I've just been promoted to dean of studies ("directeur des études") at La Plateforme (https://laplateforme.io), a tuition-free CS school in Marseille, France. 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•2h ago
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.