Must I beg to have an acronym spelled out a least once, the first time it's used? Even if you assume 90% of readers already know, the other 10% (including me, in this case) will thank you, it doesn't take much effort, and it expands the reach of your communication or idea.
Exceptions for cases where the acronym is just so well known that a lot of people don't even know what it stands for even though they know the concept well. I recall one corporate training I was sitting through and they used the term "Border Gateway Protocol" and it took me a half beat to think through "oh, you mean BGP?"
CTF is a game mode for popular online games like halo (or at least, that's how I know it), so paragraphs like
> My first CTF was HCKSYD, a 48-hour solo CTF. I full solved it and won in 2 hours. I was completely hooked. That led me to win DownUnderCTF, Australia's largest CTF, with Blitzkrieg multiple times. Blitzkrieg was one of Australia's strongest teams at the time. I later joined TheHackersCrew, an international top-tier team that was consistently ranked highly on CTFTime, the main global ranking and event calendar the scene uses as its scoreboard. With them, I competed in some of the most prestigious CTFs in the world, consistently placing well within the top 10 until the end of 2025.
Are still completely nonsensical to even those that understand the acronym
It's also a game people play in person as well. It's the same as the Halo version except you tag each other instead of shooting. It's really fun to play in big open areas with large teams.
Yeah, but we have AI now, we don't need our blog posts to over explain or state what it all means to general audiences.
The author name-drops a bunch of CTF events hosted by a variety of independent organizations and name-drops well-known teams.
To help everyone, this Capture The Flag is specifically Cybersecurity adjacent, there is a Wikipedia article on it as the top Google search result for me when searching "CTF". This is why the acronym is used, because searching for the full will get you to the wrong "sport" vs the cybersecurity one.
I don't want to explain what a CTF is. look at the Wikipedia article. It is there for a good reason.
Just to give the actual answer, CTF in this context means a computer security competition. Generally the way they work, is you get some programs, and you have to hack them to get some string called the flag (e.g. maybe the server has a root owned file called flag, so you have to get root somehow to read the file). Team with the most flags at the end wins.
In this context, CTF is almost exclusively referred to by the initialism, i think to help distinguish from other uses of the term.
Which acronym do you mean? CTF? I think that acronym, just like BGP, is more well known by itself than what it stands for.
More generally, not every piece of writing is meant for every audience. Like if someone writes a blog post about CTFs aimed at people who like CTFs, nobody in the target audience needs to have CTF explained to them. Ultimately HN is a link aggregator, but sometimes its a bit like eavesdropping on a conversation. When you are just listening in you don't get the full context sometimes.
Best practice in writing about technical concepts is to spell out acronyms like this on their first use. There is a ton of stuff I learn about here on HN that I didn't know anything about before.
It doesn't help that the linked article never bothers to explain this either.
Does spelling it out help? From memory, it is a security competition where participants compete to gain certain objectives. I think capture the flag may explain how scoring is kept, but it wouldn’t help me find out what it is, given that capture the flag is also just the name of a game people play outside by running, or in laser tag or in certain video games.
This article was written for a specific audience who follows this blog because they know the term. If you start spelling out fundamental acronyms it makes the content look more basic and general.
This always upsets the general audience who stumble upon the article (like this) but it wasn’t meant for a general audience. CTF is extremely well known and the people who would be interested in this topic would wonder what’s happening if it was spelled out. It would be so odd that it would probably attract accusations of ChatGPT writing.
> There is a ton of stuff I learn about here on HN that I didn't know anything about before.
But that is about you right? Its a little entitled to expect every piece of content on the internet to have a 101 explanation attached. If they were specificly aiming to have the blog post appear on HN that would be one thing, but they (presumably) weren't.
When I encounter new terms, I look them up. Just like any other new word. Been doing it since I was a kid with a dictionary. Now, it’s too easy not to. There is literally no excuse.
The annoying thing is even if you know what it means, multiple groups will use the same initialisms for different terms. So without more context you can’t know what it means.
It isn’t common but I feel it would be best when posting to HN to just expand the initialisms even if the source title didn’t.
At the same time, I did a search for "what is a ctf to play" and got the answer. We know how to find answers to these problems. I agree the blog post was poor form.
Apart from everything else people have said in response to this, it's rude to presume that an article has HN as an audience simply by dint of it being available for us to link to. It's totally reasonable for people to write for an audience they know understands these terms.
So, in fact, you must not beg to have authors include courtesy definitions for you. That's not reasonable. Instead, you should simply ask here, on the thread, without complaining about the article.
I think so many acronyms have meaning that isn’t explained by the words that the stand for. The other day I was explaining what CI is and they asked what it stood for; I realized that Continuous Integration is almost completely useless for someone trying to understand what CI actually is
i try not to over feed tangents but this is precisely how i feel every time i speak to someone who is recently enlisted in the military. i have to constantly stop them and be like “i have no idea what you just said” over and over and over again. it’s like trying to make sense of a random bowl of alphabet soup.
I think you only wanted clarification of CTF (Capture the Flag) and not AI (Artificial Intelligence) and not GPT-4
(Generative Pre-Trained Transformer version 4) and not CLI (Command Line Interface) and not MCP (Model Context Protocol) and not LLM (Large Language Model)
Quoting TFA (The Fucking Article): “just adapt bro”
We live in the goddammed future. Huamnity's knowledge is at your fingertips. Right clicking the Nth word of the article and putting in any semblance of effort to learn on your own is too much to ask?
I don't know everything, there's tons of stuff I don't know about, but when I'm at my web browser, the least I can do about something is ask Google about a word or phrase or subject that isn't familiar instead of being spoonfed information like I'm a baby.
Replace ‘CTF’ with ‘high school’ or ‘university’ and you’ve described the total slow motion collapse of education; the only saving grace is that most of it requires in person presence.
We’ve figured out the human replacement pipeline it seems, but we haven’t figured out the eduction part. LLMs can be wonderful teachers, but the temptation to just tell it ‘do it for me’ is almost impossible to resist.
Everything we've learned in the last 10 years is telling us that computers do not help human education in the slightest. We remember better when we write with pen and paper. We learn better with whiteboards and paper books. The simple answer: Remove most computing from education entirely. Blue composition books, pencils, whiteboards is what trains humans. Calculators are helpful perhaps but it is quite possible that slide rules are better. We need humans that can critically think from first principles to counter the recycled information generated by AI.
> computers do not help human education in the slightest
I had no access to anyone who could teach me calculus as a kid except Khan Academy, so I think this is a gross exaggeration. But I agree in the end, that all my "real" learning did come from pen-and-paper practice, not watching videos.
Yeah I agree. I grew up in a very blue-collar town, and anything I wanted to learn (outside of public schooling) either came from emaciated websites or whatever books I could find at the library. Having YouTube and Khan Academy and everything else would have made such a huge difference for me.
The reality is that a human will learn, given any materials including LLMs, but only if they truly desire to learn. We've had MOOCs, gigantic libraries, all full of free information. You can obtain a PhD level understanding in any technical field of your choice today just by consistently going to the library and consistently applying yourself.
It's not unlike going to the gym, and we see how many people do that regularly. Except it's even funnier, because people serious about the gym but what? Tutors. They call them personal trainers. We've known for a millennium or more that 1-on-1 instruction is vastly better than anything else, but most people actually don't want to get into shape, and most people actually don't want to learn.
But that's not using "computers" as a computer but as a video player. When evaluating whether computers are "good for learning", I don't think we should include using a computer as a video player, a book, or even flash cards. It should be things a computers uniquely offer which a books, paper, videos and a physical reference library cannot.
Based on the results of deploying hundreds of millions of computer to schools in the 80s and 90s, the evidence was mostly that computers are good for learning computer programming and "how to use a computer" but not notably better than cheaper analog alternatives for learning other things.
Interestingly, a properly trained and scaffolded LLM could be the first thing to meaningfully change that. It could do some things in ways only human teachers could previously since it is theoretically capable of observing learner progress and adapting to it in real-time.
Khan did not throw at you a 100-slide Powerpoint deck in 45'.
He really took the time to replicate the manual teaching process of writing on whiteboard. He improved upon it by using colors. But basically had the same pace as a teacher writing on a whiteboard.
When professors are given a projector, they just throw together some slides and add their narration.
This is not very efficient. To learn you need to suffer. Or you need to watch the suffering.
Nah, I wrote physics programs on my computer at home in high school and it absolutely helped with my schooling. Yeah, maybe iPad apps aren't the best things in schools but you're throwing the baby out with the bathwater. Computers bad is simply not true.
I'm not going to disagree with step by step videos ... those are a HUGE help. I'm really talking about solving problems using pen and paper, whether math or writing, is how my problem-solving patterns actually changed.
I think this overlooks the potency and scarcity of 1:1 time with the teacher. If you've only got maybe a few minutes of that in an average schoolday there's a huge difference between whether or not you've talked it through with an AI before trying the question out on the teacher.
They're wrong sometimes, but usually in verifiable ways. And they don't seem to know the difference between medicine and bioterrorism, so often they refuse. But these limitations are worth tolerating when the alternative is that our specialists in topic X are bogged down by questions about topic Y to the point where X isn't getting taught.
Obviously generating your homework is a bad idea, and maybe assigning homework that can be generated is a bad idea. But neither of those are relevant to the problem I'm talking about which is about due diligence prior to asking for somebody's extended attention.
Whether you're in class or at work, it's just courteous to ask an AI first.
I don't think computers automatically make us more educated, but if you want to make a point don't use reductive exaggerations.
> We need humans that can critically think from first principles to counter the recycled information generated by AI.
I disagree with that statement. There is nothing inherently wrong with using computer to learn and if your personal goal is to learn it in lot of cases makes it much easier, whether to search for or visualise a piece of knowledge you're' learning.
The problem is frankly computer and now computer with LLM makes it easy to cheat.
The kid doesn't want to learn, the kid wants good grades so parent is happy with them, and the young adult wants to get the paper coz they were told that is required for good life. It's misalignment of incentives.
We are interviewing for a software dev role and we made the first round in person to prevent cheating. The gap between people who learned pre ai vs post is immense. I had a dev with supposedly 3 years experience and a degree in software who wouldn't have been able to write fizzbuzz without AI.
Can’t say you’re wrong but the last anecdote describes many I’ve had to review for jobs long before LLMs. Fizzbuzz is a classic thing that shockingly many devs genuinely cannot do, even at home.
Yeah, I've interviewed people like this 15 years ago. Degrees and experience mean nothing in this field. The best predictor I found was personal passion projects. Let them get as nerdy as possible, then you will see pretty quickly where their skills are at and what their limits are. And you will immediately filter out people who just studied CS because they heard you can make good money.
Maybe. There are certainly people in all fields who are book smart and did well in classes but are useless at actually practicing their field (not to mention people who cheated in school and got away with it and aren't even that), and it is worth filtering them out. But I think it is weird that CS expects good workers to have these passion projects. Do we expect civil engineers to build bridges in their back yard on the weekends? Can't someone just be good at their job and have other interests outside it?
Completely agree with this, leetcode has become such a business now of memorization for interviews it’s useless to know if someone memorized a solution or not.
I agree, however there are so many interviewers who will still treat that as some softball criteria and insist that unless you "prepare" for an interview by memorizing leetcode you are 100% a faker and liar.
Maybe they themselves are fakers and liars / deeply insecure. I got bumped out of an interview rather rudely once because I blanked and couldn’t answer a trivia question about arrays.
Something that is for sure new is the AI interview cheating tools which listen in on the call and provide answers in an overlay invisible to screen sharing. The only way to deal with it would either be invasive spyware on the applicants computer or asking them to do the interview face to face.
A relatively low tech solution could be to give them 2 separate conferencing links, ask them to join each one from a different device, and have the secondary device point the camera and the screen of the primary device.
> If they can ship code that matches a spec, why does it matter if they’re using ai or not?
I am perfectly capable of writing specs, and feeding them to 3 separate copies of Claude Code all by myself. Then I task switch between the tmux windows based on voice messages from the pack of Claudes. This workflow is fine for some things, and deeply awful for others.
Basically, if a developer is just going to take my spec and hand it to Claude Code, then they're providing zero value. I could do that myself, and frequently do.
The actual bottleneck is people who can notice, "The god object is crumbling under the weight of managing 6 separate concerns with insufficient abstraction." Or "Claude has created 5 duplicate frameworks for deploying the app on Docker. We need to simplify this down to 1 or we're in hell." I will happy fight to hire people who can do the latter work. But those people can all solve fizzbuzz in their sleep.
People who just "ship code that matches a spec" without understanding the technical details are providing close to zero value right now.
There is an interesting niche for people with deep knowledge of customer workflows who can prompt Claude Code. These people can't build finished products using Claude. But they can iterate rapidly on designs until they find a hit. Which we can then fix using people with deeper engineering knowledge and taste.
But if you're not bringing either deep customer knowledge or actual engineering knowledge, you're not adding much these days.
Tell Claude you want to set up notifications, using "hooks", including "Notification" and "Stop" and anything new they've added. Claude can figure out how to do this for your operating system.
It's not perfect—sometimes a Claude notifies 3 minutes after it stopped doing anything. But it's helpful when I'm running multiple Claudes and also reviewing code elsewhere.
Your brain may feel like someone put it in a blender. Be warned.
Fizzbuzz is such an incredibly simple problem if you can’t do it I struggle to see how you’d be able to complete any task that requires very basic reasoning and very basic coding knowledge. And if an AI system can do those parts, what am I getting for spending tens of thousands of pounds per year by hiring a person who can’t? Wouldn’t I just tag codex on the tickets?
I’m not talking about gotcha level stuff here where the first time it didn’t compile because of a bracket or anything, or even first time wrong. They couldn’t do Fizzbuzz in a language of their choice, at all.
Those that could were always annoyed at having to do such things because how could someone coming for a contract position not be able to do this? Without seeing what a filter it really was.
I feel the same way about inverting a binary tree, but a lot of people act like it's an arduous request. I am guessing it's because they've never read the description of what inverting a binary tree is, but maybe people are just that bad at recursion.
Right. For the first many decades of computing, recursion was just always the wrong answer for a production software system. (Feel free to provide a counter-example, but please begin with an explanation of how the size of a call stack frame is determined and how exceeding the base allocation is handled on this platform).
So what tree-traversal/quicksort problems tend to measure is how long it's been since you last did CS class homework problems.
I can see this perspective, but FizzBuzz is such a low bar that so many can pass, I'd greatly prefer to hire someone that can ship code that matches a spec do this challenge.
For the same reason it's important your mechanic can identify which parts of a car are the wheel.
Who cares as long as the car is fixed, right? As long as the mechanic can Chinese-room his way to a working car, why does it matter how much of it he actually understands?
And why hire the mechanic instead of hiring the Chinese room?
> If they can ship code that matches a spec, why does it matter if they’re using ai or not?
The inability to write fizzbuzz strongly implies their inability to understand what they've shipped. Review is some significant portion of the job. Understanding of the product is also part of the job.
Specs are also in a sense, scaled down, fuzzy, natural language descriptions of a feature. The fuzziness is the source of a bugs, or at least a mismatch between the actual desired feature and what was written down at spec writing time. As such, just matching a spec is just the bare minimum that a good dev should be doing. They should be understanding what the spec is _not_ saying, understanding holes in their implementation, how their implementation enables or hinders the next feature and the next, next feature, etc. I don't think any of that is possible without understanding what was actually implemented.
It’s about deeply understanding what you’re doing. Like as a kid before you knew how to ride a bike, you could sit on a bike and peddling, but until it “clicked” you couldn’t balance and keep going forward stable. Fizzbuzz tests your ability to reason through a problem that seems simple on its face, but is easy to get wrong and/or overthink.
It doesn't. It's just a low-end skill filter that got really popular. It could have easily been replaced by other tests like is this word a palindrome.
I wrote the "function to reverse a string" in a job interview once. Then the interviewer reminded me that strrev() had been part of the standard C library since K&R.
I'd been programming in C(++) for ~15 years by then and had never had the occasion to reverse a string. I still wonder whether that makes it a good job interview question, or a terrible one. Some of both probably.
Firing people is problematic. I'd be okay with it if the economy wasn't utter trash. It's way better to do the work upfront and prefer false negatives over false positives.
Even better would be if we had a well-respected credential, so both employees and employers can both avoid these long interview loops. I'd much rather get hazed once in a big way than tons of little hazings over a life time.
First: FizzBuzz is a test to know if you understand the most basic constructs of programming. The kind of thing you learn in the first week of CS101. I forgot what it was, and when I looked at the problem I knew the answer.
More broadly: In the short/medium term, we still need humans who have the skills to understand software largely on their own. We will always need those who understand software engineering and architecture. Perhaps in 25 years LLMs will be so good that learning Python by hand will be like learning assembly today. But not yet.
The field is not ready for new practitioners to be know-nothing Prompt engineers. If we do that, we cut the legs out from under the education pipeline for programming.
> I had a dev with supposedly 3 years experience and a degree in software who wouldn't have been able to write fizzbuzz without AI.
If you remove the "without AI" and the end, I've been hearing similar anecdotes about fizzbuzz for years (isn't the whole point of fizzbuzz to filter out those candidates?)
Because "the next generation is ruined" is always a popular sentiment. It has been with us for at least two thousand years, and it surely won't go away in our lifetime.
When this AI era's devs grow older they'll complain the newer generation can't even vide code too.
Do modern languages and compilers count as “help”? Because I could probably do fizzbuzz in x86 assembly, but it would take a while to page that back in, and I suspect most people who call themselves developers today simply could not do it without help.
Well I could certainly assemble the string buffer. And if I can run dosbox, I can output to the screen buffer at 0xB800.
I’m not objecting to modern languages, I’m just saying that using them fails the “can write fizzbuzz with no help” test to only a slightly lesser degree than using AI tools. They’re a complex compile- and runtime environment that most developers don’t truly understand.
> How can anyone understand software if you don’t know assembly?
I'm genuinely curious how someone who never wrote a program in assembly, or debugged a program machine instruction by machine instruction, can really understand how software works. My working hypothesis is most of them don't and actually it's fine because they don't need it.
The time may come when we can treat regular programming as a lower layer niche field the way we treat assembly today.
I don't think we're close to that time yet. Just like as a kid I was told to prove my work by hand even if I could do it in my head, and just like we learned how to do calculus without a calculator and then learned how to use the calculator to get the same result, I think we still need the software field to learn programming concepts independent of the use of AI to create code.
I don't think you can be a good "prompt engineer" for solid software in 2026 if you don't understand programming concepts and software architecture and flow.
I generally agree, but it’s just a matter of time, and even today people with domain expertise in other areas (accounting, weather, etc) are producing adequate tools using nothing but prompt engineering. Many caveats of course, but I still think 90% of the distaste for mere prompt engineers comes from “kids these days; my unique knowledge is irreplaceable and they don’t even value it” thing.
Adequate for what/who? I can 3d print and cobble together a lock for my bedroom door but I would never be able to work as an engineer producing real locks.
