Greentext

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They are going to care if you can maintain your code. Programming isn't "write, throw it over the fence and forget about it", you usually have to work with what you - or your coworkers - have already done. "Reading other people's code" is, like, 95% of the programmers job. Sometimes the output of a week long, intensive work is a change in one line of code, which is a result of deep understanding of a project which can span through many files, sometimes many small applications connected with each other.

ChatGPT et al aren't good at that at all. Maybe they will be in the future, but at the moment they are not.

I don't think that's true. That's like saying that watching hours of guitar YouTube is enough to learn to play. You need to practice too, and learn from mistakes.

Professors hate this one weird trick called "studying"

Yeah, if you memorized the code and it's functionality well enough to explain it in a way that successfully bullshit someone who can sight-read it... You know how that code works. You might need a linter, but you know how that code works and can probably at least fumble your way through a shitty 0.5v of it

1. Ask ChatGPT for a solution.
2. Try to run the solution. It doesn't work.
3. Post the solution online as something you wrote all on your own, and ask people what's wrong with it.
4. Copy-paste the fixed-by-actual-human solution from the replies.

If we're talking about freshman CS 101, where every assignment is the same year-over-year and it's all machine graded, yes, 90% is definitely possible because an LLM can essentially act as a database of all problems and all solutions. A grad student TA can probably see through his "explanations", but they're probably tired from their endless stack of work, so why bother?

If we're talking about a 400 level CS class, this kid's screwed and even someone who's mastered the fundamentals will struggle through advanced algorithms and reconciling math ideas with hands-on-keyboard software.

Most of my CS exams in more advanced classes were take home. Well before the internet though. They were some of the best finals I ever took.

Assignments involved actual coding but exams were generally pen and paper when I got my degree. If a question involved coding, they were just looking for a general understanding and didn't nitpick syntax. The "language" used was more of a c++-like pseudocode than any real specific language.

ChatGPT could probably do well on such exams because making up functions is fair game, as long as it doesn't trivialize the question and demonstrates an overall understanding.

I like the sentiment of the article; however this quote really rubs me the wrong way:

I’m not suggesting we abandon AI tools—that ship has sailed.

Why would that ship have sailed? No one is forcing you to use an LLM. If, as the article supposes, using an LLM is detrimental, and it's possible to start having days where you don't use an LLM, then what's stopping you from increasing the frequency of those days until you're not using an LLM at all?

I personally don't interact with any LLMs, neither at work or at home, and I don't have any issue getting work done. Yeah there was a decently long ramp-up period — maybe about 6 months — when I started on ny current project at work where it was more learning than doing; but now I feel like I know the codebase well enough to approach any problem I come up against. I've even debugged USB driver stuff, and, while it took a lot of research and reading USB specs, I was able to figure it out without any input from an LLM.

Maybe it's just because I've never bought into the hype; I just don't see how people have such a high respect for LLMs. I'm of the opinion that using an LLM has potential only as a truly last resort — and even then will likely not be useful.

Probably promoted to middle management instead