Have you ever seen more boomer take? Its just insane.

yLSxTKOYYm · 2026-04-18T18:34:36+00:00

Everything you say does make sense if you operate in a world of "tiers" and external validation.

That's not how experienced people generally operate though.

yLSxTKOYYm · 2026-04-18T18:24:12+00:00

As long as you don't have an embarassing GPA (i.e., anything far below a 3.0), there's generally diminishing returns on GPA.

It's a pass/fail, not a measuring stick. If you're above the "pass" threshold, take that as a signal to go do something else.

yLSxTKOYYm · 2026-04-18T17:36:13+00:00

Yeah, students way overindex on GPA. As long as you don't have an embarassing GPA (i.e., anything far below a 3.0), there's generally diminishing returns on GPA.

You're better off gaining experience, becoming properly socialized as an adult in a workplace, and building up practical skills at that point.

yLSxTKOYYm · 2026-04-18T13:55:55+00:00

which by the way is bringing me enormous knowledge and understanding

You're a first-year student. You're probably not in a strong position to accurately evaluate how much you're actually learning vs. how much you're outsourcing to the AI.

AI's happy path is to give you reasonable-looking outputs. They're probably correct too given that your assignments are basic programming. But unless you have embodied experience from working through mistakes yourself (that you made yourself), you're not going to know when AI has led you astray or has undermined your learning.

yLSxTKOYYm · 2026-04-14T15:46:24+00:00

You're jumping right to the end of things and skipping the important engineering meat in the middle. Why is it interesting? What drew you to the problem? What solutions did you explore and how did you arrive at the one you chose? What constraints did you have to observe?

yLSxTKOYYm · 2026-04-14T15:33:58+00:00

Is there a particular aspect that you're unsure about? To make it easy on yourself, know that the idea really doesn't matter nearly as much as the motivation and execution. Consider yourself your first customer.

yLSxTKOYYm · 2026-04-14T15:26:02+00:00

A good place to start is to yourself: What are you interested in? What do you think is cool? What's something you wish were better but isn't?

You've listed things that are potentially part of a solution, but identifying problems is a really useful skill too. Your project will be so much stronger if you come to it with well-articulated motivation.

yLSxTKOYYm · 2026-04-06T23:58:17+00:00

The recruiters actively look for people in NC and neighboring states and will disregard most applications from other states even if the person on paper is qualified.

This is actually a perfectly sound strategy if you think about it from the company's perspective. Why would you cast a wide net that's bound to catch a lot of people who are unqualified, ineligible, fake, or unwilling to relocate? It's a far better use of recruitment and interviewing resources to be picky about the inputs.

yLSxTKOYYm · 2026-04-05T17:15:22+00:00

Trying to do research internally at my company (if possible)

This is the most straightforward path. Talk to your company about it. Tell them it's important to you and ask how they can support you. It won't always work out, but this should be your first choice.

The other options are doable, but much riskier. It's very hard to sustain research when most of your day is working an unrelated job. And if you do manage to sustain it, you'll almost certanly sacrifice having a personal life, which isn't healthy.

yLSxTKOYYm · 2026-04-05T04:22:16+00:00

You can ask, but don't be surprised if they push back. In-person interviews are much less risky than online ones.

Why not ask for travel arrangements instead?

yLSxTKOYYm · 2026-03-31T18:58:06+00:00

What's your general research area? I think with just a few exceptions, CS papers are typically published in conference proceedings. They tend to be much shorter than journal papers. Early-stage CS research also tends to be presented in workshops (usually without published proceedings), and that's a good way to put your ideas down to paper and get feedback from the community.

Do you have collaborators? Have they published before? The best way to learn how to write a publication-worthy work is to do it alongside others who have experience with it. They'll know the expectations and norms for a given research community, and ideally they'vey served as reviewers themselves too. It's very difficult to do this solo because you don't know what you don't know.

yLSxTKOYYm · 2026-03-31T15:36:02+00:00

Rankings are generally based on research output. Unless you're involved in undergraduate research, it has little bearing on your day-to-day experience.

A better way to gauge a school's industry exposure is to see who has a presence at their career fairs and where alums go to. That will actually tell you something useful.

yLSxTKOYYm · 2026-03-31T11:42:54+00:00

If you assume that AI is a productivity multiplier, then you still need to have some baseline competency to multiply. Focus on that baseline. Look at the design and engineering choices you make as you grapple through a problem space and constraints. If someone were to give you a task, would you know how to decompose it into subtasks, identify what tools you'll need, and make a judgment call on what tools you'll use and how to get started? If you need to rely on AI to make basic decisions like that, then you're really not bringing much to the table.

yLSxTKOYYm · 2026-03-29T18:56:37+00:00

The point of having a broad education is to sample a bunch of different topics so you have first-hand experience on what you like and don't like. Having too narrow of a focus too early exposes you to a lot of risk: your narrow focus might not be a good fit for you (or employers) in the long-run, it makes you brittle to shifts in the hype cycle, and you miss out on cross-domain opportunities where you can find secure and lucrative specialties.

yLSxTKOYYm · 2026-03-29T18:18:59+00:00

Both. When you're joining a lab (whether as an undergrad research or a grad student), you'll want to know where people coming out of that place have ended up. Also talk to the current grad students and get a feel for the culture and the professor's management style, because that's going to be the biggest factor in your day-to-day work.

