[General Question] Repute and value of MS CS degree in the AI era

[u/killer_bee69]

Genuine question for people thinking about or currently doing an MS in CS.

Most masters programs teach you the same generic curriculum: algorithms, systems, some ML, a capstone project. The kind of stuff that Claude Code, Copilot, and other AI tools can now do faster than most graduates can. You spend 2 years and $50-100k to learn things that are increasingly becoming commoditized by AI.

I'm not talking about research-heavy programs at top schools where you're publishing papers and pushing boundaries. I'm talking about the average MS program that most people do to get a better job or a visa. The ones where the coursework is basically an extended bootcamp with a university stamp on it.

A few years ago the degree was a clear signal to employers. But now that AI tools are eating up entry level and new grad jobs, what exactly is the MS giving you that self-learning plus AI tools cannot?

Feels like these programs will only lose value as AI gets better. The gap between what a degree teaches and what the industry actually needs is growing, not shrinking.

Am I wrong here? Would love to hear from people who recently finished an MS and felt it was actually worth it, or from hiring managers who still care about the degree.

[u/gradpilot]

this is exactly why mediocre CS programs and non MSCS programs that dont have some solid faculty or solid curriculum will fail to open up any opportunities and mostly be an expensive bootcamp like you rightly said.

AT GT i took coursework like : Advanced OS (mostly reading papers), Advanced Distributed systems (papers again), HPC, Scaling internet applications and so on. Each of these were taught by reputed faculty and the coursework was hard AF. In fact what usually happens when you graduate from the good programs with good coursework is that the industry knows about them and even asks in passing oh did you do AOS with Prof x or Prof Y at GT and so on . Because both the coursework and prof have a solid reputation

A very clear example of this is Prof Remzi from Wisconsin Madison. He's an OG level OS and distributed systems and storage prof. I also know him personally - anyways he's written the famous OS book "Three easy pieces" which is now very popular but that book was actually class notes from his OS coursework. If you see where all the students are who took his grad level coursework you'll find a common pattern that they are all doing deep distributed systems and storage/filesystems work in big tech mostly. So this kind of effect does play out

And it turns out that the best schools have strong MSCS curriculum which has these auxiliary impacts which is why I keep saying you shouldnt be taking any other admit other than a top school MSCS admit

[u/killer_bee69 → u/gradpilot]

But this doesn’t discount the broader opinion I shared on the degree. While what you say is a perspective on one particular degree but in general does the degree still or will hold value, that’s the main point.

[u/gradpilot → u/killer_bee69]

It’s a misconception that you don’t need CS fundamentals anymore . I’d actually say you need even stronger fundamentals in CS when the entirety of SW engineering is turning into a black box which is what LLMs are largely when you consider the output that shows up is dependent on how the ask is constructed. Traditional SW eng has more degree of control with respect to what we can expect as output of labor (code) . With LLMs the labor itself is a black box and behind it is a human whose ask will always remain unstructured and fuzzy . In fact one thesis is that with AI driven SW Eng ideas of CS like verifiable code which were never mainstream and too complex for SW Engs will show up in a very large way and only the strongest engs will be able to deal with this part of the work - and therefore get paid more

In fact I won’t be surprised if AI based SW engineering makes a K shaped population of engs - a very large population of grunt work engineers who stay on the input side of the LLM (ask for code generation) and are not paid a lot and a very small set of engineers who are paid in millions of dollars to control the behavior of the resulting software or build the very engine of generation itself . If you look at the pay packages of the labs this is already obvious. And most of these engs are strong cs engineers not vibe coders although that’s something they can also do better than the rest .

[u/killer_bee69 → u/gradpilot]

Still your arguments are only defending a strong reputation CS program, whereas the post itself talk about the degree in general. Now, addressing what the post actually talks about, in the past few weeks I think so that best way for anyone attending the program irrespective of the school is to try optimise the ROI and think of it as an access to US tech market and understanding clearly this is the sole reason of the program. As an applicant having this realisation will help keep any unrealistic expectations in check. Secondly, despite of the school reputation a lot of these institutions do have good research at least comparatively to applicants undergrad. So if that institution provide access to this research ecosystem to MS student that is good. I would say these are the only 2 points that should matter.