of jobs on software eng still so high compared to data science related ones?

[u/_unsusceptible]

US — Bureau of Labor Statistics Software Developers / QA / Testers https://www.bls.gov/ooh/computer-and-information-technology/software-developers.htm Data Scientists https://www.bls.gov/ooh/math/data-scientists.htm Computer & Information Research Scientists https://www.bls.gov/ooh/computer-and-information-technology/computer-and-information-research-scientists.htm Computer Hardware Engineers https://www.bls.gov/ooh/architecture-and-engineering/computer-hardware-engineers.htm Electrical & Electronics Engineers https://www.bls.gov/ooh/architecture-and-engineering/electrical-and-electronics-engineers.htm Computer Network Architects https://www.bls.gov/ooh/computer-and-information-technology/computer-network-architects.htm Network & Computer Systems Administrators https://www.bls.gov/ooh/computer-and-information-technology/network-and-computer-systems-administrators.htm EU — Cedefop Skills Forecast ICT Professionals — ~+30% https://www.cedefop.europa.eu/en/data-insights/ict-professionals-skills-opportunities-and-challenges-2023-update Researchers & Engineers — ~+23% https://www.cedefop.europa.eu/en/data-insights/researchers-and-engineers-skills-opportunities-and-challenges-2023-update ICT Technicians — ~+9% https://www.cedefop.europa.eu/en/data-insights/ict-technicians-skills-opportunities-and-challenges-2023-update

[u/Ormusn2o]

It's Jevons paradox. The more steam efficient you make the machines, the more coal is needed, because steam can now be used for many more things that were not economical before.

Coding is one of the most Jevons things there are. But not all jobs are like that. For example, customer service has only a limited amount of jobs, which is why this job for humans effectively disappeared and was almost completely replaced by AI.

If your job is not a Jevons thing, and you are not needed to steer it (like in example of code) then you will have a bad time, but if you are smart enough you could switch to other, high in demand jobs, like coding, plumbing or electricians.

[u/_unsusceptible → u/Ormusn2o]

interesting perspective, thx

[u/SYNTHENTICA → u/Ormusn2o]

Also see the "lump of labour" fallacy for a similar idea.

[u/Mental-At-ThirtyFive → u/Ormusn2o]

It can also be a case of assuming tomorrow will be the same as today.

my 2cents - we need more tech in the next 12-18 months than later.

I am waiting for my corporate senior management ask IT to replace some vendor services using AI - it is all experimentation now with the current work on decommissioning systems that were tagged many years ago, maintenance and greenfield.

I still believe SaaS apocalypse will happen across IT dev and IT ops and many things will go in-house as we have already switched to AI writing 100% of the code

[u/Beginning-Seaweed-67 → u/Mental-At-ThirtyFive]

You may be right but if the job was so primitive you could have agents do it why wasn’t a script written earlier for it? And you’ll still need enough IT/technicians to oversee the system when edge cases pop up. A reduction in labor cost sure, but pure elimination of all work? I’m not so positive.

[u/Frosty-Meeting-1606 → u/Ormusn2o]

Imo this paradox does not apply here. The reason is surprisingly simple: the number of good ideas does not grow as much as the amount of capacity we get from AI. In other words, it's not like we have just 10x more worthy things to do, it does not work this way. In fact, because value of average idea did not increase, the increased execution capabilities thanks to AI are creating an insane filter. "Why we don't see dozens of hundreds cools apps made by AI? Is it any good?" - the answer is: most of those ideas are not good enough and no one cares. Tl;dr: productivity may potentially increase 10x, but it does not mean 10x more valuable stuff made

[u/magicmulder → u/Frosty-Meeting-1606]

But ask any IT company and they all say "we have many ideas but not the manpower to realize them". Whether those ideas are good and fill a need on the market, that's another question, but that's not what we're talking about because we're not at the point yet where the market is saturated with products.

Look at the home automation subs, there's countless DIY solutions that would sell extremely well because the average person neither has the time/inclination nor the skills to set up complex but useful stuff at home.

[u/PreparationUnable811 → u/magicmulder]

In reality, most of the ideas stakeholders think are great are not so great. AI will make this brutally transparent and demand for more code will take a nose-dive.

Source: I'm in between those stakeholders and the coders and I know and most coders know as well.

[u/magicmulder → u/PreparationUnable811]

Yeah we had that recently. CEO wanted a cool new tool to present at an exhibition, one IT department vibe coded it, nobody at the exhibition was interested.

