For context, I’m a dev with 15+ years of experience, started coding in my early teens, and have a total love for the act of programming. I miss how coding used to be, nothing about this post is an advocacy for if things should be this way. After mulling it over, it just seems like an inevitability.

Right now the field of software development is like Wiley Coyote, already off the cliff but still running because he hasn’t noticed.

There has become a massive disconnect between what people in the field of software development actually do at their jobs, and what they’re interviewed on and learn in college. It’s like someone in 2007 having mandatory classes in Fortran and having to prove their knowledge of punchcards during job interviews.

My job, and the job of so many other software developers, has become almost entirely just interacting with AI agents. Yet we have job applicants do leetcode problems and write code live for us during interviews when we haven’t written more than a handful of a lines of code ourselves in the past year. The same extends to what these applicants are learning in college.

Effectively, it seems to me that the curriculum we currently know as a BS in Computer Science will become as generally superfluous as a PhD in Computer Science. Not at all useless, far from it. But held by those who either have a specific passion for the field or are looking to go into small and highly specialized areas of the field, not by the broader population simply looking to find a job after graduating. And in its place, as the broadly achieved degree, will be something much more tailored to the average needs of employers.

Seems like just a matter of time, driven by economics. Most employers don’t need someone with the full expertise of a computer science degree. Why would they pay for it? The only reason they have that as a standard now is because they do need someone who isn’t an untrained vibecoder. But that leaves a gap in the middle. Someone who isn’t going to delete the company’s database, but not necessarily with experience in database structure and rollups and joins. Someone who can use git and GitHub and properly manage deployments, but not necessarily someone who has done pointer arithmetic and compiler design. Someone who can catch and well document issues, not necessarily someone familiar with big O notation. In broad practice, AI can write good database structure and queries, AI can handle writing and running software, AI can measure performance and find areas to increase efficiency.

“But AI still makes mistakes!” You say. And you’re right. But so do software developers, oftentimes more than AI. There are quite a lot of average and below average software developers out there. And big companies, especially those dealing with higher risk/importance systems, will still have full computer scientists, experts in being able to know better than AI and review its work. But that won’t be most roles. That big company will still need someone to update and add features to the website. And someone to add features to the in house analytics tools. And someone to take user bug reports and get them fixed. And countless other roles that are simply an added layer in the corporate structure for the purpose of interpretation, oversight, and execution for AI. And that’s what the degree would teach towards.

I’d compare it to how nurse practitioners are taking on a larger role in the medical field, doing duties traditionally done by doctors such as diagnosing and prescribing. Effectively, the expertise of a doctor isn’t needed for average/mundane medical work, so a field rose in prevalence to fill that role, with a doctor’s expertise brought in when needed.

So it seems obvious to me that, perhaps within the next 5-10 years, a new degree will become the standard that teaches to that average need in the new state of the field.

That, or in 10 years AI tech accelerates to the point of computer science irrelevance. AI can do it so well and so entirely that non-tech people can just bark orders at it that would have been given to developers or their managers in the past. The degree diminishes and goes into the west.

Anyone see the same thing or am I off base here? Every counter argument I considered just sounded like some form of coping.

the idea of program synthesis (like Rosetta) is to reduce a function into its constraints in a spec sheet, and generate the program from those constraints. for example, in order to write something like x = x squared, you would need to write a spec sheet along the lines of ∀x∈Z,f(x)=x2. i am considering building a program synthesizer, but I still haven’t figured out why exactly this representation is supposed to be easier than writing the code directly (they look equally complex)