I think this is overly optimistic; it assumes universities reacted instantly and pivoted to teaching coding with AI as soon as it was feasible. In actuality, university curriculums cannot change quickly, and AI capabilities are changing much faster. In my experience, some students are using AI to write code, but then have no idea what's going on. The "skill" of typing "Write a function to do [basic thing]" will not make them AI-native or help them in the workplace.
For CS students I agree. For non-CS students, who need programming as a way to use computers as a tool, I think they do need a solid understanding of what a computer does and what it's limitations are (and what it's capable of), but for their day jobs (once they graduate), they will most likely be getting AI to do everything for them. As long as they can reason about what's happening, to understand the results and to improve them, this seems likely to be the path in the future.
This is an introductory programming course, designed for non-CS students e.g. engineers and scientists.
> Learning outcomes
> 2. Explain key concepts in AI-assisted programming, including Large Language Models (LLMs), prompting, problem decomposition, and top-down design.
> 3. Apply the workflow of AI-assisted programming and prompt-engineering techniques to guide and improve code generated by AI assistants.
This course used to be non-AI (last year), and they rewrote recently to incorporate AI tools, as they realised the writing's on the wall for non-programmers.
It must be quite challenging to write curriculum when the underlying technology (AI) is changing so quickly.
It also is naive to think, if AI is shrinking head count, that companies will seek anything other than seniors.
2008 triggered a glut of cheap experienced workers that slowly reengaged juniors but this time that the entire ladder is going to be more valuable than any grad.
In my experience, some students are using AI to write code, but then have no idea what's going on. The "skill" of typing "Write a function to do [basic thing]" will not make them AI-native or help them in the workplace.
How many of them can read x64 or ARM assembly emitted by their compilers?
It’s how I deeply understand what a RAM lookup vs having it already in a register means for optimization.
Me, too, but we should both understand what we're talking about: a hobby.
It's like teaching cursive to schoolkids. All well and good, but don't you dare complain about limited classroom time for instruction in other, more important subjects.
Understanding how computer architecture works is a hobby? Is unimportant?
I built and deployed embedded systems robotics that protect water and oil pipeline infrastructure that costs billions of dollars if there is a failure.
That is not a hobby, that’s a career.
The tools I built just helped fix the fresh water access for my entire city of 2 million people. Explain to me what’s more important than people having access to water.
That's great, you sound proud of your work and you should be. But what about all the human pipeline-inspection crews you've put out of work with your robots?
AI is not an abstraction layer. If you work entirely on the level of prompting without any knowledge or understanding of the underlying code, you are not actually an engineer, but more of a half-assed technical manager. (And your job will be first on the chopping block.)