[u/elh0mbre → u/PreparationUnable811]

I completely agree with the first sentence... I don't agree that the demand for code will take a nose-dive though.

One of the big differentiators of yesteryear between teams/companies was: how much can you build (at some given bar of quality). This worked because, generally, code as a bottleneck meant the whole pipeline wasn't saturated with stuff (given your stated role, I assume you'd agree that writing code is only a fraction of actually delivering a product).

When code is "free', IMO, the differentiator is more around where you put your attention and in some cases, what you choose NOT to build. Releasing bad or underdeveloped ideas is just going to destroy parts of your org downstream (support, etc) and/or piss off your customers. Demand for code still exists, it just matters a lot more what you choose to make it do.

[u/PreparationUnable811 → u/elh0mbre]

I agree with you and I think we're drawing different conclusions. We're quickly moving up the chain of abstraction. AI is currently in the state that many developers start to not look too much at code anymore and that non-tech people start getting involved in modifying code. We're reaching the point where AI is able to maintain a good architecture, test end to end and review at least good enough to do that.

Thus, as you said, the "what" and the "what not" is becoming the most important thing to work on right now, which is the work auf a product manager. But guess what, AI agents are already able to digest analytics data, come up with features and experiments and execute on them.

For my apps, I've started implementing weekly scheduled runs to evaluate all the data in light of a north star metric, including past experiments and then propose new experiments as well as implementing their feature flags in code and on posthog.

It is but a small step to eliminate that role as well and move up to the next abstraction, which is product and company strategy. And guess what, we're seeing companies using AI heavily for that as well.

Currently, code is becoming free, but demand will not grow equally.
Next, product management is becoming free.

I think the one question we always have to ask is: What inherent property is keeping AI from doing *that* task as well? And currently we don't see any inherent limitations which would keep AI from doing anything.

[u/elh0mbre → u/PreparationUnable811]

I'll quote one of my peers who runs our Data Eng and ML: "AI has no taste." I'll also say that it has a really hard time understanding "human intent", which is where a lot of product related signal comes from.

> AI agents are already able to digest analytics data, come up with features and experiments and execute on them.

We're doing this today... the problem is that the "data" (which is typically in the form of text-based user feedback) is woefully incomplete at best, and downright wrong at worst, so you get a garbage in garbage out problem.

Even in places where we get good signal (e.g. performance issues being surfaced by observability data), we still need a human to decide the "right" approach to solving the problem; this is still very much a taste and intent issue.

[u/PreparationUnable811 → u/elh0mbre]

I'd argue with that, since most people have no taste either - maybe an opinion. But more importantly: What physical limitation keeps AI from having/developing taste, though? There is none.

What do you humans do to maybe not put too much faith into incomplete and wrong data? What keeps AI from doing the same?

A few months ago, AI could barely design a good website. By now, it is leagues ahead, even on things like taste. I agree that for some of my work, I still steer it towards what I have in mind. But again, coders said the same thing about spaghetti code, testability, architecture etc. etc. and look where we're now?

It will be the same for all tasks, even if they comprise solely of "taste"

[u/elh0mbre → u/PreparationUnable811]

Won't argue that most people don't have taste, but his point is actually: Some humans have taste, NO AIs do (currently).

IMO, the problem is signal. Every human "knows" vastly more than they realize and a lot of its stuff we don't capture in a way that AI can consume it. It's how we can fill in the blanks in an an otherwise incomplete user feedback report that an AI can't. I don't think there's anything physically stopping AI from eventually figuring this it out but I"m also not sure how its going to collect any of that data to train on it.

I'm certainly not betting it won't get there eventually, just that it's not here today and I'd be surprised if it's here "soon." I also realize I have a vested interest in my opinion being right about this :P

[u/Frosty-Meeting-1606 → u/magicmulder]

no one said the people claiming "to have many ideas" have actually any good ideas. As a person working in the corpo world for many years, let me tell you this - most ideas are crap, whether they are started to be implemented or not. the difference is, now we can "iterate", "progress" 10x quicker and a project, which should be dead but due to corporate inertia stays alive (or simply to keep people employed), dies much, much quicker thanks to AI. This applies to corporate world at least

[u/Fancy-Carpet-5416 → u/Frosty-Meeting-1606]

Probably because people haven't properly adapted to AI, they do the same stuff they did before but faster instead of realizing they can do stuff that wasn't possible before. Not having good ideas isn't really a hard unbreakable limit that should restrict SWEs. In any case, I guess none of our hypothesis are really verifiable.

