Ask HN: Dean of studies at a French CS school – what should we teach?

8 points by fdeage 48 days ago | 6 comments

Hi HN,

I've just been promoted to dean of studies at a tuition-free CS school in [name redacted]. We take students with no degree requirements and train them from zero to Bachelor (3 yrs) and Master's (5 yrs) in software dev, DevOps, AI/data, cybersecurity, and immersive systems. We accept about 200 new students per year.

As I will have a significant influence on our future curriculum, I'm genuinely unsure what the right bets are. The ground seems to shift faster than any program can adapt. I've given up on preparing students for a 10-year horizon, I just want to make good bets on the next 3 or 5.

Students entering next September will graduate in 2029 (Bachelors) or 2031 (Masters). By then, the only thing that matters might be the gap between "can prompt an LLM" and "can actually engineer software" — or AI might have closed that gap entirely.

I have teachers who think we should double down on fundamentals (algorithms, systems, networking) because AI makes the floor higher but doesn't change what the ceiling requires. Others think teaching someone to hand-write a REST API in 2026 is like teaching cursive.

Here are some specific questions I'm wrestling with:

- What do you delete from a CS curriculum today? What are we still teaching out of inertia that AI has made, or will likely soon make, obsolete?

- What do you add? Should students spend a semester reading and reviewing codebases instead of writing them? Should we teach systems thinking or technical writing as a core skill? Or will prompt/context engineering simply be enough?

- How do you evaluate students when AI can pass most of your exams? Should we go for oral defenses? Offline exams?

- If you were hiring a junior in 2029, what would you honestly screen for?

I'm not looking for considerations about ASI/x-risk/post-work futures (though I personally think they matter a lot). But if you've redesigned a curriculum, hired juniors recently, or have educated opinions on what's now useless or will be useful, I'd love to hear it.

(Disclosure: rewritten with Opus 4.6 for misspellings and phrasing, all ideas mine)

Voranto 48 days ago |

Not a software engineer, but a student in the process of becoming one. I personally feel that the goal of university / school is not necessarily too get a lot of essential daily-use skills that will be used in the job, but more as a training for the brain. When I got my first internship, I noticed that I barely used any of the skills learned in university except a couple, but my ability to adapt to a new environment and new codebase had increased tenfold in comparison to previous years.

I may very well be wrong and have no job waiting for me in a couple years, but I feel like the goal of university should be to train the brain and become accustomed to software. The world of software is too large to be able to successfully teach the entirety of it in a couple years, so the next best thing is to prepare the students so they optimize any future learning.

For AI usage in class, I would do the same as in my university. The projects you can do as you like, but the exams are on paper and without AI. So if you choose to use AI for your projects, get ready for the exam because you may struggle there.

A subject that I feel is practically useless is for example Theory of Computation, but it has been one of my favorite subjects because it has forced me to think in some ways that I didn't before, and I have learnt a lot from it.

baubino 48 days ago |

I teach in the humanities and have a small software development practice. I strongly encourage adding a course (if you don’t have one already) on computing ethics and/or an ethics component to a course on human-computer interaction. Regardless of where AI is 3-5 years from now, preparing students to make good decisions about how, when, and where to use tech will be more important than ever.

uyzstvqs 48 days ago |

- Using AI chat as an assistant, not vibecoding or thoughtless copy-pasting. Teaching the limits of AI (it's just a statistical model giving the most probable desired answer), while embracing the huge productivity boost of having it help you figure stuff out. The only thing AI makes obsolete is StackOverflow, unless you like shooting yourself in the foot.

- Modern, simple, established tech stack. Python or Golang are good choices. Don't be teaching Java or C#, like some colleges probably still do.

- Add a little C programming to teach low-level fundamentals, enabling students to continue down that path if they desire.

- Developing from a Linux workstation. Deploying their code to Linux servers and the basics of managing them. (SBCs are great servers for learning)

- Cybersecurity fundamentals. How to avoid supply chain attacks.

- Exams: Students can work and use AI assistance. Afterwards their work is reviewed, and you question them why they made certain decisions. Those answers should make up 2/3 of the final grade.

ohnoanotherdev 44 days ago |

Junior dev here.

If possible, pair programming. Particularly with both large legacy code bases, and llm-generated greenfield content. Trying to communicate the 'gut feeling' of 'does this _definitely_ do what I think it does'.

Lots of sitting down, checking requirements for ambiguities, and learning how to write emails to the stakeholders.

Bluesky idea: hire three drama students, make them learn a spec and take on a different role each (hyperactive but bringing in feature creep; actually helpful but constantly distracted and cannot always respond; and a right b*stard who changes requests with the weather).

pillefitz 47 days ago |

I'd try to strike a good balance between CS fundamentals to teach students how to think and solve problems rigorously and patiently, and soft/leadership skills such as nonviolent communication, project management, business analysis.

dhruv3006 48 days ago |

Security - judging by the happenings on this week.