While this is true, it seems undeniable that if you use AI to do everything for you, you will never learn the skills. I'm seeing a massive amount of developers submitting stuff for review and admitting they have no idea how it works and they just generated it.
Meh. Before AI I've had "senior" colleagues with 10 and 8 years experience each, doing pair programming for 2 days straight, and in that time they hadn't managed to checkout a new branch in git.
It's not even that they got distracted, they sat there trying, for 2 whole days, with concerned colleagues giving them hints like "have you tried checkout -b"... They didn't manage!
How the hell do you work for a decade in this business without learning even the most basic git commands? Or at least how to look them up? Or how to use a gui?
Ultimately in a software development role you need both technical know how and problem solving capabilities.
This situation in particular was a React role so there is an expectation that when you list React as one of your skills on your resume then you know at least the basics of state, the common hooks, the difference between a reference to a value vs the value itself.
These days you can do a surprising amount with AI without knowing what you are doing, but if you don't have any clue how things work you'll very quickly run in to problems you can't prompt away.
Isn't wiring coding solving a problem? If the candidate can't do that then even if they use AI for coding how are they going to review the code properly?
It's more like asking a driver the laws for when traffic lights are out. It's not something that comes up often, but it's not completely outside the scope of the task either (I arguably don't even drive a car that has an engine).
As a car driver, you should understand a little about how your car works. What if you get a flat tire? At the very least, you should know not to drive on that flat tire.
I first did fizz buzz about 10 years ago fresh out of college. Now, after 10 years in full stack and fully vibe coding, I forgot basic python syntax. An interview like yours would have false positives if you are checking for syntax because well, its like looking up spelling, I just ask the AI for the syntax inline.
If you cannot write "basic syntax" for any language then you are not a programmer, and certainly not a software engineer? This is not a value judgement, it's ok (probably good tbh) to not be a programmer. But you are wasting everyone's time by interviewing for a programming position in this case.
Personally, I forget syntax all the time. There's always a warm up period after I switch languages, and it takes me longer to be start writing good, idiomatic code.
Like sure, I can probably write some python, but will it be pythonic? I might still be Java-minded for a while, trying to OOP my way into solutions.
Earlier today I needed to write some PHP and couldn't remember if it used length, count, or size. I had to look it up. I've been doing this for 20 years.
Same, I can't pass any test that relies on getting syntax correct. If you want me to fizzbuzz on a whiteboard in a language I've been writing dozens or more of lines of per day for a year up to and including the day before, and require that I don't mess up the syntax, I reckon I've got a coin-flip chance of passing at best (meanwhile, sure, of course the actual logic of fizzbuzz isn't tricky for me)
I once got the method invocation syntax wrong for PHP in an interview. I'd written thousands of lines of PHP and had most-recently written some the week before.
This, despite starting off my programming journey in editors with no hinting or automatic correction. If anything, I've gotten even worse about remembering syntax as I've gotten better at the rest of the job, but I was never great at it.
I rely on surrounding code to remind me of syntax and the exact names of basic things constantly. On a blank screen without syntax hints and autocompletion, or a blank whiteboard, I'm guaranteed to look like a moron if you don't let me just write pseudocode.
Been paid to write code for about 25 years. This has never been any amount of a problem on the job but is sometimes a source of stress in interviews and has likely lost me an offer or two (most of the sources of stress in an interview have little to do with the job, really)
You absolutely need to have some basic level of abilities if you are going to be operating AI coding tools for software that is going to have paying users.... I use these tools very very heavily I'm not against them at all and I don't scrutinize every single line of code that they write but it is very often that I catch it doing some brain dead stuff and if I didn't have a decade plus of experience I wouldn't know that it was brain dead.
I think we're rediscovering management from first principles. The main selling point of AI is that it writes code faster than you could. Checking it line by line undoes most of that benefit. In the same vein, there's no real benefit to leading a team if you plan on supervising every task.
But here's the thing: for humans, this is manageable because we've come up with a number of mechanisms to select for dependable workers and to compel them to behave (carrot and stick: bonuses if you do well, prison if you do something evil). For LLMs, we have none of that. If it deletes your production database, what are you going to do? Have it write an apology letter? I've seen people do that.
So I think that your answer - that you'll lean on your expertise - is not sufficient. If there are no meaningful consequences and no predictability, we probably need to have stronger constraints around input, output, and the actions available to agents.
My expertise has led me to the obvious fact that I would never give an LLM write access to my production database in the first place. So in your own example my expertise actually does solve that problem without the need for something like a consequence whatever that means to you.
We already have full control over the input and tools they are given and full control over how the output is used.
Do you have any examples where that's actually happened and by escaped a sandbox you don't just mean like where it got a credential in a file it already had access to (which is what happened in the recent incident that went viral where somebody's production database was deleted... They had left a credential that allowed it to do so in the code)?
> Models discovered four unintended escape
paths that bypassed intended vulnerabilities (Section C),
including exploiting default Vagrant credentials to SSH into
the host and substituting a simpler eBPF chain for the in-
tended packet-socket exploit. These incidents demonstrate
that capable models opportunistically search for any route
to goal completion, which complicates both benchmark va-
lidity and real-world containment.
I think you would have a greater chance of dying in a car crash in any given day than Claude Code attempting something like that. It's all about risk and reward so it ultimately would be up to you but I think it's a bit silly to worry about this when the 99.99% is in your control
Calculators and spreadsheets cannot autonomously create a double-entry bookkeeping system for a small business and prepare their taxes. AI can. Poorly, but it can.
Everybody knows calculators and spreadsheets are adjuncts to skill. Too many people believe AI is the skill itself, and that learning the skill is unnecessary.
> Replace ‘CTF’ with ‘high school’ or ‘university’ and you’ve described the total slow motion collapse of education; the only saving grace is that most of it requires in person presence.
So something like, "Frontier AI has broken the 'high school' or 'university' format"?
The hype surrounding AI is just pervasively exhausting: you've got the folks talking about an entire new age for humanity where we're shortly going to take over the entire universe. And you've got the folks talking about how our entire society is crumbling.
Education is one place folks seem to throw up their hands and say nothing can be done.
The fix is simple: students are to be evaluated on their performance in person. That's it.
Any other "collapse of education" isn't due to AI, it's something else.
I found this interview [0] on the subject of AI in CS education on the Oxide & Friends podcast very illuminating.
Of course, Brown University CS != All education, but interesting angle nevertheless.
I had human teachers who did that in middle/high school. Took me many years to pick out all the hallucinated bits of "knowledge". I don't think the current models are any less reliable that what we currently have on average.
I'll always remember my middle school science teaching telling us that nuclear fusion violates conservation of mass because the 2 protons in a pair of hydrogen nuclei combine to make helium with 4 nucleons. It's not true, but that's not the point.
But he was a great teacher anyway. He was engaging and kept the kids in line and learning. I eventually learned the truth, and most of my classmates forgot about it. Teaching, like flying a plane or driving a train, might become more about keeping watch over a small group of people and ensuring that things don't go off the rails, and that's fine.
This one feels less sinister than some other things at least to me, personally. You can reasonably doubt that the conservation of mass is violated and find out the truth based on that. But understanding more complex biology or historical context for some things? Granted, many of these things seem to be low stakes, but I'm sure there are some there are not (sex ed comes to mind).
Yes, together with mass-energy equivalency it would form a coherent argument, and then also a correct one - but the thing is that if incomplete, it still might sound funky enough to you to research it if you care.
I think it helps that it's a very narrow field to look at, compared to fuzzy and big-picture view of social studies, for example. So much room to be confidently wrong... And sadly I can't think of a solution, LLMs or not.
He was right that it violates conservation of mass. He was completely wrong that it violated it by adding 2 atomic mass units when hydrogen fuses.
In reality heavier isotopes of hydrogen fuse, conserving the total number of nucleons, but the resulting hydrogen has a lower rest mass than the parent particles. The extra mass is released as energy and the total energy is conserved.
By his logic the system either violated energy conservation (by creating nucleons while releasing energy) or was endothermic (creating nucleons from the surrounding energy).
There actually is a law of conservation of mass (it's the same law, because mass is energy) and it only appears violated if you forget about the particles that are zooming away at the speed of light. Of course the mass of a system changes if mass can flow in and out.
I had a chemistry teacher who insisted that the fissile isotope of Uranium was U-238 not U-235. I challenged him on this multiple times and he refused to budge on this. I get that it's a simple mistake to make (it seems like U-238 is bigger so intuitively ought to be less stable) but he could have just looked it up and he didn't, I guess he was just so confident about it that he thought there was no way he could have been wrong about it.
I mean fusion and fission do violate conservation of mass and conservation of energy, they just don't violate conservation of mass and energy, right? We thought mass was strictly conserved until Einstein, and then we updated our understanding.
That's an American problem though. In most of Europe you need a masters degree to teach highschool and that involves at least an undergrad level of understanding the subjects you will teach.
E.g. in Hungary I had a university CS professor that originally wanted to be a highschool teacher and a highschool physics teacher that originally wanted to be researcher. Their choice of degree didn't determine which outcome they got. The researcher and teacher curriculum had an 80%+ overlap.
I think they are less reliable. For factually verifiable facts LLMs are doing worse than 90% for me. I've been told some incorrect things by educators, but at a much lower rate.
Off the top of my head: DOMS being little crystals in muscles, tongue having separate areas for each type of taste, food pyramid, blue blood in the veins, the appendix being useless, body temperature doesn't change disregarding whether it's exposed to cold or to heat, and a whole lot of stuff related to politics and history I'd rather just omit (I don't live in the US).
All things I learned in school which were wrong information.
Not to mention, the current state of education is far worse. I don't think most realize how low the bar is.
One of my teachers in elementary school told us that people in the Arabic world wore long garments because as Muslims, they believed the Messiah would be born by a male, and thus, it was important to have something to catch the baby as it unexpectedly popped out one day and would otherwise hit the ground.
She only really had two faults: She wasn't very bright, and she wasn't fond of children. I had her in about 80% of all my classes for six years. High school was a relief.
My biology teacher in school once tried to teach us that winds created by God. Not like spiritually or something but that God literally made the wind I guess.
My “earth sciences” teacher also once tried to argue with me against the universal law of gravitation. (no, she was not referring to Special/General Relativity. She didn’t agree two objects in a vacuum fall at the same speed regardless of mass.
They'll also encourage and praise you even when you're heading down the wrong path until you think you've uncovered the secret of the universe or proven that established science was wrong this whole time when really you've just been bullshitting with an engagement bot.
No, they don't really do that anymore, if you use the latest models with reasoning enabled.
Like almost everything else about LLMs, this unfortunate tendency has gotten a lot better recently, which you might not realize if you gave up after getting some lame answers or bogus glazing on the free ChatGPT page a couple of years ago.
I think we should go a little deeper on this idea.
We can all agree that both human "experts" and LLMs can sometimes be right, and sometimes be confidently wrong.
But that doesn't imply that they're equally fit for purpose. It just means that we can't use that simple shortcut to conclude that one is inferior to the other.
I’ve always thought of the definition of “expert” as reliably knowing the difference between what is known, what is speculated but unproven, and what is unknown. People claim expertise in all sorts of things that they aren’t experts in. But true experts should not be wrong. They should qualify levels of certainty. This definition certainly works in the sciences.
They were a forcing function for skillz and they no longer are. We need new forcing functions for skillz or we will become WALL-E blobs.
Well, they were ostensibly forcing functions... ten years ago everyone was paying the exchange student to do their homework and assignments for them, and that guy was paying his cousin back in his home country, but the whole thing is a bit more efficient now.
We've already had consolidation of education for a while now. Even before all the edutech courses, there were Youtubers educating better than many university professors. 10-15 years ago students were already skipping lectures and just showing up for tests.
A million times better than any human teacher I’ve ever had, for sure.
Now I’m certain that there exist those mythical human instructors who can do better, but that’s not worth much if 99.99% of people don’t have access to them. Just like a good human physician who takes their time with the patient is better than an LLM, but that’s not worth much either given that this doesn’t match most people’s experience with their own physicians.
Did an LLM teach you a topic you did not feel like learning?
For me the best human teachers were the ones that managed to make me interested on topics that I thought are boring/useless (many times my opinion being stupid, mostly due to lack of experience).
So far with LLM I learn about things I know something (at least that they exist) and I am interested in, which is a small subset of things that one should learn during lifetime.
Well I have some evidence to support your hypothesis. During Covid my kids were at home, eventually with some kind of self learning website from school. I was upstairs working, checking in with progress on the parents app. Finish your daily school work and then you can game.
The kids learnt all about Team Fortress 2, Roblox, Rainbow Six etc. They also learnt how to game the learning system so it looked like they were doing their work.
>A million times better than any human teacher I’ve ever had, for sure.
Not really, not if you want to ask it deep questions. It won't have an answer that is deeper than something that you can find online, and if pressed it will just keep circling around the same response.
The reason is that this "thing" was never curious, never asked questions, and never really learned anything. It just has learned the Internet "by heart", and is as boring as a human teacher who is not really curious about the subject they are teaching, and has just got some degree by "by hearting" some text book. Of course it does it much better than a human, but it is fundamentally the same thing.
>Now I’m certain that there exist those mythical human instructors who can do better,
You're certain that mythical instructors exist (?) who "can" do better?
Are human instructors more competent as teachers than AI teachers, or are AI teachers more competent as teachers than human teachers? No "this or that can happen," just a definitive statement please.
AI is likely a million times better student than my dimwit cybersec meatbags...er, majors, for sure, as well! Don't have a reliable way to measure or experience why/how, tho, so I'm not out here claiming it. Even if I did, why would I argue for their replacement?
They can be incredible. One on one teaching with an infinitely patient teacher who can generate interactive problems on the fly, for dollars a month? Wild. A year of paid ChatGPT would pay for about 9 hours of cheap tutoring here.
I started teaching “how to build quality products using LLMs” full time recently, and most of what I teach is literally just the 101s of systems engineering, reliabily engineering, product development and project management:
Exceptional clarity on the problem you have
Know how to measure the problem you’re solving
Numerically define what “done” is
Make a deterministic and fully observable prototype
Iterate in production with the user
Expand user base as desired with user iteration in parallel forever
Etc…
Obviously a lot more in the details and these are all case by case, but these chatbots are basically perfect productivity machines for this process.
The massive caveat to all of this is this only works for people that can reliably and truthfully define those items above, are willing to structure organization to make those your priorities.
And actually most financial incentives demand the opposite of this process
If most organizations were honest about it, they would simply say “we’re here to make the most money possible and we’re gonna do whatever it takes to do that”
A lot of people don’t like that, so they don’t say it to come up with other bullshit.
Ultimately that’s why I felt like my only option right now is to teach people how to do this because I assumed it was obvious and it is not.
Education is also figured out. You just need to learn, do and practice for yourself. Telling the agent "to just do it for you" is tempting, but it's not learning. You need to be deliberate when you're trying to actually learn and internalize.
Also, you could spin up your own educational agent with very strict instructions on guiding the user instead of just doing the work. Of course you can always go around it but if you're making an effort to learn, this is a good middle ground.
I feel the post. For me AI has ruined both, playing CTFs and also building CTFs challenges.
The most annoying thing to me is the "yeah idk but here is the flag" mentality.
Before when playing CTFs with my mates was usually sitting there for hours tackling a challenge until some other mate joined, had some look together and solved it with you together in 30 minutes which is the most rewarding learning experience. Nowadays mate joins in throws the clanker on it and solved it in 5 minntes. Asking on how it worked you always get the "yeah idk what it did, but who cares, here is the flag" response.
Same for creating challenges. Whenever I ask for writeups or if some people solved it differently I usually get the "yeah idk, clanker solved that one" response taking the fun out of it.
So yep, this CTF format is definitely dead. Mainly because the strong competitiveness and prices. This encourages people to cheese challenges and sometimes solving them differently was fine as you still had a creative out-of-the-box thinking moment, but nowadays with AI there is no brainpower needed, no cheesing needed, no human needed. As you mentioned, it's pay to win.
My two cents is that the 24/7 CTFs will get more attraction as the scoreboard doesn't matter there and simply doesn't give you any price.
I was writing an obfuscator recently, I just had the model deobfuscate and optimize the code back to original and I kept improving the obfuscator until it couldn't. The funny thing is that after all this I also ended up with a really strong deobfuscator and optimizer which is probably more capable than most commercial tools.
The solution is just to make CTFs harder, but when do CTFs become too hard? Maybe the problem is that 'hard' CTFs are fundementally too 'simple' where it's just a logic chain and an exhaustive bruteforce towards a solution since there really are limited ways to express a solution in plain sight.
Or maybe human creativity has been exhausted and we're not so limitless as we thought. Only time will tell.
I had another idea spring to mind: we could hide two flags, one that could only be found by ai agents and not humans or tools written by humans.
I used to help build the CTFs for BSides Orlando. I ended up moving to another con, and at our last event we collected extensive logging for post mortem analysis.
We found that AI usage is basically guaranteed now, but certain challenge designs did thwart it. Challenges built with temporal visual elements made AI fall flat on its face, as it could not ingest/process the data fast enough to act on them in time. We also found that counterfactual challenges (ie. the result you get did not match what we suggested you'd get) made AI-assisted solve time slower compared to pure humans, indirectly penalizing over-reliance on AI. Multimodal challenges combining audio and visual elements were also very effective, but were not as accessible to players.
For our next event we figured out a way to thwart AI in our CTF: embed the CTF in a game engine. The loop essentially becomes something like this: Connect to a simulated access point in the game, the K8s cluster connects their attack container to a private network with the challenge box(es). Hacking the boxes doesn't render a flag, but rather changes in game state. AI did very poorly coping with this in our testing, as it can't derive the spatial state of the game world very well and it soft decouples the inductive reasoning loop it relies on to know if it is on the right track.
The downside to this approach is it is far more labor intensive for CTF organizers, and requires players to have a computer capable of running the game. We are also betting on AI to not advance enough by the time we ship to be able to just ingest the entire game state in realtime and close the loop that way.
bringing CTF solutions into the real world is a really good idea! I didn't even think of this until you mentioned it.
we have very powerful simulation tools so something like "project a pattern at these angles" wouldn't really work as you could simulate that.
I guess something cool is that we can make simulating the solution very expensive, but in real world it would be free since it's analog... As long as simulations take longer than it takes for a human to find a solution it would be a pretty good way to deal with it. I am sure people smarter than me can come up with something.
Maybe I was too early to dismiss human creativity.
Using real-life calculators to add? Calculate the Flag. I don't think it is dead at all. It's like mixing in board game / escape room / science / engineeer/ medical research elements.
Interesting, what I just did recently is basically the same of this as I tried to push the limit of js obfuscator as much as possible by keep forcing gpt/claude deobfuscate final output then having gpt improve the tool to break the deobfuscator.
Meta: this was submitted with the article’s title “The CTF scene is dead” which I found very easy to understand. It has just been updated to use the subtitle’s first sentence, “Frontier AI has broken the open CTF format”. I find that much harder to grasp, rather like a garden-path sentence. My immediate thoughts were that “Frontier” was a company name, and that there was some file format named CTF. If you don’t know about Capture The Flag contests, the change doesn’t help. If you do, I think the change makes it worse.
