Amazon cloud boss echoes NVIDIA CEO on coding being dead in the water: "If you go forward 24 months from now, it's possible that most developers are not coding"

It's this. When boards and non-tech savvy managers start making decisions based on a slick slide deck and a few visuals, enough will bite that people will be laid off. It's already happening.

There may be a reckoning after, but wall street likes it when you cut too deep and then bounce back to the "right" (lower) headcount. Even if you've broken the company and they just don't see the glide path.

It's gonna happen. I hope it's rare. I'd argue it's already happening, but I doubt enough people see it underpinning recent lay offs (yet).

LLMs have already reached the end of the line 🤔

I don’t believe that. At least from an implementation perspective we’re extremely early on, and I don’t see why the tech itself can’t be improved either.

Maybe it’s current iteration has hit a wall, but I don’t think anyone can really say what the future holds for it.

"at some point" being like 400 years in the future? Sure.

Ok that's probably a little bit of an exaggeration. 250 years.

It'll have to improve a magnitude for that effect. Right now it's basically an improved stack overflow.

There is no reason to believe that LLM will disrupt anyone any time soon. As it stands now the level of workmanship is absolutely terrible and there are more things to be done than anyone has enough labor to do. Making it so skilled professionals can do more literally just makes it so more companies can produce quality of work that is not complete garbage.

Juniors produce progressively more directly usable work with reason and autonomy and are the only way you develop seniors. As it stands LLM do nothing with autonomy and do much of the work they do wrong. Even with improvements they will in near term actually be a coworker. They remain something you a skilled person actually use like a wrench. In the hands of someone who knows nothing they are worth nothing. Thinking this will replace a segment of workers of any stripe is just wrong.

I wrote a comment about this several months ago on my old kbin.social account. That site is gone and I can't seem to get a link to it, so I'm just going to repost it here since I feel it's relevant. My kbin client doesn't let me copy text posts directly, so I've had to use the Select feature of the android app switcher. Unfortunately, the comment didn't emerge unscathed, and I lack the mental energy to fix it due to covid brain fog (EDIT: it appears that many uses of I were not preserved). The context of the old post was about layoffs, and it can be found here: https://kbin.earth/m/asklemmy@lemmy.ml/t/12147

I want to offer my perspective on the Al thing from the point of view of a senior individual contributor at a larger company. Management loves the idea, but there will be a lot of developers fixing auto-generated code full of bad practices and mysterious bugs at any company that tries to lean on it instead of good devs. A large language model has no concept of good or bad, and it has no logic. happily generate string- templated SQL queries that are ripe for SQL injection. I've had to fix this myself. Things get even worse when you have to deal with a shit language like Bash that is absolutely full of God awful footguns. Sometimes you have to use that wretched piece of trash language, and the scripts generated are horrific. Remember that time when Steam on Linux was effectively running rm -rf /* on people's systems? I've had to fix that same type of issue multiple times at my workplace.

I think LLMs will genuinely transform parts of the software industry, but I absolutely do not think they're going to stand in for competent developers in the near future. Maybe they can help junior developers who don't have a good grasp on syntax and patterns and such. I've personally felt no need to use them, since spend about 95% of my time on architecture, testing, and documentation.

Now, do the higher-ups think the way that do? Absolutely not. I've had senior management ask me about how I'm using Al tooling, and they always seem so disappointed when I explain why I personally don't feel the need for it and what feel its weaknesses are. Bossman sees it as a way to magically multiply IC efficiency for nothing, so absolutely agree that it's likely playing a part in at least some of these layoffs.

Basically, I think LLMs can be helpful for some folks, but my experience is that the use of LLMs by junior developers absolutely increases the workload of senior developers. Senior developers using LLMs can experience a productivity bump, but only if they're very critical of the output generated by the model. I am personally much faster just relying on traditional IDE auto complete, since I don't have to change from "I'm writing code" mode to "I'm reviewing code mode."

The problem with this take is the assertion that LLMs are going to take the place of secretaries in your analogy. The reality is that replacing junior devs with LLMs is like replacing secretaries with a network of typewriter monkeys who throw sheets of paper at a drunk MBA who decides what gets faxed.

I thought by this point everyone would know how computers work.

That, uh, did not happen.

No

Good take

Irrelevant, anyone who tries to replace their devs with LLMs will crash and burn. The lessons will be learned. But yes, many executives will make stupid ass decisions around this tech.

if lineGoUp {

    CollectUnearnedBonus()

} else {

   FireSomePeople()
   CollectUnearnedBonus()

}

ChatJippity

I'll start using that!

SHUT UP AND GO BACK TO OUR SHITTY YAML BASED INFRASTRUCTURE!

🤣😂😪😥😢😭

Will the matrix it puts us in be in 1999? Because I'd take that deal.

