It doesn't have to be this way. LLMs can be quite helpful in analysis and small coding tasks. I understand everyone doesn't control their environment, but surely there are some sane places out there?

We don't have try to use them as 'agents' to write and understand all the code for us, frankly I wouldn't trust them to do so, they make too many mistakes and foolish decisions about architecture.

those places are vanishing fast and are extremely difficult to find these days (and that will only get worse)

They shouldn’t be this way, but more are turning into this.

Not all of them. Some simply can’t afford it. Some hold true to processes to ensure quality code and knowledge behind contributions.

But what appears to be happening is a race driven by FOMO. Teams are being told to use more and more AI to speed up their productivity. Surely their competition is using AI to build more features, fix long-standing bugs, and make products more efficient. By not spending money on tokens it allows the competition to expand their share of a market. They can’t accept that; shareholders, investors, and owners would replace them with someone who is willing to pull out all the stops.

While there probably is some FOMO, there is also some market competition at play. Encumbents are somewhat justifiably worried about getting disrupted by the growing AI-native nerd crowd.

Incumbents are in the worst possible place to start chasing 30k commits a day, it is not going to end well if that’s what they’re doing.

For startups it makes some kind of sense to take risks in this way, for incumbents it makes no sense.

Yes but who’s going to develop their skills enough to be making good architecture decisions if from the beginning of their career they have an Easy Button ?

Everyone who uses the extra time they unlocked to read, write, draw, discuss. The easy button is a boon to learning in the right environment.

What's even the incentive to learn much anymore?

Why work ten hours a day if the computer is doing the work?

Now you know how everyone felt when horses were replaced by cars. Technology has not shortened anyone's work day. Only radical labor has.

I wonder how many people spend less time working but don't spend less time at work, though. I'm sure it depends on the role/company, but there must be some cohort it's enabled to slack harder. Probably not engineers.

Graeber’s Bullshit Jobs covers this at length. There is a lot of employment that just needs a butt in the seat when or even just in case they are needed. It’s really a bit tragic how many man/woman-hours are wasted due to lack of creativity.

I call bullshit on that book. I've never worked anywhere that kept people on just for the sake of it. Sure there might have been people who probably should have been fired, but the job they performed wasn't fake.

... and I can name three F250 companies that you have never worked for. :)

I suspect people who truly have very little to do in a company go fairly unnoticed and have bosses that don't even know how much work they have on their plate.

The reality is an awful lot of people don't give a damn about their work and are just showing up for a paycheck. Those people will do less if they can get away with it.

So his thoroughly-researched book, that he spent years working on, and based on thousands of individuals submitting their experiences, is completely bogus because.... you haven't had the experience that millions of others absolutely have?

Sure pal. All jobs are totally important and not at all pointless, wasteful make-work.

Japan leads the world in this phenomenon, but no doubt much of IT/STEM is similar.

lot of performative but in practice half of the job is looking busy.

I find it incredibly interesting that the topic of a 4 day work week came up seemingly quite seriously during Covid, yet I haven't seen any mention of it since ChatGPT was announced.

No one with cash is going to fund your three day weekend. No billionaire is pushing AI so we can all get a Universal Basic Income.

EZ, we just make it the law.

No one with cash funded the 8 hour workday either. Working people bled for it, in the good old days when the oligarchs were aware what they risked by not making the occasional concession.

Goes to show how badly the social contract has broken down.

arguably they're pushing AGI so that they never have to give weekends to anyone

to paraphrase Cat Power: we could all be free... maybe not.

"Now you know how everyone felt when horses were replaced by cars"

A horse can't do 70mph for 600 miles between feeds. A horse can travel across obstacles that a car would find impossible.

It's horses for courses and a mangled analogy.

If you weren't trying to miss the analogy, you'd realize every significant technology of the last few centuries gave working people hope for less work for them. And it never happened. So expecting it with AI is fool's gold.

I meant in the sense that a person can’t do their best at knowledge work that many hours a day. It simply doesn’t make sense, for boss or worker.

Queue up longer term work at the end of the day and go home.

Sorry, what? That's not at all what happened.