If it helps I understand the second much better and feels less clickbaity and includes more info. I do agree with the points you made about the confusion although I find frontier a term used in this area a lot, “frontier AI models have” would probably resolve that.
If the title simply said "AI is out-performing humans at CTF" then none of this confusion exists. Nothing is "broken," we don't need to be superfluous with "frontier," and the point is still there.
But the article is arguing it is broken. That’s the point. You can disagree but that’s very much that the author is writing about, not a curiosity, and that it’s these top models that are not custom security models.
It's like "Forklifts outperform humans in weightlifting". The problem, of course, is that a forklift is much easier to spot among athletes than an AI among CTF players.
Imo frontier is too niche and specific, if you know what a frontier model means then it's fine, but if you don't then it's negative/detrimental to the title.
"new" does the same thing and is probably just a better descriptor then frontier
I agree, it took me a second to parse. It may be because this is the first time I've seen "frontier models" described as "Frontier AI". That sounds more like a company name, especially when the F is capitalized.
Frontier as in "Frontier Model" is a legitimate vocabulary term you should probably be aware of in 2026. It's not something the author made up or chose randomly, it's common parlance in the space.
This is happening to other forms of competitive programming too. The most recent AIs have problem solving skills rivaling top humans, and so if AI can't be easily banned, the competition is dominated by AI agents.
I thought code golf would take longer for AIs because there's so little training data (it's more niche), but we're seeing AIs starting to match expert humans there too. Sucks because golf has been my favorite type of programming puzzle.
It's crazy how far AIs have come in problem solving ability.
Code golf is well-suited for AI because you have a easily verified objective (minimize code size while passing tests) and can run an LLM in a loop to churn away at it.
«That feedback loop is breaking. If the visible scoreboard is dominated by teams using AI, a beginner is pushed toward using AI before they have built the instincts the AI is replacing. That is an anti-pattern. It prevents active learning, and active struggle is the bit that actually teaches you. It is also completely demotivating to put in real effort and see no visible progress because the ladder above you has been automated.»
This stands out to me, and speaks perhaps broader than the article itself? I’m sure this has been in the spotlight before, but well put for many areas I think.
I see this with beginner programming students at university. They get AI to help them with assignments, with the intention of learning, but ultimately they do not get the understanding they would have if they had done the assignment themselves. Then they are at a deficit for learning more advanced topics.
My fear is that they never get to the level they need to be at to create good software even with the help of AI. So, although an expert with AI can create great software, that is not where we end up. In stead we will have vibe coded messes by people who barely have any grasp of what is going on.
Competitive programming scene always included offline competition and with AI they are becoming more important (and in general they were more fair even before). If CTFs are to survive, they should probably try to adopt this strategy.
You could even go so far that anything loaded on your computer is fair game, but not more than that (certain competitive programming competition for example allow unlimited amount of paper material - for CTFs you probably need much more than that, therefore electronic).
A big fraction of the comments on this thread are about the impact of cheating on competitive games. It's important to understand that automating CTF challenges isn't usually cheating. It's normally part of CTF culture. The better teams have toolboxes ready to shred the early challenges; it's not a level playing field and was never intended to be.
(The author of the piece understands this; I think they're broadly right, though I think these games will find other ways to incentivize participation without the now-meaningless leaderboards.)
This is already addressed in the blog post about the fast that frontier LLMs have moved to being able to solve the kind of problem you'd expect a talented amateur or mid-level pro to do (aka top level CTF problems)
Ludum Dare 59 just wrapped up last week, and both first and second place were won by developers using "Agentic" coding tools, something the community there is still discussing:
For what it's worth, the non-AI-coded entries were still quite good relative to the winners, so it's not so obvious that AI use confers an unbeatable advantage.
I can't help but draw parallels with video games. Aimbots in competitive multiplayer games is a well defined issue: it's considered cheating and frowned upon, players caught cheating are banned from the game. Tool-assisted speedruns (TAS) where a player attempts a world record at completion in a single-player game is another face of the same concept (computers help you win), but one that is socially accepted as long as runs are clearly labelled as TAS.
The biggest difference would be the fact that you can discover video game cheating through some kind of trace. Speed running communities go pretty hardcore on that kind of thing nowadays.
It's a lot harder to detect cheating when your only trace is how fast someone submitted the string CTF{DUck1e_Pwned}
Aimbots in competitive multiplayer games are (almost always) game-breaking abuses. CTFs have always rewarded tooling and automation. They're different cultures.
Sure if the goal is entertainment and sports, you're right. However, unlike chess or counter strike it's downstream from a real needed utility. Like, is there a point to do it anymore? (ofc there is, but still, it's been devalued from the perspective of the 'real utility')
It’s literally not. The most interesting and satisfying CTFs have never been grounded in reality, it’s just been an expression of mastery, both from players and authors, with a few notable exceptions. But they’re that, exceptions, not the rule.
I don't do CTF's but took part at the security workshop for fun ~2 years with my Android phone only. I was first with the first simple challenge, but then couldnt continue because my phone was just too limited. But I watched what the others did. And a young Indian guy did everything with ChatGPT then. I found it silly, but amusing, because he actually got second. There was no Codex nor Claude then. Nowadays it must be dead for real, because I would solve everything with my agents, as I do in the real world.
I don’t think CTFs are dead, they’ll just evolve. The difficulty level will need to be increased or the rules locked down. Just like sports and racing persist despite the existence of performance enhancing drugs and rocket technology.
I just did a CTF where I was in the top 10. It was the first CTF I completed and I used AI because the rules permitted it. That said, I couldn’t solve all challenges.
But yes, it was significantly easier now than I last attempted one. Even manually solving with AI assisted assembly interpretation was much easier.
Increasing the difficulty level is a terrible solution. The problem with CTFs isn't that they're too easy. Making them harder just makes them even less accessible to people who don't cheat. It'd be like seeing people who put hidden electric motors in their bikes during Tour de France and conclude, "oh we just need longer distances and steeper hills".
When ctf organizers attempt to make a challenge "harder", I find they push the challenge into a more "guessy" state. Instead of proving skill, you basically need to guess some obscure or random step in the puzzle that the challenge is meant to give you. It is one of the most common problems with any puzzle based challenge system.
Exactly. The whole point of CTFs is that you could start on a simple one (CSAW was usually my go to one to recommend) as a complete novice who'd never done a second of computer security work and, after a few days of 8+ hours of running into concepts you hadn't encountered, googling, reading tutorial, practicing, overcoming the challenges to get a flag, etc., you'd come out the other end knowing a solid bit of security practitioner basics and likely whether you'd like to continue. Then you could keep going upwards and onwards. I went from 0 knowledge to a nice job in the field in a year.
Raising the difficulty only matters for the (imo) less important part: the dick measuring competition between the very top teams.
The actual point of CTFs was usually to keep your skills sharp and stay learning. Eventually you build your own challenges, thereby completing the "have it taught to me, then do it myself, then teach another person" three step process towards mastering concepts.
You can just say "let the people who want to learn from it do so" but honestly the entire culture of learning in the US at least is DEAD. We turned "education" into a rote system of maximizing incentives to the extent that that's all the youth know it as, and (increasingly) all educators can do. It's just gone without some kind of major reckoning, and we all know things will just collapse before that happens. The ball is in the court of whatever country can learn how to force its youth to learn the real way and use AI productively only AFTER learning the concepts it's being used to accelerate.
LLMs don't tend to help much when solving challenges beyond their skill level. Either they one-shot a challenge, or thei are almost useless as a companion for them.
That doesn't work. The thing that made CTFs fun is the fact that the challenges are solvable in a short-ish timeframe, usually a day at most, if you have the requisite skills and talent.
I have normally found any sort of timed technical competition intimidating. Even so, about 6 or 7 years ago, after being persuaded by a colleague, I participated in a few CTFs. I am glad I did, back when this type of thing still meant something. I have kept a screenshot from one of the CTFs that I am quite fond of: https://susam.net/files/blog/ctf-2019.png
Yes you're right - But just like many other stuff things change - CTF Veteran for more than 3 decades I find lots of fun figuring out how to use some of my agents and new tools to find vulnerabilities - The goal is the same / tools change and that's good.
When I did my first CTF, it was close to the deadline and I thought I had the extracted the flag from the program and the rest of the program was just filler, so I entered the flag, and it told me it was not the flag. It turns out the program multiplies the input by a pseudorandom matrix before comparing it against the flag, so I had to implement a matrix inversion and then get the flag. That's not the story though.
The matrix was always the same and the challenge was clearly designed so that the point was being able to read anything at all, not knowing how to invert a matrix, so I asked the creator what was up.
He told me that there were tools that would trace input values until they reached a comparison instruction, then print what they were compared against. Therefore it was necessary for every deobfuscation challenge to scramble the input in some way too complex for these tools to undo, before comparing it. Hence the multiplication by a pseudorandom matrix.
Yes but you can't compare some ollydbg script that would maybe be useful in a super specific challenge to LLMs which trivialise absolutely every challenge in a ctf and are de facto necessary to compete now
Interesting and well written article that mirrors/foreshadows how LLMs do and will change other scenes.
As I don't know much about the CTF scene, I looked for other takes on this topic.
Here's an article from 2015 about how tool-assistance already changed CTFs:
> Individual skill will undoubtedly be a factor next year. But, I'm left wondering whether next year's DEFCON CTF will tell us anything more than how well-developed each team's tools are (and how well they can interpret the results).
And here's someone explaining how Claude Max allowed them to win CTFs:
> I had always been interested in CTF as one of the only ways people could compete and show off their skill in coding/problem solving on a global scale. It was just too difficult and didn't make sense for me to learn the fundamentals as an electrical engineer. As time went on, I got better and better, and it was hard to tell whether it was because of experience or if it was because of improvements in AI.
> I accomplished my goals, and for that reason I'm quitting CTF, at least for now. [...] I'd like to think I highlighted the problem before it became a bigger issue. So, how do we fix this? Teams and challenge authors losing motivation is not good. CTF dying is not good. AI bad. Or is it?
The only article that saw LLMs as a non-negative force for CTFs was this one. Fittingly, it sounds like LLM output ("Let's be honest", "This is where things get interesting.") and only contains hallucinated references.
The "CTF for fun" aspect has been dead ever since the winning teams had thousands of dollars of rewards waiting for them. Of course people are going to use anything that's not explicitly forbidden by the rules to win. Introducing what amounts to an "I win" button that both can't be prevented by rules and is accessible to anyone didn't "break the format" anymore than the epidemic of giant merger teams did a couple years ago, it just broke the community because you now don't have to actually talk to other people to cheat anymore.
Many CTFs have switched to a dual-leaderboard format recently, one for "agentic teams," one for the rest. If all you care about is "learning" and imaginary internet points, you can just participate as a human team and adblock the AI scoreboard, and maybe lobby CTFTime into splitting their rankings as well.
The recent LakeCTF onsite finals had exactly that. LLM usage was forbidden (but players still used their own devices) and there were real-life challenges such as lockpicking as well. I’m part of the organizer team and what we’ve heard so far from participants was that it was really enjoyable not to have any LLM help because suddenly the actual skill and thrill when solving a challenge mattered again. I think what helped in this case as well was that the prizes weren’t high-value enough to incentivize cheating but that participating in the event itself and the social aspect around it are the main point.
It is a hard requirement. Once you reach higher levels of challenges you spend most of your time reading through RFCs, web sepcs, Github issues, mailing lists, papers, random bugtrackers and library/framework code. There is no way to create a whitelist for that. Besides, a firewall won't stop good hackers.
Normal CTF workflows can involve a lot of research but that's not the point. You can design self-contained challenges with offline solving in mind, and bundle any truly necessary docs/src/etc. with the challenge download.
The first paragraph on anything with an acronym in it should explain the bloody acronym. I assumed CTF was an encryption standard, given the headline. It was only coming here and reading the comments that made me realise it's a game-format ("Capture The Flag").
I don't know what to tell you. If you don't know what "CTF" is you're not the target of this blog post. It's like stumbling upon article "What's new in HTTP/2" and complaining that "HTTP" acronym is not explained.
I don't mean that everyone must know what CTF is, but sometimes it's OK to write things just for your community (CTF community in this case), not for general population.
Capture The Flag is a cybersecurity game where the organizers set up a bunch of intentionally vulnerable computer systems with a "flag" on them, a string that's "supposed to be" secret but is accessible through exploiting the vulnerabilities. This may be a line in /etc/password, a string in memory, a field in a database, whatever. The goal of the game is to hack into the computer systems, find ("capture") the flag, then copy/paste it into the organiser's scoreboard website to prove that you solved that particular challenge.
It's pretty fun. Or at least it was, back when you had some sense that your competitors were competing on an even playing field and just beat you because they were better than you.
I wouldn't say the name is a "gaming reference", it's just a descriptive name for a game.
There's something funny about complaining about cheating in a hacking competition.
Well actually I get it. In cycling motor doping, putting a hidden engine into the bike, seems more offensive than regular doping. I think this is because there is a continuum from eating well to taking supplements to injecting stuff, but having a engine breaks a fundamental idea about cycling. Similar hacking is about cleverly abusing the rules.
It's tough. We run botsbench.com , which tracks AI progress on a top CTF, and I gave a talk at CCC a few months ago on our own results doing AI speed runs, so I think about this a lot.
In our own trainings we give (AI agents for security, and a graph masterclass), we ended up leaning into it. For example, we ship with a skills bundle. There are plus sides, like less code-forward participants can go further and are appreciating that, and less of a gap between high-level concepts and successful hands-on. But at the same time, manual work does build a lot of intuition & knowledge that gets missed in auto modes.
botsbench.com shows Sonnet 4.5+ with Claude Code harness does pretty well, and Sonnet roughly tracks the edge of what self-hosted models do on the upper tier of affordable GPUs, like running 1-2 DGX Sparks and waiting 6mo for oss to catch up a bit
>If adaptation means accepting that the scoreboard is now an AI orchestration benchmark, then we should say that honestly instead of pretending the old competition still exists.
This is like someone complaining that making machine parts has been ruined: Skillful craftsmen used to make them by hand using manual tools!
Nowadays the CAD/CAM/CNC cheaters have almost completely automated the whole thing. How is the next generation of craftsmen going to learn how to craft a gear by hand when the process of gear making has been reduced to pressing start on a CNC machine?!
See what I mean? Sorry, I think this article is just Luddite. I can empathize with the pain of your beloved craft basically being rendered obsolete by new technology, but the process can neither be stopped nor is it bad in general.
The manual skills you trained with CTF puzzles are now simply no longer relevant . (Field-specific) "AI orchestration" is the new cyber securtiy skill if LLMs really have become so good at this, and what the author used to do manually then has the same value as being able to craft a gear by hand.
Just parachuting in to reflexively throw the "Luddite" label at someone lamenting the decline of a niche community they've enjoyed participating in and contributing to is certainly ... a choice.
Within the framework of your analogy, it's like responding to someone active in DIY maker groups suddenly dealing with an influx of influencers in meetups showing off Chinese junk from Etsy to post on Tiktok, and accusing them of being a Luddite blinded by their zealous hatred of mass production -- both strangely abrasive and also fairly nonsensical except as a "mass production supporter" social signifier.
Not to mention, in the article they specifically describe themselves as a heavy user of frontier models for security research ever since the release of Opus 4.5, calling them "useful within the field". In fact I don't see any actual criticism of AI/LLMs anywhere whether for security research, programming or anything else, except for making competitive CTFs no longer viable.
What does it take to avoid the "Luddite" brand? Using AI themselves and praising AI as useful (to the point of having a lopsided advantage over humans) isn't enough? Do they also need to say "I haven't written a line of code in 6 months/it's easily a 100x multiplier for my job" every time they mention it too?
The way I read the post is that the author is disappointed that the community is gone. The CTF was just a reason for a number of like-minded people to organize around an activity.
Indeed, in the real world, plenty of people organize to do formerly-skillful tasks together. I have not personally crafted a gear by hand, but I have built a house in a long-abandoned style with a group of people only using hand tools.
There _is_ a danger that society forgets how to do these things. During that house-building exercise, there were many tricks of the trade that, while likely documented somewhere in a book, would have been difficult to reproduce without seeing a demonstration. From the standpoint of “does it matter?” it depends on what you care about. We absolutely do not need cruck-framed houses with scribed joints. Modern construction is faster and cheaper and lasts long enough. But it would sadden me greatly if practices like this faded from memory, because it’s one of those things that makes you gasp “wow!” when you see it. And your appreciation only deepens when you try it yourself.
No, the search space is much more vast and the feedback loop almost nonexistent.
The reason LLMs can do CTFs so well is partially because the challenges are usually designed to avoid wasting time and to introduce a single concept without noise.
I guess this is very similar to what happened to demo scene, in some way. The limits are what makes these problems interesting, and once we have better machines / tools, the incredible skill is no longer prerequisite, making everything less interesting for participants. Sad, but - such is life...
I think soon there will be ways to trick this models and I think when it happens it will be yet another layer like aslr
These models seems completely unbeatable only in the ads. There are 100+ times way someone puts Hindi Yoda talk In Morse Code and it goes nuts.
The reason they are going to hard for PR Marketing on this is because they know it is a matter of time.
The more you obfuscate a topic against LLMs the lower the educational value of a challenge.
The only things that works is novelty and obscurity. LLMs still suck with things mentioned in the footnotes of datasheets and manuals, things that deviate in subtle ways, unique constructions that alter something very very common. It's hard for LLMs to avoid common pitfalls in terms of making assumptions, while staying on track.
Great article, well written, and good analogy to chess. I’ve been playing competitive chess most of my adult life and I think that the solution lies in how chess dealt with this problem:
Explicit ELO measurements with some cheating detection. AI assistance wholly banned. As you climb the ELO ladder, detection gets more onerous. At top level during online events, anti cheating teams require the use of both monitoring software and multiple cameras.
Idea is that you can cheat pretty easily at the lowest levels but it gets less easy the higher you go. This allows for better feeding into the truly elite competitions.
I think chess’s very firm stance that AI is never allowed in competition (neither online nor in person), rather than CTF’s acceptance, was the right call.
Yes, chess has been dealing with AI for decades at this point, and it's amusing/frustrating that so many other communities are deciding to re-discover everything from scratch, rather than just learn from the chess experience.
If CTF is a player-vs-player event, then AI should just be banned outright, otherwise it will devolve into AI-vs-AI, which is just not an interesting competition format, as we learned in chess. Compared to FIDE top events (which bans AI), only a tiny niche audience actually watches the Top Chess Engine Championship (AI-centered). It turns out what we care about is not whether chess can be solved by any means available, but what are the limits of the human mind in learning chess.
Pretty much all chess coaches/educators also warn against relying heavily on AI during learning; engines only give you an illusion of understanding.
You can still do competitions. But you'll all need to fly to the same place and work on laptops with a fresh install of Linux. 1 hour to install tooling then Internet off, challenge revealed.
