In my classes there is hardly anyone that has been able to get their hands on an internship, and even the professors have started their classes with monologues about "I don't even know why you show up, none of you will have jobs after graduation, good luck out there." (quote from my DS professor) A lot of my peers are looking to move out of the US and look for jobs elsewhere, or perhaps jump straight into graduate school to ride it out.

On the Computer Engineering side, the faculty seems a lot happier, and the students also seem to be better off. But I don't think this will last however, I have noticed a steady decline in the businesses that have been searching for Computer Engineering in our career fairs. When I enrolled there were about two dozen "Computer Engineering Wanted" posters at the fair, and the last one in Feb 2025 I only counted one.

I'm honestly thinking that if this continues I'll be looking at the military, right now I'm trying to work on side projects in the meantime.

I've conducted two phone screens this month and asked each candidate to implement FizzBuzz in their language of choice after giving them an explanation of the problem. Both took more than ten minutes to write out a solution and we don't even require them to run it; I'll excuse trivial syntax errors in an interview setting if I can tell what you meant.

When CS students can't write a basic for loop and use the modulo operator without relying on AI, I weep for their generation.

I honestly think that doing an in person fake technical interview with a few easy Leetcode questions at the end of your education would be a good way to weed out those that have failed to even learn the basics of the trade.

I'm so old we learned to program with giant C reference books. There was no internet, much less Google. We didn't have no fancy auto-complete, crumbs a text editor was considered advanced. Them youngsters coming to us couldn't program without Googling syntax, or using an IDE.

So yeah, sure, AI is changing the game. It's hard to evaluate students because the tools they are using are different to our experience. For decades we "make them code" as a measure of ability. In 3 years (their college experience) the toolset has changed.

Good students, good employees, are those who understand the problem and can adapt to a solution. AI is a tool that can be wielded well, or badly. Our approach to hiring will need to adapt as well. But good people are still out there, and good people make good workers.

To be honest I never was much in love with the leet code measure of hiring. Past a certain coding skill level I was more interested in the person than their ability to memorize an algorithm. Today that necessary skill level is lower, or at least harder to evaluate, but the problem-solving-mind is still the thing we're looking for.

So be careful of seeing the use of new tools as a weakness. The history of the world is littered with obsolete technologies. (Here's a sextant, where are we?) Rather see people who use tools for what they are, tools. Look for people who are curious, who see patterns, who get things done.

And to students I say, mastery of tools is a necessary step, but ultimately an uninteresting one. See beyond them. Be curious. Look under the hood. Ask questions like "is this code good enough to be running 30 years from now?" Because a huge amount of what you see now has foundations in code written a long time ago, and written well enough to stand for decades.

College is not "learning to program". College is learning how to adapt to an ever changing world, that will require your adapting many times over your career.

You're gonna have to do a lot of work to convince me that people who only know how to drive an LLM are learning how to adapt to sweet fuck all

At least with a calculator, people still had to know the difference between addition and multiplication, in order to use the calculator correctly

Driving an LLM properly requires knowing to evaluate if the results are correct. People can certainly try to pass generated code over for PR. But even just one code feedback or debugging should uncover if the person understood what they were doing.

What if changing from a "write code" based idea of programming changes to a "remove technical debt from code" skill?

What if the next generation of programmers is not focused on the creation of new code, but rather the improvement of existing code?

What if the current crop of programmers has to literally adapt from a world that has valued code quantity to a world that values code quality (something we dont especially prioritize at the moment?)

I'd argue that we're asking the current generation to be massively adaptable in terms of what was expected of us 10 (or 30) years ago, as to what will be required of them 5 years from now.

And to be clear, I'm not suggesting that LLMs will teach them to be adaptable. I'm suggesting that a world that contains LLMs will require them to be adaptable.

I don't believe you can do this if you can't write code, but sure. Maybe

> What if the current crop of programmers has to literally adapt from a world that has valued code quantity to a world that values code quality

LLMs seem more likely to increase the value of quantity and decrease the value of quality. That's playing out in front of us right now, with people "vibecoding"

> I'm suggesting that a world that contains LLMs will require them to be adaptable.

And ones who can't adapt will be ground to mulch to fuel the LLM power plants no doubt

A calculator will always give you correct result as long as you give it correct input. This is not the case with LLM. No matter how good your prompt is, there always a chance the output is completely garbage.

One way I try to disincentivize cheating on projects is by having in-class paper exams, including weekly quizzes, as well as in-class paper assignments, and making sure that these in-class assessments are weighted significantly (roughly 60% of the overall grade). No electronic devices are allowed for these assignments. This forces my students to be able to write code without being able look up things online or consult an AI tool.

I still assign take-home programming projects that take 1-2 weeks to complete; students submit compilable source code. Practical hands-on programming experience is still vital, and even though cheating is possible, the vast majority of my students want to learn and are honest.

Still, for in-person assessments, if I had the budget, I’d prefer to hand out laptops with no Internet connection and a spartan selection of software, just a text editor and the relevant compiler/interpreter. It would making grading in-class submissions easier. But since we don’t have this budget, in-class exams and exercises are the next best solution I could think of.

As the world changes, education can be slowest to adapt. My father did his math on a slide rule. I was in high school as we transitioned to using calculators.

My personal take on your approach is that you're seeing this from the wrong side. Creating an artificial environment for testing suggests to me you're testing the wrong thing.

