I have included the basic "I am a student -- help me learn, don't just do everything for me," but I also am trying out telling it to generate a .history folder with a markdown history of every prompt and a summary of the action take in response.
I _know_ there are some tools that offer the prompt history automatically, but I've told students they can use _whatever_ tool they want, but should let me know if the folder isn't showing up as they work.
The .history folder is required if they used AI and I intend to review it and try to give specific feedback to the students using it as too much of a crutch.
I just started this last Friday, so wish me luck!
However, I see from other comments on this post that I may need to include a CLAUDE.md as a copy (and could maybe just leave the .history part out of that version?).
If your agent isn't performing as expected but can otherwise see and describe the tools as you expect, your mental model of what the tools should be is probably wrong. Adjusting the system prompt can address this, but it quickly bloats and starts to turn into a game of whack-a-mole.
I've got an agent that talks to a very large data warehouse and the system prompt is somewhere around 100 tokens. Most of the important information lives in the user's request and in the environment.
How do you intend to assess your students?
I'm hoping they learn to use it as a tool instead of trying to offload all cognition to it.
This is a CS course targeted at non-majors, so thankfully the "fundamentals" aren't as critical as the overall themes and general skills.
It likely will. Half way through a session I routinely watch the agent append my rules to the top of its thinking only to do exactly what it said it wasn’t going to do after another minute of thinking.
It will then apologize profusely right before doing it again.
As others have said, use hooks.
When used correctly, they offer a huge advantage over those who don't use them and think they understand but remain superficial. I encourage you to ask even the most obvious questions.
This doesn't mean that this approach doesn't have value though. I think it very much does.
One way to indirectly enforce use of the AI agent guidelines is via an oral examination where the instructor and student look over their work together and talk about it. Students who have genuinely tried to learn and used AI as a learning tool via the agent guidelines should do a lot better in an oral exam than students who have used AI as a solution generator.
I adopted the oral exam (without agent guidelines) for a course i teach in the academic year just gone, it worked pretty well. Next term I intend to include the agent guidelines to give them clearer guardrails. Still ultimately optional, but if students choose to ignore them it's gonna be pretty obvious during our conversation.
I imagine this applies here, too, if they want to enforce it strictly.
How could you tell? I proctored. People cheat pretty frequently and other students are none the wiser. It really takes like 4 proctors if you want to do it right. Even then I'm sure the clever ones are slipping through. These were scantron though. Short response/essay format you'd be screwed if you didn't know your stuff.
>Cheating has become omnipresent. I don’t know a single person who hasn’t used A.I. to get through some assignment in college, yet the school was at first slow to realize how widespread this would become. As freshman year went on, some professors suggested that the “nuclear option” might be called for: allowing faculty to proctor in-person exams, a practice banned at the university for over a century to demonstrate “confidence in the honor” of students.
snip
>In junior year, 49 percent of the 849 computer science majors who responded to an annual campus survey said they would rather cheat on an exam than fail.
https://www.nytimes.com/2026/05/17/opinion/chatgpt-ai-colleg...
It turns out that it's much less memorable if you're too "clear and helpful", so nothing helpful sticks for students. A good teacher (tutor, educator, pick a word) challenges students and makes them the right amount of uncomfortable.
Teaching, fairness and measuring student performance might seem like similar goals, but it's just so very easy to make sure you succeed at one while messing up the others.
(They have the same content duplicated in an AGENTS.md as well - I really wish Anthropic would hurry up and teach Claude Code to check for that file too.)
Opencode is good enough for most workflows IME, even if it doesn’t have the kitchen sink of features as cc
@AGENTS.mdSurely such a trivial feature could be implemented in seconds using e.g. Claude? It's not about them not "hurrying up".
best to
a) adapt assignments so that agents are bad at producing solutions
b) have more scenarios where students have to do things in controlled environments. Universities managed to adapt to 'any solution you need is readily available online' so I don't think it will be that different to have several times a month/year where students have to go into a room with nothing but pencil and paper to prove what knowledge they have vs what they have the skills to access
For the linear algebra written exam it didn’t work as if you learned to solve the 4 previous years exams, you could be sure most of it was familiar, so you could just prepare for a few standard exercises without really understanding the content.
Our advanced algorithm course used a bit of a combination, with a project take home exam (knapsack like optimization problem - competing for the fastest implementation) combined with a two hour written exam with multiple choice answers, but again only with books, pencil and paper to get to the right answer. This I think could work today, having both the opened ended project + some multiple choice with pencil/paper.
Let's train people to use all the tools available to solve the hardest problems, rather than solving toy problems with a slide rule.
I don't think a 4 year postsecondary education is enough time to make a developer that can hit the ground running. Not if it's 100% of class time on CS theory. Nor if it were 4 years of vocational training and labwork that leaned heavy into AI. Nor some mix. We train on the job heavily, it's just not possible to fit everything into the sausage grinder.
So why not throw in some mandatory non-major electives? Take the time to do stuff that frustrates people who want uni to be a certificate mill. I don't care if green employees are experts at the exact narrow set of tools I use. I want them to be good at learning, and to have gotten most of the standard CS topics out of the way.
This is like saying first graders should learn to use calculators, not how to do arithmetic.
Some skills are foundational, and must be learned first in order to be able to solve harder problems. Skipping those skills because software can do them is moronic.
I bet most people would not steal even if they knew they could get away with it.
Universities should be places which are at the bleeding edge of development and providing society with the best new ideas/tech, etc has to offer. Junior workers should be hotbeds of exciting talent which have the ability to revolutionise industries.