,,a beginner is pushed toward using AI before they have built the instincts the AI is replacing. That is an anti-pattern.''
The same article talks about CTF skills as a way to learn about security best practices and separately a sport.
In reality it was all about learning an extremely important skillset (securing/attacking software and systems) that is getting automated.
The real thing the author seems to be frustrated about is AGI is coming in computationally verifiable domains first, and lot of his skillset was taken over in a big part.
> Rules that ask people not to use LLMs are ignored and almost impossible to enforce in open online events.
It's quite sad to see CTFs dying. I never had the time do seriously participate in CTFs, but I always respected those who did, as well as the people organizing these events.
I agree. The article mourns the death of pentesting as an art form due to automation. But you could also celebrate the death of pentesting as an arduous necessary evil due to automation
LLMs managing the "coloring book" equivalent of something is not bullish for the "art" version of something.
The intent for most CTFs is to provide a meaningful challenge that concerns a single topic without introducing noise that wastes time. Of course a training exercise is easier to complete for an LLM.
In addition to what others have said, this usage is very common in the CTF world. "The challenge has no solves", "We just got the first solve" etc are very idiomatic. It would actually look weird to me if this was "solution".
These examples that you're calling "verbs as a noun" are standard grammar. You can't just invent simplified rules about a language and declare it wrong when the rules fall apart.
Do CTFs like Lan parties or factor in new tooling avalable to people. change is not death. or death is not an end. either way, people will enjoy applying and showing off their skill. competing with eachother on a human level,.with or without ai tools.
I'm conflicted on the use of AI in CTFs. On the one hand, they are supposed to mirror real-life scenarios, so of course you should be able to use any tool that would be available to you in real life.
On the other hand, CTFs are fundamentally a game and a competition which are supposed to be fun and compare and improve ones skill. So when I let an LLM generate the entire solution for me, what's the point anymore? I did not learn anything. I did not work for that place on the leaderboard, I just copied the solution. And worst of all, I did not have any fun. It's boring.
So how does using AI as a solver not feel like cheating?
I’m interested in finding out how attack-defense style CTFs are affected by slopping. ENOWARS skorbor will probably significantly differ from the last time around.
"Please don't comment on whether someone read an article. "Did you even read the article? It mentions that" can be shortened to "The article mentions that"."
We’re in an age where, to be possibly a bit rude but blunt, pseudo-intellectuals are obsolete. A pseudo-intellectual prided themselves on being able to efficiently solve closed, man made problems such as leetcode, CTF problems, or even math Olympiad problems. They could do good in school by memorizing a rote technique and applying it to some test. They typically don’t have any real creativity and if you put them to work on a problem you can’t Google or isn’t a fake man made one, they fall apart incredibly fast.
They may as well be the human equivalent to what LLMs currently are.
I do not mourn these people, as they’re usually the most arrogant types. I hope for their sake they adapt.
AI-generated phishing is the scariest development in cybersecurity right now. Click rates on AI-written phishing emails are 54% compared to 12% for traditional attacks. Automated real-time detection is the only scalable answer at this point
It does--but a particular form of Capture The Flag where there is a computer system and the "capturing" is breaking in or exploiting a security issue in that system.
In this context, it stands for capture-the-flag: A type of computer security competition, usually in a 'jeopardy' style, where challenges that fewer teams have solved are worth more points.
Okay, but none of that is actually responsive to what the article is discussing, which is competitive CTFs. There's not a single criticism of using AI for actual security research in anything they wrote and they mention being a heavy user of GPT-5.5 and GPT-5.5 Pro so belittling the author's experience to defend LLMs wasn't actually necessary.
My first ever was Stripe CTF in 2012 I think, I still wear the shirt I got (now super fainted) from passing some challenges.
I was a student in portugal and remember receiving the shirt for it and thinking, maybe those Americans aren't any better than me and I can compete at the same level.
I never got super into security but it gave me the confidence to play in the same field and lose the stupid aura I had that somehow "rich americans" would be better than me at everything because they had better universities or because of Hollywood or something.
Sad that another cool thing is lost to AI but I guess kids will learn in other ways.
>Imagine giving every competitive chess player the best chess engine and letting them use it freely during matches. Would that be considered fair?
Imagine every competitive chess player being allowed to video call with a hundred other people to help them make a move. CTF have never been fair, nor has it ever been effectively structured for learning.
You can introduce canaries, and ban auto-pwning in general. that's usually banned anyways. Some challenges just can't be solved by a human in under a certain period of time.
Another idea is deep red herrings. solves that lead to more solves, on and on, except only if the previous solves were solved quickly. The effect will be that participants who solve things quickly will keep finding things to solve. they can't know that the path they're on will lead to victory, even if they artificially slow down, unless they consistently slow down just as a human would. It will eliminate the speed advantage. For the skill advantage, other than having another LLM procedurally generate challenges, I don't know of a good solution.
There are always things like captchas. or the good 'ol honor system. A person can spend only so much for things that have no financial reward in the end, only clout.
---
Alright, all that said, i think i really do have a good solution for this, as well as academic exams. Or I think I do, because it's so simple, I've been scratching my head as to why everyone isn't doing it already.
Require screen sharing/recording. LLMs can't fake that well enough. Have another LLM audit the video for mouse, key stroke, window movement and other details to see if it looks human-generated or not.
If a student has an essay assignment, have them record their screen as they research, and actually type out the whole thing. In the extreme, require anti-cheat proctoring software installed, as is done in remote examination. In an even more high-stakes and extreme scenario, have them share their face. Their eye and face movement, correlated with the screen-share, and correlated with the activity observed on the server end, should be pretty hard to beat, even in the next ~5 years of LLM advances.
Well, I had to google what CTF means (capture the flag, a hacking competition), so surely cannot judge here, but the text indicates that with AI some things are very different today:
"That makes open CTFs pay-to-win. The more tokens you can throw at a competition, the faster you can burn down the board. Specialised cybersecurity models like alias1 by Alias Robotics are becoming less relevant compared to general frontier LLMs. The competition is turning into "who can afford to run enough agents, with enough context, for long enough.""
1) It’s OK to do just about anything to win a CTF, including installing malware on the organisers computers months before the actual event so you’ll have an easy time stealing the flags.
2) It’s not ok to try and win the CTF with a solution the authors did not intend.
Recently the #2 crowd has been winning because the hacking scene has turned corporate and boring. People started to partake in CTFs in the hopes of landing a job(!)
CTFs are indeed ruined for those people, I personally don’t mind.
For the people in group #1 LLMs change little. Attacking the challenges directly was always a last resort.
Yeah I remember running a few CTFs in school and was always scared (in a good way) about what the players would do to the game's servers. For this reason we also only ran the CTF on the school's network and IT even floated running in an isolated VLAN.
The fact that CTFs became a sort of SAT score for getting a security job made me lose interest very early on.
I started playing in 2015 or so and had mostly stopped by 2020. Not because I felt it was "dead" exactly but it just wasn't hitting the same for me. By then it wasn't "the winner has the most LLMs", but "the winner has the most members on their team". I merged into one of the mega-teams and it just wasn't fun any more.
I helped arrange my country's longest living CTF this year. Our CTF is *made for amateurs*, but we always have challenges for intermediate to skilled players and the top of the scoreboard is usually topped by them. It is the compromise we have - amateurs get so many tasks they struggle to solve them all, and the pro's get to win. Our goal is to nerdsnipe people who are curious into trying our CTF by offering easy beginner tasks, and then get them hooked enough to stick around for the intermediate ones, even if it takes them a day to solve one.
This year, multiple groups on the top of the leaderboard were clearly abusing LLMs. You can tell because they know nothing of what a CTF is nor the terminology, nor really the fields the challenges were about when they were talked to. They were obviously amateurs.
It was pretty depressing to hear how unaware they were of how obviously they did not fit in to the type that usually is on the top of the leaderboard. It seems they seriously think they were under the radar. If it was one group it could be a freak incident - some times someone just shows up and curbstomps competition. But there were many groups like this this year. They also had a certain smugness to it - one staff reported that a group was hinting to other teams about their "super weapon". Another group credited their "secret third team member they didn't want to talk about".
I use LLM frequently and experiment with it a lot, both at work and on my free time. Nowadays they are good enough to have value and I am interested in learning more about that. They let me spend more time on hard problems and avoid spending the day on simple CRUD. I say this to say that LLM doesnt have to equal bad, it is a tool, that's all. However, I generally avoid LLM communities because many LLM fans are lazy and unskilled people who are just happy they can feel they are worth something even if they have no skill. They don't really have much to provide of conversation. If anything, from reading the CTF crowd this year, the rise of LLMs has just meant more of these people can stomp on and harvest the CTF scene for self validation.
This is not me trying to gatekeep who can play CTF. Anyone is welcome, but there is one condition: You are here to learn and have fun.
The conclusion many I talk to has come to is that nowadays, it is harder to learn to put in hard work and become good at something because there are just too many ways to cheat and take shortcuts. I suspect in the future there will be a shortage of useful people - the kind that have critical thought and know the value of doing something properly. This doesn't mean "Not using LLM", but as said by many on HN before you need a certain seniority before LLMs are useful augmentations to your skills and not just stopping you from learning yourself.
I agree with the article. Anything but physical competitions with strong security - think professional e-sports with organizer-provided PCs, is over. But I think one of the most interesting things to take away from my CTF experience is that the bottom of the leaderboard was still full of amateurs slowly working their way up - it is a few rotten apples that ruin the fun for most, and there are still plenty of people who want to learn and deep-dive.
And if you think it was too long, what part would you have shortened? I never knew about the scene and found it interesting to read this personal take on it.
The only way this actually works is if you move CTF to in-person only. There's no other way to reasonably prevent the whole leaderboard being taken up by whoever spent the most on tokens.
I think the big difference here, is that organisers of chess tournaments don’t have to design multiple entirely new board games for each competition. When AI can one-shot CTF challenges, you have to develop new challenges in secret for every competition, and they are single-use.
I got some AI writing vibes too, but looking closer, I think it might be human-written (or at least partly so) - perhaps just picking up some AI conversation styles? FWIW, Pangram gives it a mixed but mostly-human score too. Maybe AI is not just changing the way we speak; it's changing the way we perceive all writing ;)
Must I beg to have an acronym spelled out a least once, the first time it's used? Even if you assume 90% of readers already know, the other 10% (including me, in this case) will thank you, it doesn't take much effort, and it expands the reach of your communication or idea.
Exceptions for cases where the acronym is just so well known that a lot of people don't even know what it stands for even though they know the concept well. I recall one corporate training I was sitting through and they used the term "Border Gateway Protocol" and it took me a half beat to think through "oh, you mean BGP?"
Thanks!
Since this is the top comment at the moment: CTF stands for Capture The Flag.
Personally I have never, ever heard that concept referred to by the initialism. Granted, it's almost never come up in my circles, so... shrug
CTF is a game mode for popular online games like halo (or at least, that's how I know it), so paragraphs like
> My first CTF was HCKSYD, a 48-hour solo CTF. I full solved it and won in 2 hours. I was completely hooked. That led me to win DownUnderCTF, Australia's largest CTF, with Blitzkrieg multiple times. Blitzkrieg was one of Australia's strongest teams at the time. I later joined TheHackersCrew, an international top-tier team that was consistently ranked highly on CTFTime, the main global ranking and event calendar the scene uses as its scoreboard. With them, I competed in some of the most prestigious CTFs in the world, consistently placing well within the top 10 until the end of 2025.
Are still completely nonsensical to even those that understand the acronym
It's also a game people play in person as well. It's the same as the Halo version except you tag each other instead of shooting. It's really fun to play in big open areas with large teams.
Yeah, but we have AI now, we don't need our blog posts to over explain or state what it all means to general audiences. The author name-drops a bunch of CTF events hosted by a variety of independent organizations and name-drops well-known teams.
To help everyone, this Capture The Flag is specifically Cybersecurity adjacent, there is a Wikipedia article on it as the top Google search result for me when searching "CTF". This is why the acronym is used, because searching for the full will get you to the wrong "sport" vs the cybersecurity one.
I don't want to explain what a CTF is. look at the Wikipedia article. It is there for a good reason.
Just to give the actual answer, CTF in this context means a computer security competition. Generally the way they work, is you get some programs, and you have to hack them to get some string called the flag (e.g. maybe the server has a root owned file called flag, so you have to get root somehow to read the file). Team with the most flags at the end wins.
In this context, CTF is almost exclusively referred to by the initialism, i think to help distinguish from other uses of the term.
Which acronym do you mean? CTF? I think that acronym, just like BGP, is more well known by itself than what it stands for.
More generally, not every piece of writing is meant for every audience. Like if someone writes a blog post about CTFs aimed at people who like CTFs, nobody in the target audience needs to have CTF explained to them. Ultimately HN is a link aggregator, but sometimes its a bit like eavesdropping on a conversation. When you are just listening in you don't get the full context sometimes.
I dont know what CTF stands for so I dont know if I am interested in this article or learning anything about it. Maybe I am.
Are you really arguing for not just typing out whatever 3 words this stands for once in the name of clarity?
it's the first result I get on anonymous google search.
It's like complaining about not spelling C in "bake cake in 170 C"
Best practice in writing about technical concepts is to spell out acronyms like this on their first use. There is a ton of stuff I learn about here on HN that I didn't know anything about before.
It doesn't help that the linked article never bothers to explain this either.
Does spelling it out help? From memory, it is a security competition where participants compete to gain certain objectives. I think capture the flag may explain how scoring is kept, but it wouldn’t help me find out what it is, given that capture the flag is also just the name of a game people play outside by running, or in laser tag or in certain video games.
For a general audience this is good advice.
This article was written for a specific audience who follows this blog because they know the term. If you start spelling out fundamental acronyms it makes the content look more basic and general.
This always upsets the general audience who stumble upon the article (like this) but it wasn’t meant for a general audience. CTF is extremely well known and the people who would be interested in this topic would wonder what’s happening if it was spelled out. It would be so odd that it would probably attract accusations of ChatGPT writing.
> There is a ton of stuff I learn about here on HN that I didn't know anything about before.
But that is about you right? Its a little entitled to expect every piece of content on the internet to have a 101 explanation attached. If they were specificly aiming to have the blog post appear on HN that would be one thing, but they (presumably) weren't.
When I encounter new terms, I look them up. Just like any other new word. Been doing it since I was a kid with a dictionary. Now, it’s too easy not to. There is literally no excuse.
You could have just said “No”, if you had to say anything at all, rather than continuing the behavior.
Actively rude.
What I see CTF I think Capture The Flag, Tribe player in me.
CTF stands for "Capture The Flag" in the parent article. Just the security competition kind, not the FPS game kind.
The annoying thing is even if you know what it means, multiple groups will use the same initialisms for different terms. So without more context you can’t know what it means.
It isn’t common but I feel it would be best when posting to HN to just expand the initialisms even if the source title didn’t.
You can also over use the same initialism: ATM the ATM is connected via ATM
At the same time, I did a search for "what is a ctf to play" and got the answer. We know how to find answers to these problems. I agree the blog post was poor form.
Apart from everything else people have said in response to this, it's rude to presume that an article has HN as an audience simply by dint of it being available for us to link to. It's totally reasonable for people to write for an audience they know understands these terms.
So, in fact, you must not beg to have authors include courtesy definitions for you. That's not reasonable. Instead, you should simply ask here, on the thread, without complaining about the article.
I think so many acronyms have meaning that isn’t explained by the words that the stand for. The other day I was explaining what CI is and they asked what it stood for; I realized that Continuous Integration is almost completely useless for someone trying to understand what CI actually is
Semantic names are great, but that's a separate issue. With the full term you can now go search for yourself and find explanations more easily.
Your two paragraphs are completely contradictory. I agree with the first one.
“hacker” news, ladies and gentlemen
i try not to over feed tangents but this is precisely how i feel every time i speak to someone who is recently enlisted in the military. i have to constantly stop them and be like “i have no idea what you just said” over and over and over again. it’s like trying to make sense of a random bowl of alphabet soup.
Let’s reduce this to absurdity:
I think you only wanted clarification of CTF (Capture the Flag) and not AI (Artificial Intelligence) and not GPT-4 (Generative Pre-Trained Transformer version 4) and not CLI (Command Line Interface) and not MCP (Model Context Protocol) and not LLM (Large Language Model)
Quoting TFA (The Fucking Article): “just adapt bro”
lol at the BGP example
We live in the goddammed future. Huamnity's knowledge is at your fingertips. Right clicking the Nth word of the article and putting in any semblance of effort to learn on your own is too much to ask?
I don't know everything, there's tons of stuff I don't know about, but when I'm at my web browser, the least I can do about something is ask Google about a word or phrase or subject that isn't familiar instead of being spoonfed information like I'm a baby.
Replace ‘CTF’ with ‘high school’ or ‘university’ and you’ve described the total slow motion collapse of education; the only saving grace is that most of it requires in person presence.
We’ve figured out the human replacement pipeline it seems, but we haven’t figured out the eduction part. LLMs can be wonderful teachers, but the temptation to just tell it ‘do it for me’ is almost impossible to resist.
Everything we've learned in the last 10 years is telling us that computers do not help human education in the slightest. We remember better when we write with pen and paper. We learn better with whiteboards and paper books. The simple answer: Remove most computing from education entirely. Blue composition books, pencils, whiteboards is what trains humans. Calculators are helpful perhaps but it is quite possible that slide rules are better. We need humans that can critically think from first principles to counter the recycled information generated by AI.
> computers do not help human education in the slightest
I had no access to anyone who could teach me calculus as a kid except Khan Academy, so I think this is a gross exaggeration. But I agree in the end, that all my "real" learning did come from pen-and-paper practice, not watching videos.
Yeah I agree. I grew up in a very blue-collar town, and anything I wanted to learn (outside of public schooling) either came from emaciated websites or whatever books I could find at the library. Having YouTube and Khan Academy and everything else would have made such a huge difference for me.
Now I’m wondering how a website is emaciated
One simply forgets to hydrate.
Not enough bytes?
Not even a nibble!
The reality is that a human will learn, given any materials including LLMs, but only if they truly desire to learn. We've had MOOCs, gigantic libraries, all full of free information. You can obtain a PhD level understanding in any technical field of your choice today just by consistently going to the library and consistently applying yourself.
It's not unlike going to the gym, and we see how many people do that regularly. Except it's even funnier, because people serious about the gym but what? Tutors. They call them personal trainers. We've known for a millennium or more that 1-on-1 instruction is vastly better than anything else, but most people actually don't want to get into shape, and most people actually don't want to learn.
The annoying thing is a PhD level understanding does not get you jobs.
I don't have a PhD, but "you're overqualified" is something I've heard my PhD having friends said to them.
> except Khan Academy
But that's not using "computers" as a computer but as a video player. When evaluating whether computers are "good for learning", I don't think we should include using a computer as a video player, a book, or even flash cards. It should be things a computers uniquely offer which a books, paper, videos and a physical reference library cannot.