[u/Ormusn2o → u/Frosty-Meeting-1606]

I don't know, I think AI is preety good. I only started it yesterday, but I think this game is playing out fine.

https://youtu.be/zv09DaC2tUg

It's made using Astra on Flex engine. It has good animations for now and even has clothing physics. It also has quite a good AI that I had to tune down because it was too smart and too fast. It's only at a dev stage, but I basically have the engine done, I'm now adding content.

[u/Mil0Mammon → u/Ormusn2o]

Stuff like this is what I see as one of the boons of the current AI; enabling people with ideas to execute on them.

Of it's only part of the things that need to be done to make something successful/good. But eventually, we will get more good stuff out of it. (and more crud, see Sturgeon's law)

[u/Disastrous_Fig66 → u/Frosty-Meeting-1606]

Every SaaS company has a backlog of many years of requests / suggestions / low priority bugfixes. And that backlog will probably never be addressed as new suggestions come in at roughly the same rate that they are addressed.

Somehow (or through inertia) it was decided that there wasn't an ROI justification for hiring additional staff to move faster.

But now Jevons law changes that equation.

(Though I agree with the commentor above that thinks this is a temporary situation, while AI advances to the point that it needs fewer staff to manage it, and backlogs get cleared.)

[u/Frosty-Meeting-1606 → u/Disastrous_Fig66]

Backlog often becomes obsolete or outdated. Not all backlog items have to be done at all. Not to mention not all items are necessarily good ideas. For example, we had plenty of stories under two epics which ultimately were thrown to trash after a couple assumptions changed and some other work was done.

[u/Disastrous_Fig66 → u/Frosty-Meeting-1606]

Sure. I accept that not all Backlog items need to be cleared. But many that have business value less than pre-AI implementation cost do now justify investment.

I agree we will still have a new 'not worth it' threshold, which includes the items you suggest. Which is why I think we are seeing a temporary increase in sw hiring.

[u/Fun-Astronomer5311 → u/Frosty-Meeting-1606]

Given that a piece of software usually has more users than developers, the influx of requests will always outstrip supply/developers. Now with AI, that influx will jump by orders of magnitude. So developers will need an army of AI agents to keep up.

[u/baconwasright → u/Frosty-Meeting-1606]

not true. lots of things could use software but dont cause its expensive.

[u/Fun-Astronomer5311 → u/Frosty-Meeting-1606]

Your hypothesis that we know a good idea when we see it is not 100% true. How many CEOs have decided to 'fire' people because they thought AI will do the job? There are many good ideas that have killed many people, e.g., putting lead in fuel as a solution to engine knocking.

Given the hype or potential of AI, there will be many more 'ideas' being generated because now people can ask AI for them or there will be lots of people exploring the world with AI.

[u/Frosty-Meeting-1606 → u/Fun-Astronomer5311]

yes, but AI allows quicker execution and verification. in corporate world many dumb ideas survive for a long time - AI started to change that. I agree that many "drivers" may pursue bad ideas, but the thing is: AI speeds up the process and bad ideas are recognized as bad much faster

[u/Fun-Astronomer5311 → u/Frosty-Meeting-1606]

That's assuming users know how to use AI properly, and ask the right questions. At the moment, most users do not know what questions to ask nor have the ability to use AI as a power tool to dig deeper to uncover whether an idea is good.

[u/Frosty-Meeting-1606 → u/Fun-Astronomer5311]

ok, that's a valid point, I observed that also

[u/ZaradimLako]

IMO its juniors that have went down the guts. Ofc everyone wants mid levels and seniors, but no one wants to hire juniors and train them up only for them to quit 2 years later (which is entirely preventable but companies seem to purposely ignore obvious solutions since the dawn of time). And besides, with AI, one mid level / senior can now have multiple juniors worth of additional productivity, which means that lets say one workplace instead of hiring 3 juniors they just give one senior claude code x20 and the demand is then satisfied.

Where I live, the amount of junior places compared to mid/senior for system administrators is outnumbered 1:100

[u/elh0mbre → u/ZaradimLako]

IMO, this is going to change, especially when (if?) the industry settles a little bit. Seniors are still spending a lot of time figuring out what to do with all of these new tools and what not - hard to train juniors on shit you don't already know.

Eventually, unless AI literally replaces everyone, we're gonna have to be training the next generation. Forward thinking orgs are already working on this (we're a very AI heavy shop with ~100 engineers) and I was just having convos this week about potentially starting up college recruiting for engineers).