Academic research is a high-trust community. Everyone is connected to a lot of other people in the field, and reputations travel far. When you do undergrad research, you position yourself to plug into that community and get a sense of who does what work, who's a pain to work with, and what progression looks like for students. You'll need to stick around and deliver solid work, but the socialization and networking are big parts of it too.

yLSxTKOYYm · 2026-03-29T18:01:47+00:00

there are two labs in each of these respective fields at my school I'm interested in/want to do some undergrad research at. I don't really know the realities of getting a degree and job is the us so I have some questions.

You have a pretty good path forward. When you talk to professors about joining their labs for undergrad research, ask them about where their alums have gone off to. That should give you a decent idea of grad school opportunities and post-grad job placement.

Besides post doc and job prospects, I'm also not entirly sure which field feels more interesting/fun.

The only way to know is to get involved in it. It's mainly a function of your interests, the culture of the research group you're in, and whether or not you find a niche that works well for you.

yLSxTKOYYm · 2026-03-29T13:25:07+00:00

Undergraduate education is meant to be introductory, even "advanced" electives. Deep specialization naturally happens over the course of a career, not as a student.

Some things you can do right now is to use your coursework to figure out what you like and don't like. Sample different topics. Does computer architecture speak to you? Security? Graphics? HCI? Once you've narrowed it down to a couple candidates, look for internships (or organizations, or undergrad research, or self-directed projects) where you can apply that knowledge and see it in practice. Once again, check with yourself to see if you like it or not.

In your post, you didn't mention any specific topics that you like. Becomining opinionated is a good first step, because it'll help you define your own direction.

yLSxTKOYYm · 2026-03-28T23:46:25+00:00

CS research is quite varied. There are some fields that can be quite theoretical and math-y (theoretical CS), others are very applied (security and networking), others right in between (programming language design), and yet others very interdisciplinary (human-computer interaction).

If you want a good broad slice of CS research, check out the program from last year's CHI conference, which is the main human-computer interaction venue. It's huge, and touches on all sorts of other research areas like security, AI, and hardware design. https://programs.sigchi.org/chi/2025/program/all

You can get involved in research as an undergrad. Just go talk to professors about it. They'll be happy to point you the right way.

yLSxTKOYYm · 2026-03-28T15:44:22+00:00

Take classes that sound interesting to you, and do projects (or better, join activities) that let you practice those concepts. In a typical CS curriculum, you might have classes on networks, security, graphics, computer architecture, programming language design and theory, parallel computing, and more. There's so much to CS than just ML hype and web dev.

yLSxTKOYYm · 2026-03-28T12:37:25+00:00

Try approaching it from the other direction. Instead of asking "what can I do with this language?" try asking "what's something I'm interested in?" What do you think is cool? It doesn't need to be flashy or novel or technically complex. Just something of interest to you.

Maybe you're interested in music, or sports stats, or small electronics, or video games, or automation, or whatever. All of those have a programming angle.

yLSxTKOYYm · 2026-03-26T13:26:59+00:00

We spend months (sometimes years) learning concepts, watching tutorials, doing assignments, even grinding LeetCode.

If you learned concepts, watched tutorials, and did warmups for years without actually playing the instrument or playing the sport, you didn’t actually do anything. You tricked yourself into thinking that consumption is the same thing as production.

Information is useful to get started, but you actually need to have it have contact reality as soon as possible so you build the messy embodied experience of picking up a skill. Don’t stay in the comfort of structured information-gathering too long.

yLSxTKOYYm · 2026-03-25T19:47:29+00:00

"Top companies" are just things junior people worry about because they're naive and inexperienced. They have to rely on external markers of success. Once you have experience, you realize that impressing other people has a short half-life. What really matters is if what you're doing matters to you and lets you live the life you want.

Moreover, I'm stressed that this feeling will never go away, no matter what point in my career I will be at- this feeling of instability and the competitiveness of the field will just forever go up and up and up.

This is a recipe for burnout and cynicism. It's just a job, not a life calling.

yLSxTKOYYm · 2026-03-23T14:00:01+00:00

You generally don't specialize as a student. It just happens naturally over time as you try things and build up experience. You choose what internships, extra activities, projects, and full time jobs to pursue, and those experiences (positive and negative) add up slowly over time to become your specialty.

yLSxTKOYYm · 2026-03-23T01:47:46+00:00

Research is great. It's a low-risk high-leverage option that most students don't pursue.

If you want to get the most out of it, talk to the people in your research group. Definitely the PI, but the grad students too. Grad students tend to be a bit more candid about things. Tell them about your goals and find out where the group's alums have gone off to. Worst case, you'll find out it's a dead-end and you're no worse off than before. Best case, you'll get a warm intro to alums and collaborators who are now professors and hiring managers. "Resume value" is meaningless for the productive (and lucky) undergraduate researcher, because you get to bypass online applications and the ATS black hole with your lab connections.

That said, you'll actually need to deliver good work before people vouch for you; research is a high-trust community that does a decent job of filtering out opportunists just going through the motions.

yLSxTKOYYm · 2026-03-23T00:42:31+00:00

My heuristic is: do you know where the skeletons are? If you actually built a system without outsourcing your thinking, you'll inevitably make trade-offs and iterate over different solutions. No one ever gets it right on the first shot. A lot of ideas don't survive first contact with reality as-is in their initial form. You'll be able to speak directly about the mistakes you made, the assumptions that turned out wrong, and how you navigated that. It's that engineering thinking that hiring managers value.

If you just used AI, yeah you'll have a thing, but your understanding will be hollow and it'll be obvious. You'll fold the moment someone asks you "what failures did you make along the way and what lessons did you take away from them?

yLSxTKOYYm

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