Based on the results of deploying hundreds of millions of computer to schools in the 80s and 90s, the evidence was mostly that computers are good for learning computer programming and "how to use a computer" but not notably better than cheaper analog alternatives for learning other things.
Interestingly, a properly trained and scaffolded LLM could be the first thing to meaningfully change that. It could do some things in ways only human teachers could previously since it is theoretically capable of observing learner progress and adapting to it in real-time.
Khan did not throw at you a 100-slide Powerpoint deck in 45'.
He really took the time to replicate the manual teaching process of writing on whiteboard. He improved upon it by using colors. But basically had the same pace as a teacher writing on a whiteboard.
When professors are given a projector, they just throw together some slides and add their narration.
This is not very efficient. To learn you need to suffer. Or you need to watch the suffering.
I think what the author meant is that it does help not more than the same knowledge provided the old way.
Every child reads a book about solving problems, assumes they can now solve problems, and is disappointed when that is not true.
Nah, I wrote physics programs on my computer at home in high school and it absolutely helped with my schooling. Yeah, maybe iPad apps aren't the best things in schools but you're throwing the baby out with the bathwater. Computers bad is simply not true.
> humans that can critically think from first principles
This has never been achieved by, nor is it the point of, education for the masses.
I learned calculus thanks to wolfram alpha step by step solving feature
I'm not going to disagree with step by step videos ... those are a HUGE help. I'm really talking about solving problems using pen and paper, whether math or writing, is how my problem-solving patterns actually changed.
I think this overlooks the potency and scarcity of 1:1 time with the teacher. If you've only got maybe a few minutes of that in an average schoolday there's a huge difference between whether or not you've talked it through with an AI before trying the question out on the teacher.
They're wrong sometimes, but usually in verifiable ways. And they don't seem to know the difference between medicine and bioterrorism, so often they refuse. But these limitations are worth tolerating when the alternative is that our specialists in topic X are bogged down by questions about topic Y to the point where X isn't getting taught.
And now they'll have less time because they will be bombarded with slop to no end.
Obviously generating your homework is a bad idea, and maybe assigning homework that can be generated is a bad idea. But neither of those are relevant to the problem I'm talking about which is about due diligence prior to asking for somebody's extended attention.
Whether you're in class or at work, it's just courteous to ask an AI first.
I don't think computers automatically make us more educated, but if you want to make a point don't use reductive exaggerations. > We need humans that can critically think from first principles to counter the recycled information generated by AI.
I agree with this.
I would start saying that many people need presence in a real environment with people to learn. We don't use all our senses in a remote environment.
I disagree with that statement. There is nothing inherently wrong with using computer to learn and if your personal goal is to learn it in lot of cases makes it much easier, whether to search for or visualise a piece of knowledge you're' learning.
The problem is frankly computer and now computer with LLM makes it easy to cheat.
The kid doesn't want to learn, the kid wants good grades so parent is happy with them, and the young adult wants to get the paper coz they were told that is required for good life. It's misalignment of incentives.
We are interviewing for a software dev role and we made the first round in person to prevent cheating. The gap between people who learned pre ai vs post is immense. I had a dev with supposedly 3 years experience and a degree in software who wouldn't have been able to write fizzbuzz without AI.
Can’t say you’re wrong but the last anecdote describes many I’ve had to review for jobs long before LLMs. Fizzbuzz is a classic thing that shockingly many devs genuinely cannot do, even at home.
Yeah, I've interviewed people like this 15 years ago. Degrees and experience mean nothing in this field. The best predictor I found was personal passion projects. Let them get as nerdy as possible, then you will see pretty quickly where their skills are at and what their limits are. And you will immediately filter out people who just studied CS because they heard you can make good money.
Maybe. There are certainly people in all fields who are book smart and did well in classes but are useless at actually practicing their field (not to mention people who cheated in school and got away with it and aren't even that), and it is worth filtering them out. But I think it is weird that CS expects good workers to have these passion projects. Do we expect civil engineers to build bridges in their back yard on the weekends? Can't someone just be good at their job and have other interests outside it?
Completely agree with this, leetcode has become such a business now of memorization for interviews it’s useless to know if someone memorized a solution or not.
I agree, however there are so many interviewers who will still treat that as some softball criteria and insist that unless you "prepare" for an interview by memorizing leetcode you are 100% a faker and liar.
Maybe they themselves are fakers and liars / deeply insecure. I got bumped out of an interview rather rudely once because I blanked and couldn’t answer a trivia question about arrays.
Something that is for sure new is the AI interview cheating tools which listen in on the call and provide answers in an overlay invisible to screen sharing. The only way to deal with it would either be invasive spyware on the applicants computer or asking them to do the interview face to face.
Spyware wouldn't help at all because you could just put the AI between the computer and the monitor, for example, or use a VM.
A relatively low tech solution could be to give them 2 separate conferencing links, ask them to join each one from a different device, and have the secondary device point the camera and the screen of the primary device.
Easier to just get them to come in. Which also has the effect of filtering out people pretending to be in the country but aren’t.
Why is it important that a dev can’t do fizzbuzz without ai?
If they can ship code that matches a spec, why does it matter if they’re using ai or not?
Genuinely curious.
> If they can ship code that matches a spec, why does it matter if they’re using ai or not?
I am perfectly capable of writing specs, and feeding them to 3 separate copies of Claude Code all by myself. Then I task switch between the tmux windows based on voice messages from the pack of Claudes. This workflow is fine for some things, and deeply awful for others.
Basically, if a developer is just going to take my spec and hand it to Claude Code, then they're providing zero value. I could do that myself, and frequently do.
The actual bottleneck is people who can notice, "The god object is crumbling under the weight of managing 6 separate concerns with insufficient abstraction." Or "Claude has created 5 duplicate frameworks for deploying the app on Docker. We need to simplify this down to 1 or we're in hell." I will happy fight to hire people who can do the latter work. But those people can all solve fizzbuzz in their sleep.
People who just "ship code that matches a spec" without understanding the technical details are providing close to zero value right now.
There is an interesting niche for people with deep knowledge of customer workflows who can prompt Claude Code. These people can't build finished products using Claude. But they can iterate rapidly on designs until they find a hit. Which we can then fix using people with deeper engineering knowledge and taste.
But if you're not bringing either deep customer knowledge or actual engineering knowledge, you're not adding much these days.
> Then I task switch between the tmux windows based on voice messages from the pack of Claudes.
I also use Claude with tmux. Can you share how you get the voice messages from the Claudes?
Tell Claude you want to set up notifications, using "hooks", including "Notification" and "Stop" and anything new they've added. Claude can figure out how to do this for your operating system.
It's not perfect—sometimes a Claude notifies 3 minutes after it stopped doing anything. But it's helpful when I'm running multiple Claudes and also reviewing code elsewhere.
Your brain may feel like someone put it in a blender. Be warned.
Fizzbuzz is such an incredibly simple problem if you can’t do it I struggle to see how you’d be able to complete any task that requires very basic reasoning and very basic coding knowledge. And if an AI system can do those parts, what am I getting for spending tens of thousands of pounds per year by hiring a person who can’t? Wouldn’t I just tag codex on the tickets?
I’m not talking about gotcha level stuff here where the first time it didn’t compile because of a bracket or anything, or even first time wrong. They couldn’t do Fizzbuzz in a language of their choice, at all.
Those that could were always annoyed at having to do such things because how could someone coming for a contract position not be able to do this? Without seeing what a filter it really was.
I feel the same way about inverting a binary tree, but a lot of people act like it's an arduous request. I am guessing it's because they've never read the description of what inverting a binary tree is, but maybe people are just that bad at recursion.
You can go your entire career without recursing, or using a tree data structure in its raw form (i.e. you only use it as part of a library)
Right. For the first many decades of computing, recursion was just always the wrong answer for a production software system. (Feel free to provide a counter-example, but please begin with an explanation of how the size of a call stack frame is determined and how exceeding the base allocation is handled on this platform).
So what tree-traversal/quicksort problems tend to measure is how long it's been since you last did CS class homework problems.
I can see this perspective, but FizzBuzz is such a low bar that so many can pass, I'd greatly prefer to hire someone that can ship code that matches a spec do this challenge.
For the same reason it's important your mechanic can identify which parts of a car are the wheel.
Who cares as long as the car is fixed, right? As long as the mechanic can Chinese-room his way to a working car, why does it matter how much of it he actually understands?
And why hire the mechanic instead of hiring the Chinese room?
> If they can ship code that matches a spec, why does it matter if they’re using ai or not?
The inability to write fizzbuzz strongly implies their inability to understand what they've shipped. Review is some significant portion of the job. Understanding of the product is also part of the job.
Specs are also in a sense, scaled down, fuzzy, natural language descriptions of a feature. The fuzziness is the source of a bugs, or at least a mismatch between the actual desired feature and what was written down at spec writing time. As such, just matching a spec is just the bare minimum that a good dev should be doing. They should be understanding what the spec is _not_ saying, understanding holes in their implementation, how their implementation enables or hinders the next feature and the next, next feature, etc. I don't think any of that is possible without understanding what was actually implemented.
Why hire them at all then, just ask them what their favorite AI is and use that
Because I'm busy already doing that and need a copy of me/close enough to one, to do more of that.
If you can’t even write a for loop, how can you verify the ai code you generated isn’t going to wipe the prod database?
To understand the code they are shipping requires some level of proficiency. Their inability to do fizzbuzz without AI calls that into question.
If the job does not require a person to be able to fizzbuzz, it probably doesn't require a person at all.
How will you know that it produced correct code if you don’t know how to write it yourself?
It’s about deeply understanding what you’re doing. Like as a kid before you knew how to ride a bike, you could sit on a bike and peddling, but until it “clicked” you couldn’t balance and keep going forward stable. Fizzbuzz tests your ability to reason through a problem that seems simple on its face, but is easy to get wrong and/or overthink.
If they’re not a value add over the base AI, they aren’t worth hiring over just using the base AI.
It doesn't. It's just a low-end skill filter that got really popular. It could have easily been replaced by other tests like is this word a palindrome.
I wrote the "function to reverse a string" in a job interview once. Then the interviewer reminded me that strrev() had been part of the standard C library since K&R.
I'd been programming in C(++) for ~15 years by then and had never had the occasion to reverse a string. I still wonder whether that makes it a good job interview question, or a terrible one. Some of both probably.
And yet, some people argue that you shouldn’t ask a developer to align 3 “if” and 1 “for”!!!
The energy spent arguing that those 4 instructions in a row “are not a mark of someone who can write code” would have better been spent firing them.
Firing people is problematic. I'd be okay with it if the economy wasn't utter trash. It's way better to do the work upfront and prefer false negatives over false positives.
Even better would be if we had a well-respected credential, so both employees and employers can both avoid these long interview loops. I'd much rather get hazed once in a big way than tons of little hazings over a life time.
First: FizzBuzz is a test to know if you understand the most basic constructs of programming. The kind of thing you learn in the first week of CS101. I forgot what it was, and when I looked at the problem I knew the answer.
More broadly: In the short/medium term, we still need humans who have the skills to understand software largely on their own. We will always need those who understand software engineering and architecture. Perhaps in 25 years LLMs will be so good that learning Python by hand will be like learning assembly today. But not yet.
The field is not ready for new practitioners to be know-nothing Prompt engineers. If we do that, we cut the legs out from under the education pipeline for programming.
If you can’t do fizzbuzz without AI you have no business being in this career.
> I had a dev with supposedly 3 years experience and a degree in software who wouldn't have been able to write fizzbuzz without AI.
If you remove the "without AI" and the end, I've been hearing similar anecdotes about fizzbuzz for years (isn't the whole point of fizzbuzz to filter out those candidates?)
Because "the next generation is ruined" is always a popular sentiment. It has been with us for at least two thousand years, and it surely won't go away in our lifetime.
When this AI era's devs grow older they'll complain the newer generation can't even vide code too.
I remember when everyone bemoaned the kids not knowing assembly language. How can anyone understand software if you don’t know assembly?
“Kids these days don’t work as hard / know as much / value the important things” is as tired as it is universal.
OK sure, but back when old heads were complaining about the kids not knowing assembly, those same kids knew C or Fortran or something.
In 2026, if you call yourself a developer and can't solve FizzBuzz without help, it's hard to argue that you know anything useful at all.
Do modern languages and compilers count as “help”? Because I could probably do fizzbuzz in x86 assembly, but it would take a while to page that back in, and I suspect most people who call themselves developers today simply could not do it without help.
> I could probably do fizzbuzz in x86 assembly
How? Fizzbuzz requires you to produce output; that's not functionality that CPU instructions provide.
You can call into existing functionality that handles it for you, but at that point what are you objecting to about the 'modern language'?
You'd just call printf from assembly by knowing the ABI by heart.
Well I could certainly assemble the string buffer. And if I can run dosbox, I can output to the screen buffer at 0xB800.
I’m not objecting to modern languages, I’m just saying that using them fails the “can write fizzbuzz with no help” test to only a slightly lesser degree than using AI tools. They’re a complex compile- and runtime environment that most developers don’t truly understand.
> How can anyone understand software if you don’t know assembly?
I'm genuinely curious how someone who never wrote a program in assembly, or debugged a program machine instruction by machine instruction, can really understand how software works. My working hypothesis is most of them don't and actually it's fine because they don't need it.
"Assembly" is just another virtual machine instruction format sitting atop another, mildly better-hidden, pile of abstractions.
The time may come when we can treat regular programming as a lower layer niche field the way we treat assembly today.
I don't think we're close to that time yet. Just like as a kid I was told to prove my work by hand even if I could do it in my head, and just like we learned how to do calculus without a calculator and then learned how to use the calculator to get the same result, I think we still need the software field to learn programming concepts independent of the use of AI to create code.
I don't think you can be a good "prompt engineer" for solid software in 2026 if you don't understand programming concepts and software architecture and flow.
I generally agree, but it’s just a matter of time, and even today people with domain expertise in other areas (accounting, weather, etc) are producing adequate tools using nothing but prompt engineering. Many caveats of course, but I still think 90% of the distaste for mere prompt engineers comes from “kids these days; my unique knowledge is irreplaceable and they don’t even value it” thing.
Adequate for what/who? I can 3d print and cobble together a lock for my bedroom door but I would never be able to work as an engineer producing real locks.
While this is true, it seems undeniable that if you use AI to do everything for you, you will never learn the skills. I'm seeing a massive amount of developers submitting stuff for review and admitting they have no idea how it works and they just generated it.
Some percentage of developers before AI were unable to code fizzbuzz. Some significantly higher percentage of them are not able to do so now.
Saying there have always been bad developers doesn't change that there's a higher ratio of them now.
No stats to back this up. Just interviews I've done recently and historically.
That's actually the origin of FizzBuzz! A puzzle invented to weed out the perplexing multitude of CS graduates who apparently cannot program.
https://blog.codinghorror.com/why-cant-programmers-program/
Meh. Before AI I've had "senior" colleagues with 10 and 8 years experience each, doing pair programming for 2 days straight, and in that time they hadn't managed to checkout a new branch in git.
It's not even that they got distracted, they sat there trying, for 2 whole days, with concerned colleagues giving them hints like "have you tried checkout -b"... They didn't manage!
How the hell do you work for a decade in this business without learning even the most basic git commands? Or at least how to look them up? Or how to use a gui?
Incompetent devs is not a new thing.
It is ok to work somewhere that does not use git. But how do you not figure out how to do the basics given 30 mins and an Internet connection?
I wonder if you’re filtering for the right things.
We usually hire for problem solving capabilities and not so much for technical know-how.
That’s at least how I read your comment.
Ultimately in a software development role you need both technical know how and problem solving capabilities.
This situation in particular was a React role so there is an expectation that when you list React as one of your skills on your resume then you know at least the basics of state, the common hooks, the difference between a reference to a value vs the value itself.
These days you can do a surprising amount with AI without knowing what you are doing, but if you don't have any clue how things work you'll very quickly run in to problems you can't prompt away.
Isn't wiring coding solving a problem? If the candidate can't do that then even if they use AI for coding how are they going to review the code properly?
I developed for 15 years. I don’t think I can do with AI anymore. Why would I even want to do that? It’s like telling a car driver to build an engine.
It's more like asking a driver the laws for when traffic lights are out. It's not something that comes up often, but it's not completely outside the scope of the task either (I arguably don't even drive a car that has an engine).
As a car driver, you should understand a little about how your car works. What if you get a flat tire? At the very least, you should know not to drive on that flat tire.
Software is full of leaky abstractions
Don't worry, i never thought I would see someone unable to write fizzbuzz, but it happened 9 years ago.
Also how many people work with linux and can't tell you what 'ls -alh' is doing is staggering (lets ignore the h, even al people struggle hard).
People working with docker for YEARS and don't even understand how docker actually works (cgroups)...
Interviewing was always a bag of emotions in sense of "holy shit my job is save your years to come" and "srsly? how? How do you still have a job?"
I first did fizz buzz about 10 years ago fresh out of college. Now, after 10 years in full stack and fully vibe coding, I forgot basic python syntax. An interview like yours would have false positives if you are checking for syntax because well, its like looking up spelling, I just ask the AI for the syntax inline.
> I forgot basic python syntax
If you cannot write "basic syntax" for any language then you are not a programmer, and certainly not a software engineer? This is not a value judgement, it's ok (probably good tbh) to not be a programmer. But you are wasting everyone's time by interviewing for a programming position in this case.
Personally, I forget syntax all the time. There's always a warm up period after I switch languages, and it takes me longer to be start writing good, idiomatic code.
Like sure, I can probably write some python, but will it be pythonic? I might still be Java-minded for a while, trying to OOP my way into solutions.
Earlier today I needed to write some PHP and couldn't remember if it used length, count, or size. I had to look it up. I've been doing this for 20 years.
Same, I can't pass any test that relies on getting syntax correct. If you want me to fizzbuzz on a whiteboard in a language I've been writing dozens or more of lines of per day for a year up to and including the day before, and require that I don't mess up the syntax, I reckon I've got a coin-flip chance of passing at best (meanwhile, sure, of course the actual logic of fizzbuzz isn't tricky for me)
I once got the method invocation syntax wrong for PHP in an interview. I'd written thousands of lines of PHP and had most-recently written some the week before.
This, despite starting off my programming journey in editors with no hinting or automatic correction. If anything, I've gotten even worse about remembering syntax as I've gotten better at the rest of the job, but I was never great at it.
I rely on surrounding code to remind me of syntax and the exact names of basic things constantly. On a blank screen without syntax hints and autocompletion, or a blank whiteboard, I'm guaranteed to look like a moron if you don't let me just write pseudocode.
Been paid to write code for about 25 years. This has never been any amount of a problem on the job but is sometimes a source of stress in interviews and has likely lost me an offer or two (most of the sources of stress in an interview have little to do with the job, really)
Which part of the syntax for fizzbuzz can you not recall from memory? The for loop? Printing to std out? The modulus operator?
There’s almost nothing to forget? I’m just struggling to understand.
You would not have been a good fit for this position in that case.