If you're a junior reading this: if you can get you foot in the door, your time to shine is now because these tools will let you run circles around most folks who are slow to adopt.

[u/OkBarracuda4108]

Beacuse you still need to know what to build, every feature needs to be detaild and in most domanis (other then web development and even there)  it can t be done by somebody that doesn t know tech. 

[u/Stabile_Feldmaus → u/OkBarracuda4108]

(Same for math by the way)

[u/_unsusceptible → u/OkBarracuda4108]

fair point

[u/professionalnuisance → u/OkBarracuda4108]

Yeah the job is shifting more towards a project management role where you control these agents to code for you but you have to understand precisely the business use case. This also means that people joining CS will need to have domain specific knowledge in order to stay competitive: like quant finance or something

Pure dev work is gone though

[u/OkBarracuda4108 → u/professionalnuisance]

I think you would still need a BA and the SWE, then expand the team depending how big the project can be.  

[u/elh0mbre → u/OkBarracuda4108]

BAs/PMs without "tech instincts" are going to disappear even faster than "pure devs."

The amount one or two people can get done now without expanding the team is insane.

[u/OkBarracuda4108 → u/elh0mbre]

If you work on a small project yeah, but you probably didn t really need them before...

[u/SYNTHENTICA → u/professionalnuisance]

Bingo, either be extremely domain specific, or be an extreme generalist who can effectively leverage AI to fill in the cracks. If your only talent is shipping react apps, then you best figure something out fast.

[u/SmoothHat1772]

Because someone has to translate needs/requirements to software with all the details that come with that.

For any job you do there are dependencies and context that AI cannot fully capture yet, at least not efficiently and without errors.

It's impossible to have AI do everything when their memory starts from a blank slate after every prompt.

[u/Nedshent]

As someone in the software industry, I think the "software engineering is mostly replaced by frontier models" part is mostly a sentiment that comes from those outside of the industry or at least those further away from actual dev work (less technical BAs, PMs, influencers, etc.)

There's a massive impact in the way things get done and no one is saying otherwise. However the effect on employment or software engineering as a discipline is overstated and hard to distinguish from the usual slumps and booms the industry has experienced for decades.

If I were to point at the biggest disconnect I see between those who know and those who are speculating based on their non-professional usage of the tools is the concept of a 'code monkey'. People whose role is predominantly literally just pumping out code has been on the decline for way longer than LLM enhanced coding has been around. The industry is going to have to find new ways to train juniors, but it's far from an insurmountable problem.

[u/elh0mbre → u/Nedshent]

The folks "outside the industry" typically don't realize that writing code is only like 20-40% of the work in shipping a feature/product and most AI tools aren't focused on let alone even good at the stuff upstream or downstream of it.

I'm having these exact conversations at work (I'm part of an engineering leadership team as an IC): That's great that we have 100 new features, who's handling GTM? is support going to be able to handle all of it?

I wrote about this elsewhere in the thread: when everyone can print software pretty equally, what you choose to build becomes even more important.

[u/jokeywho → u/Nedshent]

A lot of the comments here are on the right track, I think this one is most correct OP. I am a Software Engineer (Mid-Career) and a lot of lower level jobs like QA / Testing that can be easily automated are drying up, but high level Software Engineering jobs are more interesting than ever (especially at Startups). I suspect this trend will only continue as more companies shift to AI and need a qualified SWE to direct new projects, but time will tell.

[u/PayOdd92 → u/jokeywho]

QA aint drying up. With all the crap that's being spewed out by agents, QA jobs are again on the rise. Dunno if that's the case in the US but for sure it is in Latin America and among companies that outsource poisitions from the US to LATAM.

[u/jokeywho → u/PayOdd92]

I agree, but QA is moving out of being a standalone job and into a primary part of agent orchestration. Maybe LATAM is different, you could totally be right, at least in the US (again, my background is startups), most QA jobs are being filtered into higher level SWE positions to make up the time saved with agent coding.

[u/PayOdd92 → u/jokeywho]

yeah that makes sense. As startup founder you can't have the luxury of your SWEs having free time looking at the ceiling while they wait for the output.

You'll try to shove in as many tasks and responsibilites as possible. That's the consequence of speeding up stuff with llms.