Of course most school, and college, classes devolve to testing memory. "Here's the stuff to learn, remember it enough to pass the exam." And I get it, this is the way it's always been, regardless of the uselessness of the information. Who can remember when Charles 1st was beheaded? Who can't Google it in an instant?

Programing on paper without online reference tools isn't a measure of anything, because in the real world those tools exist.

Indeed, the very notion that we should even be testing "ability to write code" is outdated. That the student can create code should be a given.

Rather an exam should test understanding, not facts. Here's 2 blocks of code, which is better and why? Here's some code, what are the things about it that concern you?

Instead of treating the use of AI (or Google, or online help, or that giant C reference book I had) as "cheating", perhaps teach and assess in a world where AI exists.

I truly do get it. Testing comprehension is hard. Testing understanding is hard. Testing to sift wheat from chaff is hard. But, and I'm being harsh here i know, testing memory as a proxy for intelligence or testing hand-code-output as a proxy for understanding code is borderline meaningless.

Perhaps in the age of AI the focus switches from 'writing code' to 'reading code'. From the ability to write to the ability to prompt, review, evaluate and so on.

Perhaps the skill that needs to be taught (to the degree that community college seeks to teach skills) needs to be programing with AI, not against it.

I say all this with respect for how hard your job is, and with my thanks that you do it at all. I also say it understanding that it's a huge burden on you that you didn't necessarily sign up for.

It's similar to a calculator. We give student graphing calculators, but ONLY after they have already graphed by-hand hundreds of times. Why? Because education does not work like other things.

Efficiency, in education, is bad. We don't want to solve problems as fast as possible, we want to form the best understanding of problems possible. When I, say, want to book an airplane ticket, I want to do that in the fastest way possible. The most efficient manner. I care not about how an airport works, or how flight numbers are decided, or how planes work.

But efficient education is bad education. We can skip 99% of education, if we wanted. We can have, say, the SAT - and spend 1 year studying only for the SAT. Don't bother with the other 12 years of schooling.

Will you get an acceptable score on the SAT this way? Maybe. Will you be intelligent? No, you will be functionally illiterate.

If we use AI for programming before we can program, then we will be bad programmers. Yes, we can pass a test. Yes, we can pass a quiz. But we don't know what we're doing, because education is cumulative. If we skip steps, we lose. If we cut corners, we lose. It's like trying to put a roof on a house when the foundation isn't even poured.

Don't lock down the computer unless you are hiring people to work in a SCIF. Instead, give candidates a brutally hard/weird problem and tell them to use any resources they can get their hands on, by fair means or foul. (They will do that anyway if you hire them.) Then watch how they deal with it.

Do they just give up and stalk off in a huff?

If they Google for answers, do they use sensible queries?

If they use AI, do their prompts show skill at getting ideas, avoiding blind alleys, and creating effective tests?

If they call their friends, see how effective they are at communicating the requirements and turning the answers into a solution. Might be management material.

I feel like this doesn't get said enough, but I'm almost certain your issue is happening during filtering prior to even getting to the interview stage. Companies are straight up choosing (the wrong) applicants to interview, the applicant fails the interview, the company does not move forward with them, and then the companies does not go back and and consider the people they originally filtered out.

I know companies get swamped with tons of applications, and filtering is basically an impossible problem since anyone can make their resume look good, but every applicant that applied can't be that bad.

Bad applicant filtering at the first step is hurting both companies and applicants.

In 2009, in the midst of the financial crisis, one of my commencement speakers (and the recipient of an honorary doctorate) was Kenneth Chenault, CEO of American Express. I don't remember his exact words, but his message to the graduating class was, we have a different perspective on the world and different values— thriftier ones, necessarily— and if we stay true to them, the world will reflect them when we succeed.

"Maybe instead of having a car, like your parents' generation, your first big purchase may be a bike. Times change." Something like that.

Four days later, he laid off four thousand workers from AmEx, just a smidge more people than the graduating class.

Edit: according to Wikipedia, that year he took home $16.6 million.

I graduated into a world without internet (we had it at university, hosted on Unix and Vax machines, but it wasn't available commercially. ) People who had computers were running DOS. Most businesses had no computers at all.

So the job market was both good and bad. We graduated with skills that were hard to find. But we graduated into a world where big companies had computers, small companies had paper.

So huge market opportunity, but also huge challenges. We'd either graduate into big business (banking, insurance, etc) or start something new.

I joined a person doing custom software development. We'd sell both the need, the software, and usually the hardware. ) When we didn't have work we'd work on our own stuff, eventually switching from custom development to products.

We had to bootstrap, there was no investment money in our neck of the woods.

I won't pretend the job market is the same (or even vaguely similar) now, but it seems to me that opportunities for self-employment still exist. Software is still something you can build with basically zero capital.

Ultimately a job is just someone else finding a way to add value to society. Software us one of the few ways you can do that yourself, skipping the employer.

95% of people see "a job" as the goal. I get that. My own kids are like that (zero interest in starting something new.) But there are opportunities for the other 5%. Yes, it's lot more than just coding, and yes it's a lot more risky, but the opportunities are there.

As for me, I'm closing in on retirement, but at the same time building a new (not tech) business from scratch, because there's still value I can add, and a niche I can service.

I say this all to encourage current students. You can see the world as "done" or you can see it as an infant just waiting for you to come and add your unique value. And in 35 year's time feel free to encourage the next generation with your story.

(Many Greek fonts today don’t draw the accents and breathings that are used in older texts)