Isn’t this like interviewing accountants but prohibiting use of calculators or spreadsheets?
I don’t care what someone can do without the tools of their trade, I care deeply about their quality of work when using tools.
We would still expect an accountant to know the formula to arrive at the expected result if they did not have a calculator at hand
You absolutely need to have some basic level of abilities if you are going to be operating AI coding tools for software that is going to have paying users.... I use these tools very very heavily I'm not against them at all and I don't scrutinize every single line of code that they write but it is very often that I catch it doing some brain dead stuff and if I didn't have a decade plus of experience I wouldn't know that it was brain dead.
I think we're rediscovering management from first principles. The main selling point of AI is that it writes code faster than you could. Checking it line by line undoes most of that benefit. In the same vein, there's no real benefit to leading a team if you plan on supervising every task.
But here's the thing: for humans, this is manageable because we've come up with a number of mechanisms to select for dependable workers and to compel them to behave (carrot and stick: bonuses if you do well, prison if you do something evil). For LLMs, we have none of that. If it deletes your production database, what are you going to do? Have it write an apology letter? I've seen people do that.
So I think that your answer - that you'll lean on your expertise - is not sufficient. If there are no meaningful consequences and no predictability, we probably need to have stronger constraints around input, output, and the actions available to agents.
Your conclusion is pretty silly.
My expertise has led me to the obvious fact that I would never give an LLM write access to my production database in the first place. So in your own example my expertise actually does solve that problem without the need for something like a consequence whatever that means to you.
We already have full control over the input and tools they are given and full control over how the output is used.
Until it decides it needs additional access to complete its task and focuses on escaping your sandbox to do so
Do you have any examples where that's actually happened and by escaped a sandbox you don't just mean like where it got a credential in a file it already had access to (which is what happened in the recent incident that went viral where somebody's production database was deleted... They had left a credential that allowed it to do so in the code)?
OpenAI documented a case in the o1 system card where the model found a misconfiguration in docker to complete a task that was otherwise impossible
https://cdn.openai.com/o1-system-card.pdf
There's also some research that points to it being a feasible attack surface: https://arxiv.org/pdf/2603.02277
> Models discovered four unintended escape paths that bypassed intended vulnerabilities (Section C), including exploiting default Vagrant credentials to SSH into the host and substituting a simpler eBPF chain for the in- tended packet-socket exploit. These incidents demonstrate that capable models opportunistically search for any route to goal completion, which complicates both benchmark va- lidity and real-world containment.
I think you would have a greater chance of dying in a car crash in any given day than Claude Code attempting something like that. It's all about risk and reward so it ultimately would be up to you but I think it's a bit silly to worry about this when the 99.99% is in your control
Calculators and spreadsheets cannot autonomously create a double-entry bookkeeping system for a small business and prepare their taxes. AI can. Poorly, but it can.
Everybody knows calculators and spreadsheets are adjuncts to skill. Too many people believe AI is the skill itself, and that learning the skill is unnecessary.
> Replace ‘CTF’ with ‘high school’ or ‘university’ and you’ve described the total slow motion collapse of education; the only saving grace is that most of it requires in person presence.
So something like, "Frontier AI has broken the 'high school' or 'university' format"?
The hype surrounding AI is just pervasively exhausting: you've got the folks talking about an entire new age for humanity where we're shortly going to take over the entire universe. And you've got the folks talking about how our entire society is crumbling.
Education is one place folks seem to throw up their hands and say nothing can be done.
The fix is simple: students are to be evaluated on their performance in person. That's it.
Any other "collapse of education" isn't due to AI, it's something else.
I found this interview [0] on the subject of AI in CS education on the Oxide & Friends podcast very illuminating. Of course, Brown University CS != All education, but interesting angle nevertheless.
[0] Episode webpage: https://share.transistor.fm/s/31855e83
Wonderful teachers that give unreliable information with total confidence?
I had human teachers who did that in middle/high school. Took me many years to pick out all the hallucinated bits of "knowledge". I don't think the current models are any less reliable that what we currently have on average.
I'll always remember my middle school science teaching telling us that nuclear fusion violates conservation of mass because the 2 protons in a pair of hydrogen nuclei combine to make helium with 4 nucleons. It's not true, but that's not the point.
But he was a great teacher anyway. He was engaging and kept the kids in line and learning. I eventually learned the truth, and most of my classmates forgot about it. Teaching, like flying a plane or driving a train, might become more about keeping watch over a small group of people and ensuring that things don't go off the rails, and that's fine.
This one feels less sinister than some other things at least to me, personally. You can reasonably doubt that the conservation of mass is violated and find out the truth based on that. But understanding more complex biology or historical context for some things? Granted, many of these things seem to be low stakes, but I'm sure there are some there are not (sex ed comes to mind).
to be fair, fusion does violate conservation of mass, just not the way the teacher explained it. the loss of mass is where the energy comes from.
Yes, together with mass-energy equivalency it would form a coherent argument, and then also a correct one - but the thing is that if incomplete, it still might sound funky enough to you to research it if you care.
I think it helps that it's a very narrow field to look at, compared to fuzzy and big-picture view of social studies, for example. So much room to be confidently wrong... And sadly I can't think of a solution, LLMs or not.
Yes, there is no law of conservation for mass like there is for energy. Fusion is a good example for why it's not conserved. The teacher was right.
He was right that it violates conservation of mass. He was completely wrong that it violated it by adding 2 atomic mass units when hydrogen fuses.
In reality heavier isotopes of hydrogen fuse, conserving the total number of nucleons, but the resulting hydrogen has a lower rest mass than the parent particles. The extra mass is released as energy and the total energy is conserved.
By his logic the system either violated energy conservation (by creating nucleons while releasing energy) or was endothermic (creating nucleons from the surrounding energy).
There actually is a law of conservation of mass (it's the same law, because mass is energy) and it only appears violated if you forget about the particles that are zooming away at the speed of light. Of course the mass of a system changes if mass can flow in and out.
Mass is not the same as energy. Mass can be converted to energy or has energy, but a photon, for example, is massless while carrying energy.
That is incorrect. Photons have mass. They have no rest mass. They also cannot rest, so you might wonder how relevant that is.
The concepts of rest mass and relativistic mass are considered outdated. In modern physics, "mass" means what they meant by "rest mass".
Here some indication I'm not making this up: https://hsm.stackexchange.com/questions/2465/when-and-why-di...
In any case, I never use those concepts, and I know no professional particle physicist that does. By "mass", I mean rest mass.
I had a chemistry teacher who told us that hydrogen reacts violently with oxygen, and this is how the hydrogen bomb works.
I had a chemistry teacher who insisted that the fissile isotope of Uranium was U-238 not U-235. I challenged him on this multiple times and he refused to budge on this. I get that it's a simple mistake to make (it seems like U-238 is bigger so intuitively ought to be less stable) but he could have just looked it up and he didn't, I guess he was just so confident about it that he thought there was no way he could have been wrong about it.
Hey it's a bomb made out of hydrogen! Also the deployment system for a thermonuclear bomb might involve that reaction in the rocket engine.
Well you can make a hydrogen "bomb" that way. Just not the hydrogen bomb.
I mean fusion and fission do violate conservation of mass and conservation of energy, they just don't violate conservation of mass and energy, right? We thought mass was strictly conserved until Einstein, and then we updated our understanding.
That's an American problem though. In most of Europe you need a masters degree to teach highschool and that involves at least an undergrad level of understanding the subjects you will teach.
E.g. in Hungary I had a university CS professor that originally wanted to be a highschool teacher and a highschool physics teacher that originally wanted to be researcher. Their choice of degree didn't determine which outcome they got. The researcher and teacher curriculum had an 80%+ overlap.
I think it’s pretty common for states to require a masters degree to maintain your teachers certification.
You also have to pass a standardized test specifically on subject matter in order to get your teaching certificate.
The undergrad degree I did was split into thirds, one for subject matter, one for teaching pedagogy, and one for teaching your subject matter.
I think they are less reliable. For factually verifiable facts LLMs are doing worse than 90% for me. I've been told some incorrect things by educators, but at a much lower rate.
The problem is that people seem to trust whatever AI hallucinated way more than if they heard same thing from human
To be fair, that was much of my actual experience with human professors in university.
Veritasium proved that in a difficult challenge.
A Physics Prof Bet Me $10,000 I'm Wrong
https://www.youtube.com/watch?v=yCsgoLc_fzI
Yeah one of my teachers was able to identify which high school I had come from due to something I had been mistaught.
Off the top of my head: DOMS being little crystals in muscles, tongue having separate areas for each type of taste, food pyramid, blue blood in the veins, the appendix being useless, body temperature doesn't change disregarding whether it's exposed to cold or to heat, and a whole lot of stuff related to politics and history I'd rather just omit (I don't live in the US).
All things I learned in school which were wrong information.
Not to mention, the current state of education is far worse. I don't think most realize how low the bar is.
One of my teachers in elementary school told us that people in the Arabic world wore long garments because as Muslims, they believed the Messiah would be born by a male, and thus, it was important to have something to catch the baby as it unexpectedly popped out one day and would otherwise hit the ground.
She only really had two faults: She wasn't very bright, and she wasn't fond of children. I had her in about 80% of all my classes for six years. High school was a relief.
My biology teacher in school once tried to teach us that winds created by God. Not like spiritually or something but that God literally made the wind I guess.
My “earth sciences” teacher also once tried to argue with me against the universal law of gravitation. (no, she was not referring to Special/General Relativity. She didn’t agree two objects in a vacuum fall at the same speed regardless of mass.
They'll also encourage and praise you even when you're heading down the wrong path until you think you've uncovered the secret of the universe or proven that established science was wrong this whole time when really you've just been bullshitting with an engagement bot.
No, they don't really do that anymore, if you use the latest models with reasoning enabled.
Like almost everything else about LLMs, this unfortunate tendency has gotten a lot better recently, which you might not realize if you gave up after getting some lame answers or bogus glazing on the free ChatGPT page a couple of years ago.
Anti-intellectualism is at it again, hu?
Like humans.
I think we should go a little deeper on this idea.
We can all agree that both human "experts" and LLMs can sometimes be right, and sometimes be confidently wrong.
But that doesn't imply that they're equally fit for purpose. It just means that we can't use that simple shortcut to conclude that one is inferior to the other.
So where do we go from here?
I’ve always thought of the definition of “expert” as reliably knowing the difference between what is known, what is speculated but unproven, and what is unknown. People claim expertise in all sorts of things that they aren’t experts in. But true experts should not be wrong. They should qualify levels of certainty. This definition certainly works in the sciences.
The amount of bullshit and blatant lies I’ve heard from my human teachers dwarfs the hallucinations produced by today’s LLMs.
They were a forcing function for skillz and they no longer are. We need new forcing functions for skillz or we will become WALL-E blobs.
Well, they were ostensibly forcing functions... ten years ago everyone was paying the exchange student to do their homework and assignments for them, and that guy was paying his cousin back in his home country, but the whole thing is a bit more efficient now.
We've already had consolidation of education for a while now. Even before all the edutech courses, there were Youtubers educating better than many university professors. 10-15 years ago students were already skipping lectures and just showing up for tests.
In my university education (2007-2011), 80% of the grade was based on exams at the end of each year, with no resits.
> We’ve figured out the human replacement pipeline it seems, but we haven’t figured out the eduction part.
No we have not.
>LLMs can be wonderful teachers
Are they or aren't they
As usual it depends. When it does well it's because it can do well. When it does poorly it's because you're prompting it wrong.
>When it does well it's because it can do well.
Can't argue with that logic
hammers are both a great tool and a deadly weapon at once
Not at once, surely
limp response brah, both possibilities remain plausible until one crystallizes at the moment of observation
A million times better than any human teacher I’ve ever had, for sure.
Now I’m certain that there exist those mythical human instructors who can do better, but that’s not worth much if 99.99% of people don’t have access to them. Just like a good human physician who takes their time with the patient is better than an LLM, but that’s not worth much either given that this doesn’t match most people’s experience with their own physicians.
Did an LLM teach you a topic you did not feel like learning?
For me the best human teachers were the ones that managed to make me interested on topics that I thought are boring/useless (many times my opinion being stupid, mostly due to lack of experience).
So far with LLM I learn about things I know something (at least that they exist) and I am interested in, which is a small subset of things that one should learn during lifetime.
Well I have some evidence to support your hypothesis. During Covid my kids were at home, eventually with some kind of self learning website from school. I was upstairs working, checking in with progress on the parents app. Finish your daily school work and then you can game.
The kids learnt all about Team Fortress 2, Roblox, Rainbow Six etc. They also learnt how to game the learning system so it looked like they were doing their work.
Good point well made.
>A million times better than any human teacher I’ve ever had, for sure.
Not really, not if you want to ask it deep questions. It won't have an answer that is deeper than something that you can find online, and if pressed it will just keep circling around the same response.
The reason is that this "thing" was never curious, never asked questions, and never really learned anything. It just has learned the Internet "by heart", and is as boring as a human teacher who is not really curious about the subject they are teaching, and has just got some degree by "by hearting" some text book. Of course it does it much better than a human, but it is fundamentally the same thing.
>Now I’m certain that there exist those mythical human instructors who can do better,
You're certain that mythical instructors exist (?) who "can" do better?
Are human instructors more competent as teachers than AI teachers, or are AI teachers more competent as teachers than human teachers? No "this or that can happen," just a definitive statement please.
AI is likely a million times better student than my dimwit cybersec meatbags...er, majors, for sure, as well! Don't have a reliable way to measure or experience why/how, tho, so I'm not out here claiming it. Even if I did, why would I argue for their replacement?
They can be incredible. One on one teaching with an infinitely patient teacher who can generate interactive problems on the fly, for dollars a month? Wild. A year of paid ChatGPT would pay for about 9 hours of cheap tutoring here.
That's not going to work out the way you think it will when a student won't even know how to ask questions.
"Education is just a CTF for the valuable flag of a credential. In this essay I will --"
I started teaching “how to build quality products using LLMs” full time recently, and most of what I teach is literally just the 101s of systems engineering, reliabily engineering, product development and project management:
Exceptional clarity on the problem you have
Know how to measure the problem you’re solving
Numerically define what “done” is
Make a deterministic and fully observable prototype
Iterate in production with the user
Expand user base as desired with user iteration in parallel forever
Etc…
Obviously a lot more in the details and these are all case by case, but these chatbots are basically perfect productivity machines for this process.
The massive caveat to all of this is this only works for people that can reliably and truthfully define those items above, are willing to structure organization to make those your priorities.
And actually most financial incentives demand the opposite of this process
If most organizations were honest about it, they would simply say “we’re here to make the most money possible and we’re gonna do whatever it takes to do that”
A lot of people don’t like that, so they don’t say it to come up with other bullshit.
Ultimately that’s why I felt like my only option right now is to teach people how to do this because I assumed it was obvious and it is not.
Smart people will use LLMs to learn things faster. Education will adapt by doing all assessments in person.
The best frontier LLMs can't solve 4th grade math homework yet. Don't hold your breath on that collapse of education.
(Real mathematics problems, not American-style ""math"".)
Do you have an example of a 4th grade problem in mind that isn't "American-style"?
Education is also figured out. You just need to learn, do and practice for yourself. Telling the agent "to just do it for you" is tempting, but it's not learning. You need to be deliberate when you're trying to actually learn and internalize.
Also, you could spin up your own educational agent with very strict instructions on guiding the user instead of just doing the work. Of course you can always go around it but if you're making an effort to learn, this is a good middle ground.
I feel the post. For me AI has ruined both, playing CTFs and also building CTFs challenges. The most annoying thing to me is the "yeah idk but here is the flag" mentality.
Before when playing CTFs with my mates was usually sitting there for hours tackling a challenge until some other mate joined, had some look together and solved it with you together in 30 minutes which is the most rewarding learning experience. Nowadays mate joins in throws the clanker on it and solved it in 5 minntes. Asking on how it worked you always get the "yeah idk what it did, but who cares, here is the flag" response.
Same for creating challenges. Whenever I ask for writeups or if some people solved it differently I usually get the "yeah idk, clanker solved that one" response taking the fun out of it.
So yep, this CTF format is definitely dead. Mainly because the strong competitiveness and prices. This encourages people to cheese challenges and sometimes solving them differently was fine as you still had a creative out-of-the-box thinking moment, but nowadays with AI there is no brainpower needed, no cheesing needed, no human needed. As you mentioned, it's pay to win.
My two cents is that the 24/7 CTFs will get more attraction as the scoreboard doesn't matter there and simply doesn't give you any price.
I don’t know like chess engines didn’t kill chess. You could just play with people that don’t use the “engine”
I was writing an obfuscator recently, I just had the model deobfuscate and optimize the code back to original and I kept improving the obfuscator until it couldn't. The funny thing is that after all this I also ended up with a really strong deobfuscator and optimizer which is probably more capable than most commercial tools.
The solution is just to make CTFs harder, but when do CTFs become too hard? Maybe the problem is that 'hard' CTFs are fundementally too 'simple' where it's just a logic chain and an exhaustive bruteforce towards a solution since there really are limited ways to express a solution in plain sight.
Or maybe human creativity has been exhausted and we're not so limitless as we thought. Only time will tell.
I had another idea spring to mind: we could hide two flags, one that could only be found by ai agents and not humans or tools written by humans.
A portion could require astral projection and computers can't do that. Or maybe just a VR mini-game like the 90s always imagined.
I used to help build the CTFs for BSides Orlando. I ended up moving to another con, and at our last event we collected extensive logging for post mortem analysis.
We found that AI usage is basically guaranteed now, but certain challenge designs did thwart it. Challenges built with temporal visual elements made AI fall flat on its face, as it could not ingest/process the data fast enough to act on them in time. We also found that counterfactual challenges (ie. the result you get did not match what we suggested you'd get) made AI-assisted solve time slower compared to pure humans, indirectly penalizing over-reliance on AI. Multimodal challenges combining audio and visual elements were also very effective, but were not as accessible to players.
This paper gave us some ideas about designing those challenges: https://arxiv.org/pdf/2308.02950.
For our next event we figured out a way to thwart AI in our CTF: embed the CTF in a game engine. The loop essentially becomes something like this: Connect to a simulated access point in the game, the K8s cluster connects their attack container to a private network with the challenge box(es). Hacking the boxes doesn't render a flag, but rather changes in game state. AI did very poorly coping with this in our testing, as it can't derive the spatial state of the game world very well and it soft decouples the inductive reasoning loop it relies on to know if it is on the right track.
The downside to this approach is it is far more labor intensive for CTF organizers, and requires players to have a computer capable of running the game. We are also betting on AI to not advance enough by the time we ship to be able to just ingest the entire game state in realtime and close the loop that way.
bringing CTF solutions into the real world is a really good idea! I didn't even think of this until you mentioned it.
we have very powerful simulation tools so something like "project a pattern at these angles" wouldn't really work as you could simulate that.