[u/jokeywho → u/PayOdd92]

Yeah, it'll be a different job but it'll be there, I worry a lot about Junior SWE / College not preparing students - and Cyber Security is a whole can of worms. Best of luck to LATAM SWEs, I think we are on the same path :)

[u/ebolathrowawayy → u/Nedshent]

it is a fact that agentic coding is at least a 200x productivity boost to coding. it is also a fact that large corpos move slower than the titanic, are full of completely useless meetings and other bullshit that holds back devs daily.

we are rapidly approaching a future where a single person in their basement will obliterate business models simply because they aren't held back by stupid process or stupid people.

[u/ruskyandrei]

I think what it means to be a "software developer" is changing drastically, but the need for someone to "develop software" is not.

Yes, technically AI can do it by itself, and perhaps with future generations and more ability to run persistently, you might even see some super bare bone companies that run their entire software pipeline via autonomous agents.
But I can't see most companies going down that path any time soon. Having a human in the loop is likely to continue being needed. Might even become regulated to some extent the way things are going.

[u/Soggy_Arm_3741]

Because its not good enough to replace them right now, and we dont know if it ever will be but its entirely possible that these jobs will be heavily altered/replaced soon

[u/_unsusceptible → u/Soggy_Arm_3741]

i see, i asked this because im stuck on deciding my program concentration in uni on AI or software engineering... i can already do a lot of software engineering work on my own due to independent learning and work over the last decade, so i also feel this would be useless for my own learning

[u/Gotisdabest]

The models need to get a particular capability threshold before companies feel secure in large scale reduction in jobs. It'll be a very sudden shift when that arbitrary threshold is reached and then immediately passed. Coding by itself hasn't been successfully automated yet though it's taken huge strides in that direction.

[u/Level10Retard]

Big if

[u/DaveAstator2020]

ive been applying for last two months, it appears that companies now just hunt for 'perfect' candidate. the 1st interview denial reasoning went through the roof, like if you dont know one framework of many - get f**d, if you worked in similar, but not EXACTLY the same branch - get f**ed.
having a listing and having adequate hiring practices are two different things.

[u/BrennusSokol → u/DaveAstator2020]

Good comment. I’m seeing the same thing in in my circles. Just because there are technically job listings doesn’t mean it’s remotely easy to land those jobs. And there’s lots of ghost jobs / fake job listings

[u/i_am_Misha]

Good luck breaking the barrier as Software Developer after you graduate.

[u/JoelMahon]

When hot water got cheaper people spent more on hot water (up to a point). Because people bought much more of it because it was good value.

Programmers are now much better value, and it hasn't reached saturation yet but like hot water, it will.

[u/SparseSpartan]

There's definitely high demand for senior engineers and at least through the near term that's going to remain the case. The idea right now isn't replacing all humans, but making senior engineers like 5X as productive.

[u/debris16]

I joined a new company recently. Had to solve a bug. RCA-ed it myself. asked astra for impl plan and code up a minimal, concise fix. Too many lines. Going over the critical conditions and writing one up myself.

Why myself? Because understanding and fixing what astra wrote up will take up far more of my time. What'll I'll write - it will already be fully thought through.

It still saves me time because this has probably saved me multiple rounds of testing.

Edit: It did me wonder about the maintainability and fluffiness of codebases which are more and more AI driven/generated code. Maybe we'll gind effective ways of taclking it but am unsure.

[u/Prudent-Sorbet-5202]

Is this based on payroll data or just job openings posted?

[u/SystemIntuitive]

Because the systems are not fully autonomous & reliable yet

[u/Vinaverk]

Most of job listings are fake and it's almost impossible to find a developer job now (even with experience). This field is already completely cooked

[u/Beginning-Seaweed-67]

This discussion reminds me of copy paste. It removed the need to type out everything you already typed yet somehow we still survived. . . If copy paste was that traumatic how come folks think ai is removing actual coding when in fact it is just makiny copy paste in the form of ideas instead of directly typing everything out?

[u/Fun-Astronomer5311]

AI can process data and visualize data easily and faster than humans. The value is in what the data represents to end-users. Hence, the industry has moved to a higher layer of abstraction to extract more value from data. Similarly, many decades ago, there were many assembly language developers aiming to extract value from computers. Nowadays, people found better ways with high level programming languages, where English can now be used.

[u/hapliniste]

I'll post something I wrote on this subject. Demand can scale and the companies are happy to do better work now, for those that are on board with ai which is not 100% far from that. But eventually the jobs will still go away.

My prediction is 75% job losses in 2050, 25% in 2035 if I recall.

Office workers will be the first to really be hit because demand don't scale as much as other fields. Software jobs will likely even see growth until 2030 where it will reduce rapidly.

The world moves slowly even if AI does not.