What I think is disappearing is not so much the quality of academic education, but the baptism by firehose that entry level CS positions used to offer - where you had no choice but learn how things actually work while having a safe space to fail during a period in your career when productivity expectations of you were minimal to none.

That time when you got to internalise through first hand experience what good & bad look like is when you built the skill/intuition that now differentiates competent LLM wielding devs from the vibers. The problem is that expectations of juniors are inevitably rising, and they don't have the experience or confidence (or motivation) to push back on the 'why don't you just AI' management narrative, so are by default turning to rolling the dice to meet those expectations. This is how we end up with a generation of devs that truly don't understand the technology they're deploying and imho this is the boringdystopia / skynet future that we all need to defend against.

I know it's probably been said a million times, but this kinda feels like global warming, in that it's a problem that we fundamentally will never be able to fix if we just continue to chase short term profit & infinite growth.

> If you earned your CS degree (or any degree) before 2022 or so, the value of that degree is going to grow and grow and grow

In my experience, target schools are the only universities now that can make their assignments too hard for AI.

When my university tried that, the assignments were too hard for students. So they gave up.

That’s an insight that a project I’m working on has built upon: https://unratified.org/connection/ai/higher-order-effects/#1...

Education and training and entry level work build judgement.

That's not something enthusiasts here and elsewhere want to hear, that's pretty obvious also in this discussion. People seems extremely polarized these days.

AI is either the next wheel or abysmal doom for future generations. I see both and neither at the same time.

In corporate environment where navigating processes, politics and other non-dev tasks takes significantly longer than actual coding, AI is just a bit better google search. And trust me, all these non-dev parts are still growing and growing fast. Its useful, but not elevating people beyond their true levels in any significant way (I guess we can agree ie nr of lines produced per day ain't a good idea, rather some Dilbert-esque comic for Friday afternoon).

We're now reaching the point where people have gone their whole college education on AI, and I've noticed a huge rise in the number of engineers that struggle to write basic stuff by hand. I had someone tell me they forgot how to append to a list in their chosen language, and couldn't define a simple tree data structure with correct syntax. This has made me very cautious about maintaining my fluency in programming, and I'll usually turn off AI tools for a good chunk of the day just to make sure I don't get too rusty.

"Those who can't, do..."

> think the folks burning thousands of dollars of credits are unable to describe what they want.

Basically, yes. I bought 'business tier' and I know about webdev but I'm somewhere between intern and junior, so I do a lot of discussing. One session is "I want [functionality and constraints], ask me relevant major design questions" then implementation, then me investigating and asking for fixes.

  > I think the folks burning thousands of dollars of credits are unable to describe what they want.

I don't see the value of a junior instructing an AI, because I as a senior can also instruct an AI.

I perceive the AI itself as a very fast junior that I pair program with. So you basically need the seniority to be able to work with a "junior ai".

The bar for human juniors is now way higher than it used to be.

I used to do online interviews with full access to Google or any online resource (so long as you shared your screen and I could see). Use your own code editor, no penalty at all for searching up syntax or anything else.

I always asked a simple question like here is an array full of objects. Please filter out any objects where the "age" property is less than 20, or the "eye color" property is red or blue. It was meant more as a sanity check that this person can do basic programming than anything else.

Tons and tons of people failed to make basically any progress, much less solve the problem, despite saying that they worked programming day to day in that language. For a mid level role I would filter out a good 8 or 9 out of ten applicants with it.

I would consider it a non-leetcode type of question since it did not require any algorithm tricks or any optimization in time/space.

Nowadays that kind of question is trivial for AI so it doesn't seem like the best test. I'm not hiring right now,.but when I do I'm not sure what I will ask.

> mid/difficult

You're assuming the question has to even be that difficult. I've proctored sessions for senior-level webdev roles where the questions were akin to "baby's first React component" -- write a component that updates a counter when you click a button. So many candidates (who purported to be working with React for years) would fail, abysmally. Not like they were just making small mistakes; I didn't even care about best practices -- they just needed to make it work. So many failed. Lot of frauds out there.

Simple: don’t do that.

It’s been well over a decade that I’ve had to do the coding interview monkey dance and I actually turned down an offer where I did pass a coding interview because I found it insulting and took a job for slightly less money where the new to the company director was interested in a more strategic hire (2016). That was the same thing that happened before in 2014 and after in 2018 - a new manager/director/CTO looking for a strategic hire.

In fact even my job at BigTech -AWS ProServe (full time blue badge RSU earning employee) as a customer facing consultant specializing in app dev was all behavioral as well as my next full time job as a staff consultant in 2023.

I’m 51 years old and was 40 in 2014. If I’m still trying to compete based on my ability to reverse a b tree on the whiteboard even at 40, I have made some horrible life decisions.

(Well actually I did make a horrible life decision staying at my second job too long until 2008 and becoming an expert beginner. But that’s another story)

I've put a lot of thought into hiring in this era, and what I've personally found works the best is:

Let them use their preferred setup and AI to the full extent they want, and evaluate their output and their methodology. Ask questions of "why did you choose X over Y", especially if you're skeptical, and see their reasoning. Ask what they'd do next with more time.

It's clear when a candidate can build an entire working product, end-to-end, in <1 day vs. someone who struggles to create a bug-free MVP and would take a week for the product.

In addition to the technical interview, hiring them on a trial basis is the absolute best if possible.

Taste and technical understanding of goals and implementation to reach those goals is the biggest differentiator now. AI can handle all the code and syntax, but it's not great at architecture yet - it defaults to what's mid if not otherwise instructed.

"And then what happens in a year when the models can handle that as well?"

Either the machines exterminate us or we become glorified pets.

Hope the AIs prefer us to cats (even though that's a long shot).

It's like having an early/broken chess engine.

An amateur with a chess engine that blunders 10% of the time will hardly play much better than if they didn't use it. They might even play worse. Over the course of a game, those small probabilities stack up to make a blunder a certainty, and the amateur will not be able to distinguish it from a good move.

However, an experienced player with the same broken engine will easily beat even a grandmaster since they will be able to recognise the blunder and ignore it.

I often find myself asking LLMs "but if you do X won't it be broken because Y?". If you can't see the blunders and use LLMs as slot machines then you're going to spend more money in order to iterate slower.

> Junior devs can indeed prompt better than some of the old timers

I guess? I don't really see why that would be the case. Being a senior is also about understanding the requirements better and knowing how/what to test. I mean we're talking about prompting text into a textarea, something I think even an "old timer" can do pretty well.