Android Security Bulletin–September 2025 (source.android.com)

There has been article after article talking about the high unemployment rate for new CS grads (mostly due to AI taking entry-role positions), even at world leading universities like MIT and Stanford (https://news.ycombinator.com/item?id=44157365)

As a junior CS student this is rather despairing

Before you tell me to ride the wave and learn about AI, I hate AI. I've used it, I've built with it, I've hacked it, but I simply refuse to work in it for my career.

It's not that I'm never going to use AI in my job, it's just that I don't want my career to revolve around it

But the thing is, I love computers. I'm not in it for the money, I'm not here to build the next Google, I just love building systems and seeing them work

I also want to go into cybersecurity, not just plain software development (but I do like building software on the side)

I have a number of side projects that I'm invested in, I'm in a number of CS and non-CS clubs at my university, I work in research on and off campus, I don't want to be super market-y in social media, I want to go to grad school, but I just can't shake the feeling that I'm not going to be able to get a job out of college and all of my work in CS will go to waste

So what can a CS student who hates AI prepare for the post-college post-AI work market?

Comments (4)

amradio1989 · 1h ago

You know the answer. The best way to prepare for any job market is to meet the demand. The demand right now is for AI knowledge and skills. There's no way around it if you want to be employed in a well-paying job with benefits and paid time off.

If that's not important to you, you can do whatever you want. Build systems, do contract work, join a small dev shop that shares your values, work on open source projects, etc. You don't have to touch AI if you don't want to.

There's more risk in that second option, and probably a lot less money (though not necessarily) but you'll be happier.

taylodl · 1h ago

1. Get experience. Generally, that involves internships.

2. Look for opportunities to make a quantifiable impact. If you don't understand the business impact of your work then ask.

3. Learn how to use AI properly. It's a productivity tool, nothing more. Those who understand the strengths of AI and the strengths of human analysis and experience and know how to blend those together when creating solutions are the ones who will still have jobs in the future. It's not easy to get that blend right and you're at a disadvantage by not having a lot of solutioning experience - so practice.

I’d be careful about going into cybersecurity. AI is well poised to have a significant impact in that area and could lead to substantial job loss, especially in roles focused on monitoring and incident response. If you're considering this path, think strategically: focus on areas that require human judgment, like threat modeling, red teaming, or security architecture. Software development will also be impacted by AI, but likely at a slower pace due to its creative and architectural nature.

fcpguru · 2h ago

I'm confused. It's like you want to be a professional courier but want to distinguish yourself by your excellent walking skills and you HATE bicycles. But using a 10 speed bike is always going to make you a better courier and bicycles are not going to be dis-invented anytime soon.

pavel_lishin · 2h ago

I disagree with the bicycle analogy or by how much AI currently improves productivity, but I do agree that these code tools are likely here to stay - so my advice would be to at least become familiar with them.

You don't have to love them, you don't even necessarily have to use them, but if we're sticking with the bicycle analogy, you do need to know to look before crossing the street, and you need to be able to put a bike into the correct gear if you have to ride it.