Trying to code with a harry potter magic spell will have issues of alignment over time.

Software development has always evolved.

A preference for it to stay the same way isn't always in our hands.

You can have a say in how software development evolves by how you choose to learn the tools in a way that can influence other people.

But if you verify the code generated using the Harry Potter spell using spells from other wizards and possibly even a mortal human, the risk of code incantation can be mitigated.

Clearly I need to go back to the library, and by going back to the library, I mean to ask an agent to recursively ask at least 1000 other agents to do, and then responding by whispering in each others ears back to me to keep maximum accuracy.

If you have downtime ("waiting") and are complaining about not learning anything, I think that's on you.

In my experience, using LLMs to automate boring tasks gives time to learn about the interesting parts.

As to working 10 hours a day, was he working less hours before LLMs, or what's the relevance?

If he's waiting around, he should give it bigger chunks of work or work on multiple projects in parallel. Give it larger prompt and go for a walk.

perhaps during those walks he may try and catch up on the learning being missed out on by having outsourcing thinking to a data collection machine

I mean, you're free to not "outsource your thinking". If you actually believe that fiddling with the code by hand is essential, just spend 5 minutes giving a prompt and 55 minutes working by hand. Boom, you're as efficient as 2 programmers were before AI, and you only had to "miss out on" 1/12th of the learning.

That's great for everyone who isn't the author of the post:

> A year ago leadership told us everything goes through agents now. Hand written code needed a reason

I can't imagine needing to ask for permission or having to justify myself every time I personally wrote code. That definitely sounds like hell

Ironically the author of the original post is probably a LLM reddit spam bot https://news.ycombinator.com/item?id=50434474

But in any case, in that hypothetical scenario, just automate your day job and spend time coding a side project you're passionate about. You might have to spend 10 minutes out of every hour prompting, but hey, that's still 400 minutes a day for your side project of choice.

im sure your take applies to the majority of men who label themselves programmers

This reads as a flippant and reductive comment that projects a bit (outsourcing thinking?) but actually helps surface a good rule of thumb:

If you're telling an agent how to implement something, congrats! You're doing it right and should go on a walk while it's being implemented.

If the agent is telling you how to implement something, you should probably take a walk to digest it, and come back to tell that implementation-machine what to actually do so you can take another walk while it's being implemented.

i have no idea what you are accusing me of, did you want to make it a bit clearer what i am supposedly projecting? to me, the act of doing something is outsourced to entity X, when entity X is requested to do that thing (and proceeds to do it). are you saying the only actual thinking that occurs in human structures occurs at the planning level, therefore plan execution involves no further scope for learning?

That sounds great in theory, but a) it leads to burnout trying to do so much stuff in parallel and b) it's useless in the end unless you're willing to just yoloship things.

I stopped doing it as a result.

My real point is you shouldn't be sitting there waiting so you can tell the agent to "continue." Spec stuff out more and let it do it's thing. Whether you yolo-ship it or not is another matter.

My point is the context switching gets so exhausting that it's not worth it. The more you spread your attention thin by having lots on the go, the less you understand about any of it, the longer it takes to properly verify its correct before shipping. These things are at odds with one another.

It's amazing how much you missed the point.

>> If he's waiting around, he should give it bigger chunks of work or work on multiple projects in parallel. Give it larger prompt and go for a walk.

The level of stupidity of this statement is unbelievable.

> learning absolutely nothing

we shifted to 100% AI gen code a month ago and i realized my knowledge acquisition has nearly frozen. sure, i can evaluate and learn a little when i recognize an inconsistency at the edge or know there are alternatives when an LLM confidently makes a decision without presenting alternatives. but for each instance i catch i assume there is at least one other thing i missed

on the flipside, this sort of means the more ignorant someone is, the faster they will produce. not a problem yet but i think it will be

> the more ignorant someone is, the faster they will produce

It's a lot easier to produce "correct" code when they don't have a reference point for what "incorrect" code looks like. The optimistic side of me believes we'll discover new ways to scale websites because of this knowledge gap. A lot of cool tech was built in the 2000s precisely because we didn't know how stuff scaled yet.