[est31]

I think the older AI users are even held back because they might be doing things that are not neccessary any more, like explaining basic things, like please don't bring in random dependencies but prefer the ones that are there already, or the classic think really strongly and make a plan, or try to use a prestigious register of the language in attempts to make it think harder.

Nowadays I just paste a test, build, or linter error message into the chat and the clanker knows immediately what to do, where it originated, and looks into causes. Often times I come back to the chat and see a working explanation together with a fix.

Before I had to actually explain why I want it to change some implementation in some direction, otherwise it would refuse no I won't do that because abc. Nowadays I can just pass the raw instruction "please move this into its own function", etc, and it follows.

So yeah, a lot of these skills become outdated very quickly, the technology is changing so fast, and one needs to constantly revisit if what one had to do a couple of months earlier is still required, whether there's still the limits of the technology precisely there or further out.

[port11]

I’ve no idea what you’re using, but “I simply paste” isn’t giving me good results at all.

An hour ago Gemini decided it needed to scan my entire home folder to find the test file I asked it to look into. Sonnet will definitely try to install new dependencies, even though I’m doing SDD and have a clear AGENTS.md.

I’m always baffled at people’s magic results with LLMs. I’m impressed by the new tools, but lots of comments here would suggest my Gemini/Sonnet/Opus are much worse than yours.

[fl7305]

> I think the older AI users are even held back because they might be doing things that are not neccessary any more

As the same age as Linus Torvalds, I'd say that it can be the opposite.

We are so used to "leaky abstractions", that we have just accepted this as another imperfect new tech stack.

Unlike less experienced developers, we know that you have to learn a bit about the underlying layers to use the high level abstraction layer effectively.

What is going on under the hood? What was the sequence of events which caused my inputs to give these outputs / error messages?

Once you learn enough of how the underlying layers work, you'll get far fewer errors because you'll subconciously avoid them. Meanwhile, people with a "I only work at the high-level"-mindset keeps trying to feed the high-level layer different inputs more or less at random.

For LLMs, it's certainly a challenge.

The basic low level LLM architecture is very simple. You can write a naive LLM core inference engine in a few hundred lines of code.

But that is like writing a logic gate simulator and feeding it a huge CPU gate list + many GBs of kernel+rootfs disk images. It doesn't tell you how the thing actually behaves.

So you move up the layers. Often you can't get hard data on how they really work. Instead you rely on empirical and anecdotal data.

But you still form a mental image of what the rough layers are, and what you can expect in their behavior given different inputs.

For LLMs, a critical piece is the context window. It has to be understood and managed to get good results. Make sure it's fed with the right amount of the right data, and you get much better results.

> Nowadays I just paste a test, build, or linter error message into the chat and the clanker knows immediately what to do

That's exactly the right thing to do given the right circumstances.

But if you're doing a big refactoring across a huge code base, you won't get the same good results. You'll need to understand the context window and how your tools/framework feeds it with data for your subagents.

[OJFord]

I think GP meant 'longer time users of AI', not 'older aged users of AI'.

Their point being that it's not really an advantage to have learnt the tricks and ways to deal with it a year, two years ago when it's so much better now, and that's not necessary or there's different tricks.

[est31]

Yeah I meant it in the context of the comment I was replying to, to be precise in the context of the comment that one was replying to, i.e. "10 years of certified Claude Code experience required".

The technology is moving so fast that the tricks you learned a year ago might not be relevant any more.

[fl7305]

Thanks, I agree 100% with that.

[rednafi]

I still see people doing "you are a world class distributed systems engineer" think. Never fails me to chuckle.