I just finished a PhD in stats, and before that, studied computer science. I had planned to go back to industry to do software engineering or be a data scientist afterwards.
However, it seems that in the meantime, vibe coding has taken over the software industry and swallowed most data scientist roles. Few open positions, and the ones that do exist are just pushing a button instead of thinking and solving problems. Is this a correct assessment? Should I try to get back in or just find a new career? I am not too keen on staying in academia either.
With a PhD in stats you should be able to make more than most software developers. Companies need scientists to sign off on certain claims for liability reasons and it’s easier for them to just have one in house. That’s a licensed position that AI will not be able to take away.
AI poses one major risk to SE in general: the dropped need for low/entry level employees.
It used to be, a senior would have a team of mid- and junior engineers, senior would be in charge of the big picture while the team learned, and delivered the actual low level tasks.
But with AI, companies started hiring only seniors. Which is an issue - now the market is full of “entry level” graduates who simply can’t find a job because nobody’s hiring. And seniors are left wrangling AI agents that don’t learn, don’t work autonomously, don’t ask questions, don’t bring ideas.
don’t bring idea
In my experience the AI agents do if you ask them. Rather than giving them a problem and telling them to solve it autonomously, I ask them to give me feedback on my plan and propose potential alternatives before starting any coding, and often I get good suggestions from them this way.
If your idea of an idea is “concept that I personally am not aware of but which has been conceived, elaborated on and documented by another human being”…
Then yes, totally!
The AI can extrapolate, but even if it couldn’t, ultimately I need an idea that works, not necessarily a completely original idea that works (and most humans don’t come up with completely original ideas very often either).
Yeah, I was gonna say, most engineers are gonna be taking a lot of code from the internet anyway. Most problems modern companies face have already been solved in one way or another, its just figuring out what fits your specific product and needs. That being said, I’m pro “ai as a tool in non-creative fields”, but it certainly doesn’t replace engey level engineers. I see it closer to a calculator or like factory machine. It can cut out the grunt work and summarize things well, but it takes a looooot of steering to actually work. And the engineer can maybe learn some new concepts or techniques along the way
Sauce for the first sentence?
I don’t feel comfortable telling anyone to go into software engineering right now. I think the future is really uncertain. That said, I’m also not convinced this is a bad time.
The need for software engineering isn’t going away. LLMs are actually not very good at thinking and solving problems at a high level, so we still need people for that. LLMs are more of a performance multiplier than a replacement for human software engineers.
That does mean that fewer engineers will be needed to do the same work. But also, I think there’s a chance it’s a Jevons Paradox situation, and maybe if the cost of software drops we’ll see even more demand for it - like how we found tons of new uses for electricity when prices dropped. Maybe we’re entering a golden age of bespoke software. Unclear.
I agree with this take. Lots of uncertainty because LLMs are rubbish at probably solving (which is a human’s strength). LLMs don’t have a semantic understanding of the problem they’ve been tasked with solving.
tl;dr LLMs are useful tool but not software engineers.
The Jevons paradox point is interesting. Maybe we’ll finally get better software products, so far it seems like everything is as buggy and slow as as ever.
Even if unemployment isn’t an issue, engineers would need to have the flexibility/freedom to do things by hand sometimes though I think. Go into details, understand the lower level work. Just like pilots occasionally hand-fly not to lose their skills. Otherwise, it’s just too mind numbing to do long term, even if humans were involved in the big picture decisions.
The Jevons paradox point is interesting. Maybe we’ll finally get better software products, so far it seems like everything is as buggy and slow as as ever.
The bar to be a coder is being lowered, but actual software engineering with metrics, requirements, and deadlines will probably increase. I can easily see a world where everyone rushes into the AI to solve problems that used to not be cost effective and at the end of the first push (hopefully that’s around now) there’s a lot of new, untested code, and no metrics whether programmers were more efficient, and more importantly no metrics (I saw stats PhD) about whether the bottom line increased: https://www.cnbc.com/2026/10/02/ai-redefining-wall-street-jobs.html
How would one measure the efficacy of two different AI generated trading regimes (or however it is they work up there) when the people who understood what they were asking can’t understand any of the code?
Thanks for your perspective. It helps to get some hope that software development skills might be still needed in the future.
YES
My advice, as always, is to take a look at current offers and try to find both a line of work and a company that would interest you (and has the right benefits for you). Then build towards the requirements, not the other way around.
Every single piece of our economy runs on software so there are plenty of options beyond being an AI wrangler at Evil-Corp.
I left corporate software engineering after 10 years. I wouldn’t recommend it unless you can stomach the worst side of humanity.
I still love development, but I would only return if I can get a guarantee that I don’t have to develop or work with AI, and only if I’m offered more than I was making before
What did you switch to?
I already had a second career in circus so I’m just shifting priorities
circus
wat
I’m a senior developer. I haven’t written any code by hand so far this year, and the highly technical stuff I have on the resume is already done both faster and better by AI than I would be able to do it. However, I find that there’s still a lot of work for me to do because the AI has trouble maintaining coherence and working towards long-term goals in the absence of straightforward metrics. I end up herding a bunch of highly competent but easily distracted AI agents. It’s like being a manager, I think, although I’ve never managed humans myself. You still have to keep track of the overall goal and how the different agents are working (or failing to work) towards it in a way that requires human judgement and experience. I wouldn’t suggest becoming a junior dev in 2026 (because I would rather work with an AI than a junior dev) but senior devs aren’t obsolete yet although the nature of the role is changing rapidly and I don’t know what the future will bring.
I’d give it a couple months before really committing to a new career
Everything is very uncertain right now, but the AI bubble is looking very poppable right now. After that happens, I think we’ll have a lot more clarity about what the future will look like
It’s going to be a long 8 weeks, but hopefully on the other side of that things will start making sense again
Data analysis is only going to be more and more in demand.