I'm at the point where what I work on requires such a depth of knowledge that I just manage my own projects. Doesn't help that my work's PM team consistently brings in new hires only to toss them on the difficult projects no one else is willing to take. They see a project is doomed to fail so they put their least skilled and newest person on it so the seniors don't suffer any failures.

Simplifying things to a level that is understandable for the PMs just leads to overlooked footguns. Trying to explain a small subset of the footguns just leads to them wildly misinterpreting what is going on, causing more work for me to sort out what terrible misconceptions they've blasted out to everyone else.

If you can't actually be a reliable force multiplier, or even someone I can rely on to get accurate information from other teams, just get out of my way please.

That's when you write an AI auto reply cron. Let the snake eat its tail. Hehe

Realises devs have always joked about their jobs just being about copy-pasting solutions from StackOverflow 80% of the time

Oh God...

job wasn’t that important

I keep telling you that changing out the battery in the smoke alarm isn't worth the effort and you keep telling me that the house is currently on fire, we need to get out of here immediately, and I just roll my eyes because you're only proving my point.

Define "works"?

If you're a CEO, cutting all your talent, enshittifying your product, and pocketing the difference in new, lower costs vs standard profits might be considered as "working".

Like in Twitter?

Oh perhaps the CEOs are the ones that need to be replaced?

Define "works."

Because the goals of a money-hungry CEO don't always align with those of the workers in the company itself (or often, even the consumer). I imagine this guy will think it worked just fine as he's enjoying his golden parachute.

😜 👢

I've always thought that design and maintenance are the difficult and gruelling parts, and writing code is when you get to relax for a bit. Most of the time you're in maintenance mode, and it's harder than writing new code.

This. I’m learning a new skill right now & hardly any of it is actual writing— it’s how to arrange the pieces someone else wrote (& which sometimes AI can decently reproduce.)

When you use a computer you don’t start by mining iron, because the thing is already built

AI is quite good at writing small sections of code. Usually because it's more or less just copying something off the internet that it's found, maybe changing a few bits around, but essentially just regurgitating something that's in its data set. I could of course just have done that but it saves time since the AI can find the relevant piece of code to copy and modify more or less instantly.

But it falls apart if you ask it to build entire applications. You can barely even get it to write pong without a lot of tinkering around after the fact which rather defeats the point really.

It also doesn't deal well if the thing you're trying to program for is not very well documented, which would include things like drivers, which presumably is their bread and butter.

Looking at your examples, and I have to object at putting scratch in there.

My kids use it in clubs, and it's great for getting algorithmic basics down before the keyboard proficiency is there for real coding.

while(True):

staffNumbers-=1

staffWorkload*=1.1

staffWages*=0.95

executiveWages*=1.2

It also doesn’t know what’s going on a couple line before it, so say I am in a language that has options for functional styling using maps and I want to keep that flow going, it will start throwing for loops at you, so you end up having to rewrite it all anyway. I have find I end up spending more time writing the prompts then validating it did what I want correctly (normally not) than just looking at the docs and doing it myself, the bonus being I don’t have to reprompt it again later because now I know how to do it

We are 18 months into AI replacing me in 6 months. I mean… the CEO of OpenAI as well as many researchers have already said LLMs have mostly reached their limit. They are “generalizers” and if you ask them to do anything new they hallucinate quite frequently. Trying to get AI to replace developers when it hasn’t even replaced other menial office jobs is like saying “we taught AI to drive, it will replace all F1 drivers in 6 months”.

It's based on the last few years of messaging. They've consistently said AI will do X, Y, and Z, and it ends up doing each of those so poorly that you need pretty much the same staff to babysit the AI. I think it's actually a net-negative in terms of productivity for technical work because you end up having to go over the output extremely carefully to make sure its correct, whereas you'd have some level of trust with a human employee.

AI certainly has a place in a technical workflow, but it's nowhere close to replacing human workers, at least not right now. It'll keep eating at the fringes for the next 5 years minimum, if not indefinitely, and I think the net result will be making human workers more productive, not replacing human workers. And the more productive we are per person, the more valuable that person is, and the more work gets generated.

An inherent flaw in transformer architecture (what all LLMs use under the hood) is the quadratic memory cost to context. The model needs 4 times as much memory to remember its last 1000 output tokens as it needed to remember the last 500. When coding anything complex, the amount of code one has to consider quickly grows beyond these limits. At least, if you want it to work.

This is a fundamental flaw with transformer - based LLMs, an inherent limit on the complexity of task they can 'understand'. It isn't feasible to just keep throwing memory at the problem, a fundamental change in the underlying model structure is required. This is a subject of intense research, but nothing has emerged yet.

Transformers themselves were old hat and well studied long before these models broke into the mainstream with DallE and ChatGPT.