I guess something cool is that we can make simulating the solution very expensive, but in real world it would be free since it's analog... As long as simulations take longer than it takes for a human to find a solution it would be a pretty good way to deal with it. I am sure people smarter than me can come up with something.
Maybe I was too early to dismiss human creativity.
Maybe CTF is dead, but there are plenty of fun problems in the real world -- ask any scientist, engineer, or medical researcher.
There are a million places where a computer can interact with a non-digital system in a loop.
- Tune an FPGA, or a whole data-center, or just a physical computer.
- Make a drone fly somewhere.
- Design a selective toxin (or anti-toxin).
Or, you know, get more people to click on adds. All totally possible to automate.
Using real-life calculators to add? Calculate the Flag. I don't think it is dead at all. It's like mixing in board game / escape room / science / engineeer/ medical research elements.
Interesting, what I just did recently is basically the same of this as I tried to push the limit of js obfuscator as much as possible by keep forcing gpt/claude deobfuscate final output then having gpt improve the tool to break the deobfuscator.
Do you publish it somewhere? Here's a sample my my js obfuscator output: https://gist.github.com/Trung0246/c8f30f1b3bb6a9f57b0d9be94d...
Meta: this was submitted with the article’s title “The CTF scene is dead” which I found very easy to understand. It has just been updated to use the subtitle’s first sentence, “Frontier AI has broken the open CTF format”. I find that much harder to grasp, rather like a garden-path sentence. My immediate thoughts were that “Frontier” was a company name, and that there was some file format named CTF. If you don’t know about Capture The Flag contests, the change doesn’t help. If you do, I think the change makes it worse.
If it helps I understand the second much better and feels less clickbaity and includes more info. I do agree with the points you made about the confusion although I find frontier a term used in this area a lot, “frontier AI models have” would probably resolve that.
If the title simply said "AI is out-performing humans at CTF" then none of this confusion exists. Nothing is "broken," we don't need to be superfluous with "frontier," and the point is still there.
But the article is arguing it is broken. That’s the point. You can disagree but that’s very much that the author is writing about, not a curiosity, and that it’s these top models that are not custom security models.
CTF competitions and leaderboards are broken. Major competitions have stopped. Top competitors have dropped out.
It's like "Forklifts outperform humans in weightlifting". The problem, of course, is that a forklift is much easier to spot among athletes than an AI among CTF players.
Imo frontier is too niche and specific, if you know what a frontier model means then it's fine, but if you don't then it's negative/detrimental to the title.
"new" does the same thing and is probably just a better descriptor then frontier
if you are on HN and have no idea what "frontier model" would mean maybe it's time you found out.
I also misread the updated title.
"Frontier models break the open CTF format" is good
"Frontier AI..." means wtf is Frontier AI.
Because of course it exists (just googled it): https://frontierai.company/
But then you're not acting as a billboard promoting AI. Isn't that partly the point?
I agree, it took me a second to parse. It may be because this is the first time I've seen "frontier models" described as "Frontier AI". That sounds more like a company name, especially when the F is capitalized.
Frontier as in "Frontier Model" is a legitimate vocabulary term you should probably be aware of in 2026. It's not something the author made up or chose randomly, it's common parlance in the space.
The article never defined CTF. Nor have the top comments here. Skip.
Basic rule: define every abbreviation when it is first used.
Why do people always hijack threads to discuss titles? Most articles have terrible titles. Just downvote it and move on.
You can't downvote a submission.
Why do you contribute to making this thread longer? Just downvote an move on.
They can't downvote.
https://en.wikipedia.org/wiki/Capture_the_flag_(cybersecurit...
still has no mention of AI, but that will likely change as they increasingly dominate competition.
Using AI on CTF is like using a car to get better at the 100 yard dash
This is happening to other forms of competitive programming too. The most recent AIs have problem solving skills rivaling top humans, and so if AI can't be easily banned, the competition is dominated by AI agents.
I thought code golf would take longer for AIs because there's so little training data (it's more niche), but we're seeing AIs starting to match expert humans there too. Sucks because golf has been my favorite type of programming puzzle.
It's crazy how far AIs have come in problem solving ability.
Code golf is well-suited for AI because you have a easily verified objective (minimize code size while passing tests) and can run an LLM in a loop to churn away at it.
>The competition is turning into "who can afford to run enough agents, with enough context, for long enough."
This will basically become true for everything.
«That feedback loop is breaking. If the visible scoreboard is dominated by teams using AI, a beginner is pushed toward using AI before they have built the instincts the AI is replacing. That is an anti-pattern. It prevents active learning, and active struggle is the bit that actually teaches you. It is also completely demotivating to put in real effort and see no visible progress because the ladder above you has been automated.»
This stands out to me, and speaks perhaps broader than the article itself? I’m sure this has been in the spotlight before, but well put for many areas I think.
I see this with beginner programming students at university. They get AI to help them with assignments, with the intention of learning, but ultimately they do not get the understanding they would have if they had done the assignment themselves. Then they are at a deficit for learning more advanced topics.
My fear is that they never get to the level they need to be at to create good software even with the help of AI. So, although an expert with AI can create great software, that is not where we end up. In stead we will have vibe coded messes by people who barely have any grasp of what is going on.
Competitive programming scene always included offline competition and with AI they are becoming more important (and in general they were more fair even before). If CTFs are to survive, they should probably try to adopt this strategy.
You could even go so far that anything loaded on your computer is fair game, but not more than that (certain competitive programming competition for example allow unlimited amount of paper material - for CTFs you probably need much more than that, therefore electronic).
A big fraction of the comments on this thread are about the impact of cheating on competitive games. It's important to understand that automating CTF challenges isn't usually cheating. It's normally part of CTF culture. The better teams have toolboxes ready to shred the early challenges; it's not a level playing field and was never intended to be.
(The author of the piece understands this; I think they're broadly right, though I think these games will find other ways to incentivize participation without the now-meaningless leaderboards.)
This is already addressed in the blog post about the fast that frontier LLMs have moved to being able to solve the kind of problem you'd expect a talented amateur or mid-level pro to do (aka top level CTF problems)
It's not only CTFs. I strongly believe being a programmer at a gamejam like Ludum Dare, or hackathons is pretty much over.
Ludum Dare 59 just wrapped up last week, and both first and second place were won by developers using "Agentic" coding tools, something the community there is still discussing:
https://ldjam.com/events/ludum-dare/59/setidream/about-ai-ar...
For what it's worth, the non-AI-coded entries were still quite good relative to the winners, so it's not so obvious that AI use confers an unbeatable advantage.
I can't help but draw parallels with video games. Aimbots in competitive multiplayer games is a well defined issue: it's considered cheating and frowned upon, players caught cheating are banned from the game. Tool-assisted speedruns (TAS) where a player attempts a world record at completion in a single-player game is another face of the same concept (computers help you win), but one that is socially accepted as long as runs are clearly labelled as TAS.
The biggest difference would be the fact that you can discover video game cheating through some kind of trace. Speed running communities go pretty hardcore on that kind of thing nowadays.
It's a lot harder to detect cheating when your only trace is how fast someone submitted the string CTF{DUck1e_Pwned}
Aimbots in competitive multiplayer games are (almost always) game-breaking abuses. CTFs have always rewarded tooling and automation. They're different cultures.
Sure if the goal is entertainment and sports, you're right. However, unlike chess or counter strike it's downstream from a real needed utility. Like, is there a point to do it anymore? (ofc there is, but still, it's been devalued from the perspective of the 'real utility')
It’s literally not. The most interesting and satisfying CTFs have never been grounded in reality, it’s just been an expression of mastery, both from players and authors, with a few notable exceptions. But they’re that, exceptions, not the rule.
I don't do CTF's but took part at the security workshop for fun ~2 years with my Android phone only. I was first with the first simple challenge, but then couldnt continue because my phone was just too limited. But I watched what the others did. And a young Indian guy did everything with ChatGPT then. I found it silly, but amusing, because he actually got second. There was no Codex nor Claude then. Nowadays it must be dead for real, because I would solve everything with my agents, as I do in the real world.
I don’t think CTFs are dead, they’ll just evolve. The difficulty level will need to be increased or the rules locked down. Just like sports and racing persist despite the existence of performance enhancing drugs and rocket technology.
I just did a CTF where I was in the top 10. It was the first CTF I completed and I used AI because the rules permitted it. That said, I couldn’t solve all challenges.
But yes, it was significantly easier now than I last attempted one. Even manually solving with AI assisted assembly interpretation was much easier.
Increasing the difficulty level is a terrible solution. The problem with CTFs isn't that they're too easy. Making them harder just makes them even less accessible to people who don't cheat. It'd be like seeing people who put hidden electric motors in their bikes during Tour de France and conclude, "oh we just need longer distances and steeper hills".
When ctf organizers attempt to make a challenge "harder", I find they push the challenge into a more "guessy" state. Instead of proving skill, you basically need to guess some obscure or random step in the puzzle that the challenge is meant to give you. It is one of the most common problems with any puzzle based challenge system.
Exactly. The whole point of CTFs is that you could start on a simple one (CSAW was usually my go to one to recommend) as a complete novice who'd never done a second of computer security work and, after a few days of 8+ hours of running into concepts you hadn't encountered, googling, reading tutorial, practicing, overcoming the challenges to get a flag, etc., you'd come out the other end knowing a solid bit of security practitioner basics and likely whether you'd like to continue. Then you could keep going upwards and onwards. I went from 0 knowledge to a nice job in the field in a year.
Raising the difficulty only matters for the (imo) less important part: the dick measuring competition between the very top teams.
The actual point of CTFs was usually to keep your skills sharp and stay learning. Eventually you build your own challenges, thereby completing the "have it taught to me, then do it myself, then teach another person" three step process towards mastering concepts.
You can just say "let the people who want to learn from it do so" but honestly the entire culture of learning in the US at least is DEAD. We turned "education" into a rote system of maximizing incentives to the extent that that's all the youth know it as, and (increasingly) all educators can do. It's just gone without some kind of major reckoning, and we all know things will just collapse before that happens. The ball is in the court of whatever country can learn how to force its youth to learn the real way and use AI productively only AFTER learning the concepts it's being used to accelerate.
LLMs don't tend to help much when solving challenges beyond their skill level. Either they one-shot a challenge, or thei are almost useless as a companion for them.
That doesn't work. The thing that made CTFs fun is the fact that the challenges are solvable in a short-ish timeframe, usually a day at most, if you have the requisite skills and talent.
The issue is they become pay to win, which just isn’t as much fun.
I have normally found any sort of timed technical competition intimidating. Even so, about 6 or 7 years ago, after being persuaded by a colleague, I participated in a few CTFs. I am glad I did, back when this type of thing still meant something. I have kept a screenshot from one of the CTFs that I am quite fond of: https://susam.net/files/blog/ctf-2019.png
Yes you're right - But just like many other stuff things change - CTF Veteran for more than 3 decades I find lots of fun figuring out how to use some of my agents and new tools to find vulnerabilities - The goal is the same / tools change and that's good.
When I did my first CTF, it was close to the deadline and I thought I had the extracted the flag from the program and the rest of the program was just filler, so I entered the flag, and it told me it was not the flag. It turns out the program multiplies the input by a pseudorandom matrix before comparing it against the flag, so I had to implement a matrix inversion and then get the flag. That's not the story though.
The matrix was always the same and the challenge was clearly designed so that the point was being able to read anything at all, not knowing how to invert a matrix, so I asked the creator what was up.
He told me that there were tools that would trace input values until they reached a comparison instruction, then print what they were compared against. Therefore it was necessary for every deobfuscation challenge to scramble the input in some way too complex for these tools to undo, before comparing it. Hence the multiplication by a pseudorandom matrix.
The point is, cheating tools aren't new.
Yes but you can't compare some ollydbg script that would maybe be useful in a super specific challenge to LLMs which trivialise absolutely every challenge in a ctf and are de facto necessary to compete now
Interesting and well written article that mirrors/foreshadows how LLMs do and will change other scenes.
As I don't know much about the CTF scene, I looked for other takes on this topic.
Here's an article from 2015 about how tool-assistance already changed CTFs:
> Individual skill will undoubtedly be a factor next year. But, I'm left wondering whether next year's DEFCON CTF will tell us anything more than how well-developed each team's tools are (and how well they can interpret the results).
https://fuzyll.com/2015/ctf-is-dead-long-live-ctf/
But there are quite a few recent (2026) articles with the same core message as in the original article, e.g., https://blog.includesecurity.com/2026/04/ctfs-in-the-ai-era/ or https://k3ng.xyz/blog/ctf-is-dead
And here's someone explaining how Claude Max allowed them to win CTFs:
> I had always been interested in CTF as one of the only ways people could compete and show off their skill in coding/problem solving on a global scale. It was just too difficult and didn't make sense for me to learn the fundamentals as an electrical engineer. As time went on, I got better and better, and it was hard to tell whether it was because of experience or if it was because of improvements in AI.
> I accomplished my goals, and for that reason I'm quitting CTF, at least for now. [...] I'd like to think I highlighted the problem before it became a bigger issue. So, how do we fix this? Teams and challenge authors losing motivation is not good. CTF dying is not good. AI bad. Or is it?
https://blog.krauq.com/post/ctf-is-dying-because-of-ai
The only article that saw LLMs as a non-negative force for CTFs was this one. Fittingly, it sounds like LLM output ("Let's be honest", "This is where things get interesting.") and only contains hallucinated references.
https://caverav.cl/posts/ctfs-not-dead/ctfs-not-dead/
The "CTF for fun" aspect has been dead ever since the winning teams had thousands of dollars of rewards waiting for them. Of course people are going to use anything that's not explicitly forbidden by the rules to win. Introducing what amounts to an "I win" button that both can't be prevented by rules and is accessible to anyone didn't "break the format" anymore than the epidemic of giant merger teams did a couple years ago, it just broke the community because you now don't have to actually talk to other people to cheat anymore.
Many CTFs have switched to a dual-leaderboard format recently, one for "agentic teams," one for the rest. If all you care about is "learning" and imaginary internet points, you can just participate as a human team and adblock the AI scoreboard, and maybe lobby CTFTime into splitting their rankings as well.
You could make it offline and with provided laptops only, just like with the competitive CS2 scene.
Offline CTFs could also incorporate physical security challenges, like lockpicking
The recent LakeCTF onsite finals had exactly that. LLM usage was forbidden (but players still used their own devices) and there were real-life challenges such as lockpicking as well. I’m part of the organizer team and what we’ve heard so far from participants was that it was really enjoyable not to have any LLM help because suddenly the actual skill and thrill when solving a challenge mattered again. I think what helped in this case as well was that the prizes weren’t high-value enough to incentivize cheating but that participating in the event itself and the social aspect around it are the main point.
I do like the idea of escape the room games becoming the cybersecurity employable competition meta
They often do
Ctfs need preparation and unconstrained internet, even if you block domains it’s possible to tunnel out
Unconstrained internet is nice, but I don't think it's a hard requirement. Just tricky to enforce, even in-person.
It is a hard requirement. Once you reach higher levels of challenges you spend most of your time reading through RFCs, web sepcs, Github issues, mailing lists, papers, random bugtrackers and library/framework code. There is no way to create a whitelist for that. Besides, a firewall won't stop good hackers.
Normal CTF workflows can involve a lot of research but that's not the point. You can design self-contained challenges with offline solving in mind, and bundle any truly necessary docs/src/etc. with the challenge download.
Presumably if you block domains, you wouldn't be able to use AI to find a way around the block. So doing so demonstrates at least some human skill
Proxy through an EC2. Ask me how I know.
Or forethought, I’m sure you could ask an AI how to circumvent any blocks.
Use jumpbox to access CTF. Disable all wireless for the playing hall.
I think you’re forgetting hotspots, or laptops with inbuilt 4/5g
Faraday cages exist. Finally a use for all those damn SCIFs tech companies were building in the late 2010's...
Since real-life situations involve AI, banning AI would make CTFs just a simple game, not a demonstration of capabilities and talent.
What do you mean? Solving a CTF challenge demonstrates way more capabilities and talent than just asking a chat bot to solve a CTF challenge.
They always were just a game?
The first paragraph on anything with an acronym in it should explain the bloody acronym. I assumed CTF was an encryption standard, given the headline. It was only coming here and reading the comments that made me realise it's a game-format ("Capture The Flag").
I don't know what to tell you. If you don't know what "CTF" is you're not the target of this blog post. It's like stumbling upon article "What's new in HTTP/2" and complaining that "HTTP" acronym is not explained.
I don't mean that everyone must know what CTF is, but sometimes it's OK to write things just for your community (CTF community in this case), not for general population.
Capture the flag the only expansion of CTF that i know but even if it is capture the flag this still doesnt make any sense. Like Quake CTF?
https://en.wikipedia.org/wiki/Capture_the_flag_(cybersecurit...
What is CTF? And why is the cyber security world filled with silly gaming references?
Capture The Flag is a cybersecurity game where the organizers set up a bunch of intentionally vulnerable computer systems with a "flag" on them, a string that's "supposed to be" secret but is accessible through exploiting the vulnerabilities. This may be a line in /etc/password, a string in memory, a field in a database, whatever. The goal of the game is to hack into the computer systems, find ("capture") the flag, then copy/paste it into the organiser's scoreboard website to prove that you solved that particular challenge.
It's pretty fun. Or at least it was, back when you had some sense that your competitors were competing on an even playing field and just beat you because they were better than you.
I wouldn't say the name is a "gaming reference", it's just a descriptive name for a game.
https://en.wikipedia.org/wiki/Capture_the_flag_(cybersecurit...
Its a war game reference I guess?
There's something funny about complaining about cheating in a hacking competition.
Well actually I get it. In cycling motor doping, putting a hidden engine into the bike, seems more offensive than regular doping. I think this is because there is a continuum from eating well to taking supplements to injecting stuff, but having a engine breaks a fundamental idea about cycling. Similar hacking is about cleverly abusing the rules.
It's tough. We run botsbench.com , which tracks AI progress on a top CTF, and I gave a talk at CCC a few months ago on our own results doing AI speed runs, so I think about this a lot.
In our own trainings we give (AI agents for security, and a graph masterclass), we ended up leaning into it. For example, we ship with a skills bundle. There are plus sides, like less code-forward participants can go further and are appreciating that, and less of a gap between high-level concepts and successful hands-on. But at the same time, manual work does build a lot of intuition & knowledge that gets missed in auto modes.
Will this bring back the age of LAN parties, where the LAN is disconnected from the internet, and mobile connectivity is blocked?
I think that ship has sailed as well --
botsbench.com shows Sonnet 4.5+ with Claude Code harness does pretty well, and Sonnet roughly tracks the edge of what self-hosted models do on the upper tier of affordable GPUs, like running 1-2 DGX Sparks and waiting 6mo for oss to catch up a bit
>If adaptation means accepting that the scoreboard is now an AI orchestration benchmark, then we should say that honestly instead of pretending the old competition still exists.
This is like someone complaining that making machine parts has been ruined: Skillful craftsmen used to make them by hand using manual tools!
