alt Hacker NewsI’m hearing this more and more from both students and teachers. It seems like everyone in education is frustrated and can’t figure out how to use AI for education productively yet.
TBH I’m also thinking about how to use AI at work for learning. (My work environment is 100% all-in on AI.) Everyone can see and admit that AI coding is making us lazier and that it produces too much code to do old-style line by line reviews. Some people are using agent teams to churn out millions of lines of code where there’s zero hope of reviewing it. We don’t yet know how to keep quality high and complexity low while doing agent coding, we’re just having them write lots of tests and hoping that when things break they’re easy to fix. Agents should get better at broad architecture in the future, but they’re definitely not there yet.
> The amount of work involved has also tripled
This has to be one of the big ironies of using AI. I’ve heard this from other students too. The problem is that old-style assignments where the level of difficulty was hand-crafted is way way too easy for an LLM, therefore teachers need to crank the level of difficulty so the student has to actually spend some time on the assignment. But LLMs are getting better every month and the difficulty is so high that no students can possibly do the assignment by hand and now small errors in assignment design can lead to large errors in effort and time required.
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AI has killed the cheap education model.
In that, 500 person frosh lectures are dead. 32 students per class, 6 classes a day are dead.
What remains? The Oxbridge model that has been going on for nearly a millennia.
Briefly: 4-10 students and a proctor. You do the reading/work, you meet a few times a week. The proctor facilitates discussion and guides students. Many schools do this, but not many students get to see it.
Why? Because it is very expensive. The proctor has to be at least a graduate in the same subject, likely having a graduate degree in it. These are small classes by design. And don;t even get started on the training that the proctors have to do to get ready and not be a lawsuit generation machine.
I feel this is really the only way forward. Which is almost maximally unfortunate.
Yes, 'Cheap' Big State University will still exist, but it's program will be so degraded by AI that it's graduates will be seen as worthless. While 'Very Expensive' Small Liberal Arts College with the Oxbridge model will guarantee that the students are at least minimally educated to bullshit well enough. Meaning that the rich and poor gap grows and grows.
> We don’t yet know how to keep quality high and complexity low while doing agent coding, we’re just having them write lots of tests and hoping that when things break they’re easy to fix
Implement more versions with different languages, frameworks, libraries and AI agents. Then you can do differential execution for testing, which is easier than imagining testing scenarios from pure code. You can fuzz or use production data (shadow mode execution) to get notified early of divergences.
Keeping a population of diverse replicas might be the simplest way to derisk AI code. When 2 replicas diverge an agent can decide - was it a bug in one of them, or was the spec unclear? Either way, if you fix a bug or clarify the spec you come ahead.
A separate class of problems is related to intent divergence. For that my solution is to keep a full log of all user messages during the lifetime of the project. Even 10,000 messages collected over weeks and months can be read and summarized in a few minutes. That means you can check for intent divergence with agents, but you always start from the raw source (your human messages) not from intermediate summaries and diverged code.
Combining the 2 ideas would make each replica agent derive the user intent separately from the same log.
I taught my Claude to teach me new skills, where I wanted to understand its work deeper. Specifically, I wanted to learn coccinelle semantic patching, so I told it to find potential places to apply it but withhold the solutions from me. Instead, it walks me through producing a patch myself.
> It seems like everyone in education is frustrated and can’t figure out how to use AI for education productively yet.
Oh, it's terrible. I'm a computer science instructor at a university (I have 20 years of industry experience prior) and it was already bad enough before trying to predict where the market was going to be 4 years in the future. But a year ago, it was tough to predict where the market was going to be in one month.
So yeah, we can teach all kinds of stuff. But is it the right stuff? With one month of visibility, who can tell?
But now I feel like it's settled down a little bit. And now I feel like I have more like 7 to 8 months of visibility. One thing that's helped is that we see the hiring differential between seniors and juniors. So now we can answer the question, what does the market want? It wants the expertise between junior and senior. And I'm confident it'll want that for at least the next 7-8 months.
Good luck cramming that into 4 years, though! I figure we have to try to bridge the gap as best we can. Eventually, seniors will become rare enough that the expense isn't worth it. It'll become better to hire cheaper most-qualified juniors.
There's still some seriously open-ended questions though. How much does coding matter, for example? If you ask senior devs who don't do any coding how much they rely on their coding expertise to make decisions, you'll get a zillion answers across the spectrum. This becomes even more true for senior devs who use AI for coding. Heck, ask 100 devs if it's important that you can even read code or not and see what comes out!
And then there's the question of how do you teach those systems level thinking skills? Historically, universities haven't taught those skills. You came out of the University with general problem solving skills in technology, and then at your job you were exposed to a small corner of the codebase to fix some bug. Gradually, over the years, you learn more and more of the codebase and become more and more senior. We have to get that into our curriculum. I'm working on that as we speak and will be working on that for the next several years, it looks like; even if my position vanishes, I'll keep attacking it—this is a tough problem that's fun to try to crack.
Anyway, I hope someday my forward visibility gets back up to 18 months. Won't that be amazing. I'd also like to buy some RAM. ;)