The real work of software engineering isn't the coding. That is like saying that being a doctor is all about reading health charts. Planning, designing, testing and maintaining software is the hard part, and it is often much more political than it is a technical challenge. I'm not worried about getting replaced by AI. In fact, LLMs ability to generate high volumes of code only makes the skills to understand it to be more in demand.

It's tons easier to repkace CEOs, HR, managers and so on than coders. Coders needs to be creative, an HR or manager not so much. Are they leaving three months from now you think?

I'll start worrying when they are all gone.

I don't understand how you could understand how LLMs work, and then write this.

Machines can learn that...

Ah, nevermind.

If you'll excuse me saying, I feel that you are the one who is looking at something and extrapolating.

We'll have full self driving next year.

And just like that, they'll forget about these previous statements as well.

I fear Elon Musk's broken promises method is being admired and copied.

it will use a lot of energy for every query and a lot of resources for cooling

Well, so do coders. Coffee can be quite taxing on the environment, as can air conditioning!

Also, it seems to only do digital art.

The problem is that not everyone looks for that human-to-human emotional connection in art. For some, it's just a part of a much bigger whole.

For example, if you're an indie game dev with a small budget and no artistic skills, you may not be that scrupulous about getting an AI to generate some sprites or 3D models for you, if the alternative is to commission the art assets with money you don't have.

Similar idea applies to companies building a website. Why pay for a licence to download some stock images or design assets if you can just get a GenAI to pump out hundreds for you that are very convincing (and probably even better) for a couple bucks?

Don't need to be abstract art, it manages to make many kinds of art.

The difference between art and coding is that if you pick a slightly different color or make a line with slightly the wrong angle, it doesn't change much. In code, however, slight mistakes usually result in bugs.

Will that not be more experiensive than having developers?

If only we had an overarching structure that everyone in society has agreed exists for the purposes of enforcing laws and regulating things. Something that governs people living in a region... Maybe then they could be compelled to show exactly what they're using, and what those models are being trained with.

Oh well.

This explains so much about 1 in 4 IT people I meet.

Possibly. But... Here's the thing. I've dealt with "business rules" engines before at a job. I used a few different ones. The idea is always to make coding simpler so non technical people can do it. Unless you couldn't tell from context, I'm a software engineer lol. I was the one writing and troubleshooting those tools. And it was harder than if it was just in a "normal" language like Java or whatever.

I have a soft spot for this area and there's a non zero chance this comment makes me obsess over them again for a bit lol. But the point I'm making is that "normal" coding was always better and more useful.

It's not a perfect comparison because LLMs output "real" code and not code that is "Scratch-like", but I just don't see it happening.

I could see using LLMs exclusively over search engines (as a first place to look that is) in 2 years. But we'll see.

Definitely be coding less I think. Coding or programming is basically the "grunt work". The real skill is understanding requirements and translating that into some product.

I find there comes a point where, even with a lot of context, the AI just hasn't been trained to solve the problem. At that point it will cycle you round and round the same few wrong answers until you give up and work it out yourself.

To actually answer your question - yes, but the only times I actually find it useful is for tests, for everything else it's usually iffy and takes longer.

Intelligently loading the window could be the next useful trick

I think that giving the LLM an API to access additional context and then making it more of an agent style process will give the most improvement.

Let it request the interface for the class your using, let it request the code for that extension method you call. I think that would solve a lot, but I still see a LOT of instances where it calls wrong class/method names randomly.

This would also require a lot more in depth (and language specific!) IDE integration though, so I forsee a lot of price hikes for IDEs in the near future!

Nah, if it doesn't pan out then all these folks will pretend they never said this, but in 24 months programming will be obsoleted by

The most successful ML in-house projects I've seen took at least 3 times as long than initially projected to become usable, and the results were underwhelming.

You have to keep in mind that most of the corporate ML undertakings are fundamentally flawed because they don't use ML specialists. They use eager beavers who are enthusiastic about ML and entirely self-taught and will move on in 1 year and want to have "AI" on their resume when they leave.

Meanwhile, any software architect worth their salt will diplomatically avoid to give you any clear estimate for anything having to do with ML – because it's basically a black box full of hopes and dreams. They'll happily give you estimates and build infrastructure around the box but refuse to touch the actual thing with a ten foot pole.

GitHub Copilot does chat like ChatGPT, and writes code based on a prompt. I have decades of experience programming and I use it a lot. It gives me starting points, boilerplate and examples. It won't build a whole application with no coding work from the human.

You can definitely 'chat' with copilot, like other llms as well as the inline editor auto complete.

There will still be people who are able to rapidly learn with AI on their side and people who fail to do it. The fast ones are able to focus much more on the underlying problems and less on language specifics. The definition of low level and high level programers will change in the context of AI. Nobody today is implementing a linked list outside of university and in the future nobody will be needed to write the repeated code which still is needed in a lot of frameworks.

But of course there might the point of a critical collapse if AI only learns from its own code and inefficient code gets repeated constantly.