Ask HN: What should CS students do to prepare for the job market after college?
8 comments
I really understand how you feel, I've been in the industry for 15 years but I'd probably feel similarly if I were in your shoes.
I work in this field because I've always been passionate about it, and the current climate is far from great. Almost everyone is going crazy for AI-assisted coding (including many self-proclaimed senior/staff and above), just looking for ways to become more productive.
Truth is, if you're really passionate about the craft then the gains from AI-coding are marginal. It's nice to let AI do some grunt work, like writing boring unit tests, but all the fun stuff is still left to you.
Try to focus on that, use AI to automate some of the boring, energy-draining stuff, and work hard on the interesting bits while honing your craft. I guarantee you'll come out on top if you follow that plan.
Let all the wannabes get drunk on AI, the way things are shaping up today AI-coding is hitting a ceiling, and there's no risk of good engineers being replaced anytime soon.
Last bit of advice, avoid web development. It's an over saturated field, and most AI companies are focusing on generating web apps. Dive deep in any field that interests you (mobile, backend, data engineering, gaming, embedded, the list is endless) and have a great time while gradually increasing your value and your comp.
Good luck!
I work in this field because I've always been passionate about it, and the current climate is far from great. Almost everyone is going crazy for AI-assisted coding (including many self-proclaimed senior/staff and above), just looking for ways to become more productive.
Truth is, if you're really passionate about the craft then the gains from AI-coding are marginal. It's nice to let AI do some grunt work, like writing boring unit tests, but all the fun stuff is still left to you.
Try to focus on that, use AI to automate some of the boring, energy-draining stuff, and work hard on the interesting bits while honing your craft. I guarantee you'll come out on top if you follow that plan.
Let all the wannabes get drunk on AI, the way things are shaping up today AI-coding is hitting a ceiling, and there's no risk of good engineers being replaced anytime soon.
Last bit of advice, avoid web development. It's an over saturated field, and most AI companies are focusing on generating web apps. Dive deep in any field that interests you (mobile, backend, data engineering, gaming, embedded, the list is endless) and have a great time while gradually increasing your value and your comp.
Good luck!
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.
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.
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.
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.
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.
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.
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.
AI is just a tool to help you do your job, like an IDE, or stackoverflow, why do you have so much antipathy towards it?
I work with students (older teens/early 20s) and I understand the feeling of fear/despair. The reality is there are things you can't change and you should focus on those that you can. We're still not sure what is the impact of this generation of AI and it's hard to get an unbiased view amongst the hype. There are non-AI factors (ZIRP, Post-COVID, economic/demographic trends) that are likely contributing much more to the poor hiring conditions we're experiencing. Some comments/suggestions:
1) Take the emotion out of it. AI is just a technology and you don't have to love/hate it. Do try to understand it. Even if you are a skeptic of the LLM/AGI hype, the technology underneath it all is still quite fascinating. It surprized a lot of technologists.
2) Don't count on your degree. I think we're in this weird period where the traditional institutions are slowly collapsing, but the new hasn't been invented/popularized. Do finish your degree, but take time to hedge your bets and gain experiences outside of school. The great thing about being in your stage of life is you have very little to lose and a lot to gain from risk-taking. If you're constantly surrounded by your peers and academics, you'll not have the exposure to reality that you'd need to adapt.
3) Biggest skill that's missing, esp in Gen Z and not taught in higher ed, is how to communicate/signal to others like potential future employers. Beyond the superficial stuff like how to craft resume etc, but genuinely building your professional network. Who you know really matters. And not in the casual/family/we-play-golf-together sense, but out of professional respect. Make it a habit to reach out to engineers you admire and just ask for advice and interesting trends they're seeing (ex. in cybersecurity). When you do it as a student, and not as a job/favor-seeker, it changes the social dynamics. You'd be surprized how many would not only respond but talk your ears off. If they ignore you, big whoop, don't take it personally and just move on. A small minority of these people could make a huge impact on your life and career.
Some more tactical stuff:
- I'd assume you already know this, but resist the urge to use AI to learn. I've banned AI assistants for our junior engineers because they really slow down learning. It feels faster but you actually retain very little. We're re-discovering that doing things manually has a ton of long-term benefits that are hard to capture.
- Do take some effort to understand how businesses work. You'll likely be working in one and it's in your interest to understand the flow of money, incentive structures, and how businesses make decisions.
- Learn to eat well and exercise. It'll help boost your mood and not get bogged down in despair. Find ways to keep your spirit up for the long-term. Diversify your information diet away from TikTok, Instagram, and social media in general. Young people today have the dubious honor of being the first generation to have to fight off mass algorithmic addiction. Try to talk to more people in person to get a better sense of reality.
1) Take the emotion out of it. AI is just a technology and you don't have to love/hate it. Do try to understand it. Even if you are a skeptic of the LLM/AGI hype, the technology underneath it all is still quite fascinating. It surprized a lot of technologists.
2) Don't count on your degree. I think we're in this weird period where the traditional institutions are slowly collapsing, but the new hasn't been invented/popularized. Do finish your degree, but take time to hedge your bets and gain experiences outside of school. The great thing about being in your stage of life is you have very little to lose and a lot to gain from risk-taking. If you're constantly surrounded by your peers and academics, you'll not have the exposure to reality that you'd need to adapt.
3) Biggest skill that's missing, esp in Gen Z and not taught in higher ed, is how to communicate/signal to others like potential future employers. Beyond the superficial stuff like how to craft resume etc, but genuinely building your professional network. Who you know really matters. And not in the casual/family/we-play-golf-together sense, but out of professional respect. Make it a habit to reach out to engineers you admire and just ask for advice and interesting trends they're seeing (ex. in cybersecurity). When you do it as a student, and not as a job/favor-seeker, it changes the social dynamics. You'd be surprized how many would not only respond but talk your ears off. If they ignore you, big whoop, don't take it personally and just move on. A small minority of these people could make a huge impact on your life and career.
Some more tactical stuff:
- I'd assume you already know this, but resist the urge to use AI to learn. I've banned AI assistants for our junior engineers because they really slow down learning. It feels faster but you actually retain very little. We're re-discovering that doing things manually has a ton of long-term benefits that are hard to capture.
- Do take some effort to understand how businesses work. You'll likely be working in one and it's in your interest to understand the flow of money, incentive structures, and how businesses make decisions.
- Learn to eat well and exercise. It'll help boost your mood and not get bogged down in despair. Find ways to keep your spirit up for the long-term. Diversify your information diet away from TikTok, Instagram, and social media in general. Young people today have the dubious honor of being the first generation to have to fight off mass algorithmic addiction. Try to talk to more people in person to get a better sense of reality.
Study something that is in demand. Ie not cs.
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?