What do you think about this one?
A Student Used AI to Beat Amazon’s Brutal Technical Interview. He Got an Offer and Someone Tattled to His University
I may be a old man yelling at the clouds, but I still think programming skills are going nowhere. He seems to bet his future on his 'predictions'
The interview process being broken doesn't mean the job is broken/useless. It's shitty IMO that Columbia university wants to take "disciplinary action" for exposing useless interviewing practices. It would've been better to tell Roy about ethics and say "If you want to do this kind of stuff, that's fine, but here's the way to do it. In fact you can continue doing this at our university and make a career out of it. Let's talk."
And Amazon's reaction is also dumb (as expected). They should instead be hiring this dude to improve their interviewing practices by letting him build internal tooling to try and defeat the interviewing process. Of course they won't do this because there is a certain prestige in getting a FAANG job. Keeping recruiting costs low but interest high with a high rejection rate is the goal for recruiting.
I'm not quite sure there's a winner in this triangle, except those outside it: this might force companies to change their recruitment practices. My guess is that there will be a lot of resistance first and more money will be spent on "fraud detection" than actual improvements. It will be a cat and mouse game with probably the companies losing, but at least some C-suite bastard will get rich selling the fraud detection solution 🤷
A guy in a bank ferrying billions in my neck of the woods told me how 'most' software jobs involve cutting and pasting snippets fron the likes of git, sourceforge, etc. His bank is in deep on AI, be it on operations, or investments. On the one hand, I admire his disconnected bliss, but damn, all the money is being moved by the people who don't understand coding, and being given to the people who don't know how to code. State of the bubble right now. FML.
Honestly, Columbia's reaction feels less about ethics and more about damage control. Lee didn’t cheat to land a job — he built an AI tool to expose how broken Big Tech’s hiring process is. Ironically, that shows the kind of problem-solving and innovation those companies claim to value.
What’s troubling is the university’s overreach. His actions had nothing to do with his academic work, yet Columbia is stepping in — not to uphold integrity, but seemingly to protect its reputation. It looks like a "Bauernopfer" — making an example of Lee to scare other students away from using AI tools.
But there’s a deeper issue: universities are losing their grip on being the sole gatekeepers of knowledge. AI and open-access information are disrupting traditional models, and instead of adapting, institutions are doubling down on outdated rules. This isn’t about Lee’s tool — it’s about "Geltungsverlust" — the fear that their authority is slipping in a world where students can bypass conventional performance measuring schemes.
-- Generated out of discussion with 4o as from a european standpoint I can't understand why the uni was even allowed to act
Should have read it to the end and totally agree
“It’s an attempt at a standardized test that measures problem solving, but in today’s world that’s just obsolete.”
The only thing AI will replace is small, standalone scripts/programs. 99% of stuff companies actually write is highly integrated with existing code, special (sometimes obsolete) frameworks, open and closed source. The things they throw at you in interviews is generic scripts because they aren't telling you to read through 6k lines of korn shell scripts to actually understand and write their code. And they won't have you read and understand millions of lines of code, configs and makefiles to implement something new, in the interview.
He basically cheated on his little brother in Mario Kart and thinks he can now beat Verstappen on the real track. Bro needs to get a reality check in an actual work environment. Especially in a large company.
I recently needed to implement some batch processing logic in our code to account for some api level restrictions (the code already pulls from the api in pages and date ranges, but if I specify a date range too wide or a batch that would get too many records back, it gets rejected, so we need to break it down and run the date range in batches). I tell this junior developer what the issue is, and what we need to add to the existing class in our codebase. I follow up with him after a week, and this is what he sends me.
Boilerplate code from chatgpt that has almost nothing to do with what we discussed. And how can you even give me a whole 'working' code without even testing it? He didn't even clone our original repo and test it as is to understand why we need what we need. AI sure is making programmers dumb.
I would argue that he is not a programmer
Does it least actually have something to do with PayPal? And is pandas actually useful? lol
I can understand commenting ASM, optimized C code can use some comments too, but commenting python should be a crime, as its function calls document themselves, and you'll usually split data over named variables anyway.
For now. Eventually, I'd expect LLMs to be better at ingesting the massive existing codebase and taking it into account and either planning an approach or spitting out the first iteration of code. Holding large amounts of a language in memory and adding to it is their whole thing.
Hopefully we can fix the energy usage first.
I have a feeling that the Dyson sphere will end up powering only the AI of the world and nothing else.
They can context and predict contextually relevant symbols, but will they ever do so in a way that is consistently meaningful and accurate? I personally don't think so because an LLM is not a machine capable of logical reasoning. LLMs hallucinating is just them making bad predictions, and I don't think we're going to fix that regardless of the amount of context we give them. LLMs generating useful code in this context is like asking for perfect meteorological reports with our current understanding of weather systems in my opinion. It feels like any system capable of doing what you suggest needs to be able to actually generate its own model that matches the task it's performing.
Or not. I dunno, I'm just some idiot software dev on the internet who only has a small amount of domain knowledge and who shouldn't be commenting on shit like this without having had any coffee.