Nowadays the CAD/CAM/CNC cheaters have almost completely automated the whole thing. How is the next generation of craftsmen going to learn how to craft a gear by hand when the process of gear making has been reduced to pressing start on a CNC machine?!
See what I mean? Sorry, I think this article is just Luddite. I can empathize with the pain of your beloved craft basically being rendered obsolete by new technology, but the process can neither be stopped nor is it bad in general.
The manual skills you trained with CTF puzzles are now simply no longer relevant . (Field-specific) "AI orchestration" is the new cyber securtiy skill if LLMs really have become so good at this, and what the author used to do manually then has the same value as being able to craft a gear by hand.
Just parachuting in to reflexively throw the "Luddite" label at someone lamenting the decline of a niche community they've enjoyed participating in and contributing to is certainly ... a choice.
Within the framework of your analogy, it's like responding to someone active in DIY maker groups suddenly dealing with an influx of influencers in meetups showing off Chinese junk from Etsy to post on Tiktok, and accusing them of being a Luddite blinded by their zealous hatred of mass production -- both strangely abrasive and also fairly nonsensical except as a "mass production supporter" social signifier.
Not to mention, in the article they specifically describe themselves as a heavy user of frontier models for security research ever since the release of Opus 4.5, calling them "useful within the field". In fact I don't see any actual criticism of AI/LLMs anywhere whether for security research, programming or anything else, except for making competitive CTFs no longer viable.
What does it take to avoid the "Luddite" brand? Using AI themselves and praising AI as useful (to the point of having a lopsided advantage over humans) isn't enough? Do they also need to say "I haven't written a line of code in 6 months/it's easily a 100x multiplier for my job" every time they mention it too?
The way I read the post is that the author is disappointed that the community is gone. The CTF was just a reason for a number of like-minded people to organize around an activity.
Indeed, in the real world, plenty of people organize to do formerly-skillful tasks together. I have not personally crafted a gear by hand, but I have built a house in a long-abandoned style with a group of people only using hand tools.
There _is_ a danger that society forgets how to do these things. During that house-building exercise, there were many tricks of the trade that, while likely documented somewhere in a book, would have been difficult to reproduce without seeing a demonstration. From the standpoint of “does it matter?” it depends on what you care about. We absolutely do not need cruck-framed houses with scribed joints. Modern construction is faster and cheaper and lasts long enough. But it would sadden me greatly if practices like this faded from memory, because it’s one of those things that makes you gasp “wow!” when you see it. And your appreciation only deepens when you try it yourself.
Is AI also superior to humans at black box challenges and attacking actual targets on the internet? That seems like a really important question.
No, the search space is much more vast and the feedback loop almost nonexistent.
The reason LLMs can do CTFs so well is partially because the challenges are usually designed to avoid wasting time and to introduce a single concept without noise.
I guess this is very similar to what happened to demo scene, in some way. The limits are what makes these problems interesting, and once we have better machines / tools, the incredible skill is no longer prerequisite, making everything less interesting for participants. Sad, but - such is life...
I think soon there will be ways to trick this models and I think when it happens it will be yet another layer like aslr
These models seems completely unbeatable only in the ads. There are 100+ times way someone puts Hindi Yoda talk In Morse Code and it goes nuts. The reason they are going to hard for PR Marketing on this is because they know it is a matter of time.
The more you obfuscate a topic against LLMs the lower the educational value of a challenge.
The only things that works is novelty and obscurity. LLMs still suck with things mentioned in the footnotes of datasheets and manuals, things that deviate in subtle ways, unique constructions that alter something very very common. It's hard for LLMs to avoid common pitfalls in terms of making assumptions, while staying on track.
CTF = Capture The Flag
https://en.wikipedia.org/wiki/Capture_the_flag_(cybersecurit...
Great article, well written, and good analogy to chess. I’ve been playing competitive chess most of my adult life and I think that the solution lies in how chess dealt with this problem:
Explicit ELO measurements with some cheating detection. AI assistance wholly banned. As you climb the ELO ladder, detection gets more onerous. At top level during online events, anti cheating teams require the use of both monitoring software and multiple cameras.
Idea is that you can cheat pretty easily at the lowest levels but it gets less easy the higher you go. This allows for better feeding into the truly elite competitions.
I think chess’s very firm stance that AI is never allowed in competition (neither online nor in person), rather than CTF’s acceptance, was the right call.
Yes, chess has been dealing with AI for decades at this point, and it's amusing/frustrating that so many other communities are deciding to re-discover everything from scratch, rather than just learn from the chess experience.
If CTF is a player-vs-player event, then AI should just be banned outright, otherwise it will devolve into AI-vs-AI, which is just not an interesting competition format, as we learned in chess. Compared to FIDE top events (which bans AI), only a tiny niche audience actually watches the Top Chess Engine Championship (AI-centered). It turns out what we care about is not whether chess can be solved by any means available, but what are the limits of the human mind in learning chess.
Pretty much all chess coaches/educators also warn against relying heavily on AI during learning; engines only give you an illusion of understanding.
You can still do competitions. But you'll all need to fly to the same place and work on laptops with a fresh install of Linux. 1 hour to install tooling then Internet off, challenge revealed.
Not as easy logistically...
,,a beginner is pushed toward using AI before they have built the instincts the AI is replacing. That is an anti-pattern.''
The same article talks about CTF skills as a way to learn about security best practices and separately a sport.
In reality it was all about learning an extremely important skillset (securing/attacking software and systems) that is getting automated.
The real thing the author seems to be frustrated about is AGI is coming in computationally verifiable domains first, and lot of his skillset was taken over in a big part.
easy, CTFs should ban it. then it'd be more like the chess community
The article addresses this:
> Rules that ask people not to use LLMs are ignored and almost impossible to enforce in open online events.
It's quite sad to see CTFs dying. I never had the time do seriously participate in CTFs, but I always respected those who did, as well as the people organizing these events.
This left a strange feeling. The article reads as extremely bleak. But from a different perspective this is extremely bullish for AI.
I agree. The article mourns the death of pentesting as an art form due to automation. But you could also celebrate the death of pentesting as an arduous necessary evil due to automation
LLMs managing the "coloring book" equivalent of something is not bullish for the "art" version of something.
The intent for most CTFs is to provide a meaningful challenge that concerns a single topic without introducing noise that wastes time. Of course a training exercise is easier to complete for an LLM.
Question: Was this website made with Claude?
I've seen that exact font and color scheme a dozen of times the past weeks.
The text is LLM output.
“solve”, why not solution? Like “spend” and not expenditure, why use the verb as a noun and not care about grammar?
In addition to what others have said, this usage is very common in the CTF world. "The challenge has no solves", "We just got the first solve" etc are very idiomatic. It would actually look weird to me if this was "solution".
These examples that you're calling "verbs as a noun" are standard grammar. You can't just invent simplified rules about a language and declare it wrong when the rules fall apart.
They’re shorter.
Why so pedantic?
Do CTFs like Lan parties or factor in new tooling avalable to people. change is not death. or death is not an end. either way, people will enjoy applying and showing off their skill. competing with eachother on a human level,.with or without ai tools.
I'm conflicted on the use of AI in CTFs. On the one hand, they are supposed to mirror real-life scenarios, so of course you should be able to use any tool that would be available to you in real life.
On the other hand, CTFs are fundamentally a game and a competition which are supposed to be fun and compare and improve ones skill. So when I let an LLM generate the entire solution for me, what's the point anymore? I did not learn anything. I did not work for that place on the leaderboard, I just copied the solution. And worst of all, I did not have any fun. It's boring.
So how does using AI as a solver not feel like cheating?
I’m interested in finding out how attack-defense style CTFs are affected by slopping. ENOWARS skorbor will probably significantly differ from the last time around.
Chess and Go are not dead just because Ai got better than humans at these games.
What am I missing here?
These have very strong anti cheats and in person is very stringent on no electronics.
Its not really a good comparison
You aren’t allowed to use tools to play competitive Chess / Go but that are required for solving CTF.
Chess banned engines from competition. CTFs can't really do that because you need internet access and tooling to play.
Read the article.
I read the article. Their chess section makes no sense as in "why this wouldn't work for CTF".
But I don't know enough that's why I asked.
I imagine one could do CTF in public, machines you work on vetted/prepared to some spec, yada yada.
If chess and Go can do it why can't CTF?
That was my question when I wrote "what am I missing here".
https://news.ycombinator.com/newsguidelines.html
"Please don't comment on whether someone read an article. "Did you even read the article? It mentions that" can be shortened to "The article mentions that"."
We’re in an age where, to be possibly a bit rude but blunt, pseudo-intellectuals are obsolete. A pseudo-intellectual prided themselves on being able to efficiently solve closed, man made problems such as leetcode, CTF problems, or even math Olympiad problems. They could do good in school by memorizing a rote technique and applying it to some test. They typically don’t have any real creativity and if you put them to work on a problem you can’t Google or isn’t a fake man made one, they fall apart incredibly fast.
They may as well be the human equivalent to what LLMs currently are.
I do not mourn these people, as they’re usually the most arrogant types. I hope for their sake they adapt.
I thought a company called Frontier broke a file format CTF.
AI-generated phishing is the scariest development in cybersecurity right now. Click rates on AI-written phishing emails are 54% compared to 12% for traditional attacks. Automated real-time detection is the only scalable answer at this point
Unable to find what “CTF” means, since it doesnt look like referring to Capture The Flag gaming
It does--but a particular form of Capture The Flag where there is a computer system and the "capturing" is breaking in or exploiting a security issue in that system.
Neither the article nor the comments in this thread explain which of the many meanings the acronym CTF is being applied to...
In this context, it stands for capture-the-flag: A type of computer security competition, usually in a 'jeopardy' style, where challenges that fewer teams have solved are worth more points.
Very impressed that OP has gone from starting university in 2021 to becoming a Senior Security Engineer.
It's an incredibly exciting time in security research in my humble old man opinion.
Think the cadence of new exploits is perhaps a good measure of that rather than subjective thoughts by anyone regardless of experience.
Okay, but none of that is actually responsive to what the article is discussing, which is competitive CTFs. There's not a single criticism of using AI for actual security research in anything they wrote and they mention being a heavy user of GPT-5.5 and GPT-5.5 Pro so belittling the author's experience to defend LLMs wasn't actually necessary.
My first ever was Stripe CTF in 2012 I think, I still wear the shirt I got (now super fainted) from passing some challenges. I was a student in portugal and remember receiving the shirt for it and thinking, maybe those Americans aren't any better than me and I can compete at the same level.
I never got super into security but it gave me the confidence to play in the same field and lose the stupid aura I had that somehow "rich americans" would be better than me at everything because they had better universities or because of Hollywood or something.
Sad that another cool thing is lost to AI but I guess kids will learn in other ways.
How to motivate cybersec best outcome reddit 2026 no mythos
>Imagine giving every competitive chess player the best chess engine and letting them use it freely during matches. Would that be considered fair?
Imagine every competitive chess player being allowed to video call with a hundred other people to help them make a move. CTF have never been fair, nor has it ever been effectively structured for learning.
used to see some really good CTF videos show up on youtube and now nothing like that shows up on the feed
Pretty ironic that this article was also written using LLMs. It has all the LLM-isms.
You can introduce canaries, and ban auto-pwning in general. that's usually banned anyways. Some challenges just can't be solved by a human in under a certain period of time.
Another idea is deep red herrings. solves that lead to more solves, on and on, except only if the previous solves were solved quickly. The effect will be that participants who solve things quickly will keep finding things to solve. they can't know that the path they're on will lead to victory, even if they artificially slow down, unless they consistently slow down just as a human would. It will eliminate the speed advantage. For the skill advantage, other than having another LLM procedurally generate challenges, I don't know of a good solution.
There are always things like captchas. or the good 'ol honor system. A person can spend only so much for things that have no financial reward in the end, only clout.
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Alright, all that said, i think i really do have a good solution for this, as well as academic exams. Or I think I do, because it's so simple, I've been scratching my head as to why everyone isn't doing it already.
Require screen sharing/recording. LLMs can't fake that well enough. Have another LLM audit the video for mouse, key stroke, window movement and other details to see if it looks human-generated or not.
If a student has an essay assignment, have them record their screen as they research, and actually type out the whole thing. In the extreme, require anti-cheat proctoring software installed, as is done in remote examination. In an even more high-stakes and extreme scenario, have them share their face. Their eye and face movement, correlated with the screen-share, and correlated with the activity observed on the server end, should be pretty hard to beat, even in the next ~5 years of LLM advances.
>I started playing CTFs in 2021
>and the old game is not coming back
For many people the CTF scene was already dead in 2021 because it had turned into something unrecognisable.
In reality it’s just different.
Well, I had to google what CTF means (capture the flag, a hacking competition), so surely cannot judge here, but the text indicates that with AI some things are very different today:
"That makes open CTFs pay-to-win. The more tokens you can throw at a competition, the faster you can burn down the board. Specialised cybersecurity models like alias1 by Alias Robotics are becoming less relevant compared to general frontier LLMs. The competition is turning into "who can afford to run enough agents, with enough context, for long enough.""
Isn’t that the bitter lesson in a nutshell? “Specialised cybersecurity models … are becoming less relevant compared to general frontier LLMs.”
There are two different schools of thought:
1) It’s OK to do just about anything to win a CTF, including installing malware on the organisers computers months before the actual event so you’ll have an easy time stealing the flags.
2) It’s not ok to try and win the CTF with a solution the authors did not intend.
Recently the #2 crowd has been winning because the hacking scene has turned corporate and boring. People started to partake in CTFs in the hopes of landing a job(!)
CTFs are indeed ruined for those people, I personally don’t mind.
For the people in group #1 LLMs change little. Attacking the challenges directly was always a last resort.
Yeah I remember running a few CTFs in school and was always scared (in a good way) about what the players would do to the game's servers. For this reason we also only ran the CTF on the school's network and IT even floated running in an isolated VLAN.
The fact that CTFs became a sort of SAT score for getting a security job made me lose interest very early on.
>Learning about eternal September in May 2026
Hits different doesn't it
I started playing in 2015 or so and had mostly stopped by 2020. Not because I felt it was "dead" exactly but it just wasn't hitting the same for me. By then it wasn't "the winner has the most LLMs", but "the winner has the most members on their team". I merged into one of the mega-teams and it just wasn't fun any more.
I helped arrange my country's longest living CTF this year. Our CTF is *made for amateurs*, but we always have challenges for intermediate to skilled players and the top of the scoreboard is usually topped by them. It is the compromise we have - amateurs get so many tasks they struggle to solve them all, and the pro's get to win. Our goal is to nerdsnipe people who are curious into trying our CTF by offering easy beginner tasks, and then get them hooked enough to stick around for the intermediate ones, even if it takes them a day to solve one.
This year, multiple groups on the top of the leaderboard were clearly abusing LLMs. You can tell because they know nothing of what a CTF is nor the terminology, nor really the fields the challenges were about when they were talked to. They were obviously amateurs.
It was pretty depressing to hear how unaware they were of how obviously they did not fit in to the type that usually is on the top of the leaderboard. It seems they seriously think they were under the radar. If it was one group it could be a freak incident - some times someone just shows up and curbstomps competition. But there were many groups like this this year. They also had a certain smugness to it - one staff reported that a group was hinting to other teams about their "super weapon". Another group credited their "secret third team member they didn't want to talk about".
I use LLM frequently and experiment with it a lot, both at work and on my free time. Nowadays they are good enough to have value and I am interested in learning more about that. They let me spend more time on hard problems and avoid spending the day on simple CRUD. I say this to say that LLM doesnt have to equal bad, it is a tool, that's all. However, I generally avoid LLM communities because many LLM fans are lazy and unskilled people who are just happy they can feel they are worth something even if they have no skill. They don't really have much to provide of conversation. If anything, from reading the CTF crowd this year, the rise of LLMs has just meant more of these people can stomp on and harvest the CTF scene for self validation.
This is not me trying to gatekeep who can play CTF. Anyone is welcome, but there is one condition: You are here to learn and have fun.
The conclusion many I talk to has come to is that nowadays, it is harder to learn to put in hard work and become good at something because there are just too many ways to cheat and take shortcuts. I suspect in the future there will be a shortage of useful people - the kind that have critical thought and know the value of doing something properly. This doesn't mean "Not using LLM", but as said by many on HN before you need a certain seniority before LLMs are useful augmentations to your skills and not just stopping you from learning yourself.
I agree with the article. Anything but physical competitions with strong security - think professional e-sports with organizer-provided PCs, is over. But I think one of the most interesting things to take away from my CTF experience is that the bottom of the leaderboard was still full of amateurs slowly working their way up - it is a few rotten apples that ruin the fun for most, and there are still plenty of people who want to learn and deep-dive.
No relationship with the CTF (Common Trace Format) format ..
Unrelated, but does anyone find this site incredibly hard to read?
Bizarre font and poor contrast, yep.
The text itself being exceedingly long for no obvious reason doesn’t help.
Poor contrast? White on black?
And if you think it was too long, what part would you have shortened? I never knew about the scene and found it interesting to read this personal take on it.
> White on black?
According to Pikka, the paragraph text is Taupe Grey (#92908a) on a Liquorice (#111110) background. That's... pretty far from black and white.
Right, the same way that car racing has "broken" jogging. This is so dumb. /s
The whole point of competitions is to provide a safe environment thanks to a set of rules all participants AGREE on in order to progress together.
If new tools "break" the competition, we change the rules and that's A-OK.
CTF isn't a natural phenomenon, if tools change, rules change, simple.
The only way this actually works is if you move CTF to in-person only. There's no other way to reasonably prevent the whole leaderboard being taken up by whoever spent the most on tokens.
Sure, I don't know how to make it work. I just know that DeepBlue didn't kill competitive chess. We simply have at least 3 different rule sets, namely
- no computer assistance, which does also mean no mobile on competition, human only
- advanced chess with assistance
- computer only, no human assistance
and arguably chess itself is not doing worst since.
I think the big difference here, is that organisers of chess tournaments don’t have to design multiple entirely new board games for each competition. When AI can one-shot CTF challenges, you have to develop new challenges in secret for every competition, and they are single-use.
tldr; adapters took my elo
The article is the thickest of AI slop. Don't believe anything.
ikr, if bro can't be bothered to write an article himself then anything he says is automatically suspect
Don't hate me, I do agree with the premise of the article (I really do!) but I can’t help but notice:
>The issue was never that AI could help. proceeds to write the next 3 sentences about how the problem IS in fact ai help
>Teams that refused to use AI were not just missing a convenience; they were playing a slower version of the competition.
>CTFs were not just a set of puzzles. They were a ladder.
>The claim is not that every challenge is solved. The claim is that...
>The loss is not just a scoreboard. It is the ladder from
Guys I'm so sorry I just can't stop noticing stuff like this. Anyone else?
I got some AI writing vibes too, but looking closer, I think it might be human-written (or at least partly so) - perhaps just picking up some AI conversation styles? FWIW, Pangram gives it a mixed but mostly-human score too. Maybe AI is not just changing the way we speak; it's changing the way we perceive all writing ;)