By creating such milquetoast environments to study in, which are seemingly scared or unable to prepare people for the future, students are being done a disservice.
Far too many people are far too comfortable with their cushty positions, and it's not doing the youth any favours.
>In our tech-enabled, newly A.I.-powered world, students were increasingly fudging just about everything. They would embezzle dorm funds to spend on their friends and lie about having Covid to get the UberEats credits that the school offered to those in quarantine. Some kids I knew published a paper that claimed a groundbreaking new A.I. advancement. Online sleuths quickly pointed out that it appeared to be just a stolen Chinese model, to which the two Stanford co-authors responded by blaming the plagiarism on the third author.
>In junior year, 49 percent of the 849 computer science majors who responded to an annual campus survey said they would rather cheat on an exam than fail. A friend of mine captured the school’s ethos while we were discussing the tech hardware and other items our student club neglected to return to corporate sponsors. It was all, I recall her saying, “just a little bit of fraud.”
https://www.nytimes.com/2026/05/17/opinion/chatgpt-ai-colleg...
The onus should be on the instructor to make sure that the student ends up actually understanding and being able to code/solve problems that they pose without using coding agents.
Why? Because:
1. this is exactly what is going on in the real world. People are able to get AI to do whatever the hell they want, but the ones who just use it lazily end up with huge cognitive debts and codebases riddled with opaque bugs that they do not understand whatsoever. If we prevent students from confronting this temptation, then we are sort of coddling or shielding them from it, and not really preparing them to avoid pitfalls of this type.
2. you can actually learn a LOT by being given the answer, if you actually care to learn. i personally think it's pretty fucking lame to handicap a student's ability to learn in an attempt to prevent lazy abuse. isn't the whole point of a grade to measure how well you understand things? can't you have pop quizzes, assignments on a computer with no agent use, written tests, etc etc. to catch the lazy abusers? this is an unnecessary prevention of lazy abuse that unfairly handicaps learning
Even if you "actually care to learn", this is a huge mental shortcut and you're deceiving yourself if you think deep learning is happening from looking at the answer.
On top of that, the pressures to just finish the coursework and move on to your other homework due tomorrow seems pretty high. Your suggestion means we're no longer coddling/shielding students, but we also aren't actively helping them, are we?
> Your suggestion means we're no longer coddling/shielding students, but we also aren't actively helping them, are we?
My suggestion is just the former, it doesn't imply the latter.
That's a major reason why employers have traditionally valued degrees from research universities, even if they are not particularly highly ranked. Being able to thrive in an environment like that shows a degree of independence and initiative.
https://gist.github.com/1cg/a6c6f2276a1fe5ee172282580a44a7ac
please let me know if you make improvements, I'd love to iterate on it
Do you have further insights on AI and education since?
Getting fat is one thing, but getting stupid is another, and I really fear for the future of humanity when it becomes so easy to sidestep the processes that let us actually learn and grow because stuff like "using agent ai coding is trivial".
They shouldn't be thrown into a big soup with shaky aims.
We still - as a society - manage to have PE and driving as different subjects. The same can equally apply here.
The solution is to scale the difficulty of the objective measures. Expect far more from students.
Reorient the university around physical laboratories and timesharing resources no single student could afford. It's already like this in many STEM disciplines.
More internships, more networking, more large projects. Less trivial tests of knowledge and credentialism.
So now students are _required_ to use agents? That's a bit crazy
Would universities be paying the token cost? Is that you Dario?
A Claude subscription is like 1/5th the cost of one textbook.
I think we have a tendency to think the worst of your people. They frequently surprise me though.
To enable it, run /config > output styles > Learning
This seems unreasonable to me. One of the best uses of AI is that you can just tell your computer what to do in natural language and it does it. Running bash commands isn't part of the education, its busy work.
https://gist.github.com/1cg/a6c6f2276a1fe5ee172282580a44a7ac
> * Run bash commands
Students who prefer to use zsh keep winning.
It's kinda funny to think about various forms of code generation. From compilers to IDEs to parser generators to, now, LLMs. Even several higher level languages that compile to lower level languages are generative, essentially.
Still not a fan of LLMs, but it's always a good to remember that the concept isn't entirely new or unique.
Once they have graduated they will be on the job using LLMs and agents all day long, and their employers not only won't care they will be encouraging or requiring it.
There really needs to be diversity in delivery styles for different modules of courses according to their aims, with 'ai access' as a key variable.
If AI is allowed, it should be based on $x of usage/student, with an audit trail to prove no external funding was used, and module aims based on using AI to the max while conserving token use. Like actually creating wild, ambitious shit which takes cutting edge services to the max.
If AI is not allowed for a module, then it really needs to go back to the old skool, with handwritten exams, or coding using old machines and textbooks. Some skills, techniques, etc, really do need drilling.
Straddling the middle will help nobody, result in accusations, increase the burden on teaching staff, and result in a course without a realistic focus.
Though I guess if you're a big brand university, you don't really need to care about innovating. The money will keep pouring in. The whole further education sector is in dire need of a shake up.
During my undergrad it was normal to see people refer to Chegg solutions to get their answers, or as a friend for theirs.
Maybe there’s a reason my first CS professor wrote out Java code with pencil and paper I guess.
Reminds me of this: https://www.youtube.com/watch?v=k9ojK9Q_ARE
CS336: Language Modeling from Scratch
The "but we do not let them write code directly" is a smoke screen to appease critics and parents. Yes, hello parents, you pay for your offspring to become a mindless industry tool.