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).

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

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

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 thought by this point everyone would know how computers work.

That, uh, did not happen.

No

Good take

ChatJippity

I'll start using that!

🤣😂😪😥😢😭

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...

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

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

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.

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!

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.

Also, it seems to only do digital art.

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

<insert fresh buzz here>