Those are two different narratives. One implies that everyone will be able to code and build: "English as a programming language", etc. The other is one of those headless-chicken, apocalyptic scenarios where AI has already made (or will very shortly make) human programmers obsolete.

"AI taking jobs" means everyone's job. I won't even comment on the absurdity of that idea; to me, it only comes from people who've never worked professionally.

At the end of the day, companies will take any vaguely reasonable excuse to cull juniors and save money. It's just business. LLMs are simply the latest excuse, though yes, they do improve productivity, to varying degrees depending on what exactly you work on.

It's wrong maybe 40-50% of the time, so I can't even imagine the disasters I'm averting by recognising when it's giving me completely bonkers suggestions.

To me, that has never been more true.

Most junior dev ask GeminiPiTi to write the JavaScript code for them, whereas I ask it for explanation on the underlying model of async/await and the execution model of a JavaScript engine.

There is a similar issue when you learn piano. Your immediate wish is to play Chopin, whereas the true path is to identify,name and study all the tricks there are in his pieces of art.

I have never heard that before

i just soent some time cleaning up au code where it lied about the architecture so it wrote the wrong thing. the architecture is wonky, sure, but finding the wonks earlier would have been better

1. Unconsciously incompetent

2. Consciously incompetent

3. Consciously competent

4. Unconsciously competent

The challenge with AI, it will give you “good enough” output, without feedback loops you never move to 2,3,4 and assume you are doing ok. Hence it stunts learning. So juniors or inexperienced stay inexperienced, without knowing what they don’t know.

You have to Use it as an expert thinking partner. Tell it to ask you questions & not give you the answer.

Similarly, it takes experience to spot when the LLM is going in the wrong direction it making mistakes.

I think for supercharging a junior, it should be used more like a pair programmer, not for code generation. It can help you quickly gain knowledge and troubleshoot. But relying on a juniors prompts and guidance to get good code gen is going to be suboptimal.

-techs they understand but still not master. AI aids with implementation details only experts knowb about

- No time for long coding tasks. It aids with fast implementations and automatic tests.

- No time for learning techs that adress well understood problems. Ai helps with quick intros, fast demos and solver of learners' misunderstandings

In essence, in seniors it impacts productivity

In the case of juniors AI fills the gaps too. But these are different from seniors' and AI does not excell in them because gaps are wider and broader

- Understand the problems of the business domain. AI helps but not that much.

- Understand how the organization works. AI is not very helpful here.

- Learn the techs to be used. AI helps but it doesn't know how to guide a junior in a specific organisational context and specific business domain.

In essence it helps, but not that much because the gaps are wider and more difficult to fill

This is all a pretty well-trodden debate at this point though. AI works as a Copilot which you monitor and verify and task with specific things, it does not work as a pilot. It's not about junior or senior, it's about whether you want to use this thing to do your homework/write your essay/write your code for you or whether you use it as an assistant/tutor, and whether you are able to verify its output or not.

Edit interesting thread: https://news.ycombinator.com/item?id=27678424

Edit: an example of the kind of comment I was talking about: https://news.ycombinator.com/item?id=27677690

But that was just said by crappy influencers whose opinion doesn’t matter as they are impressed by examples result of overfitting

It can be really, really hard to tell when what it's producing is a bag of ** and it's leading you down the garden path. I've been a dev for 20 years (which isn't to imply I'm any good at it yet) and it's not uncommon I'll find myself leaning on the AI a bit too hard and then you realise you've lost a day to a pattern that wasn't right, or an API it hallucinated, in the first place.

It basically feels like I'm being gaslit constantly, even though I've changed my tools to some that feel like they work better with AIs. I expect it's difficult for junior devs to cope with that and keep up with senior devs, who normally would have offloaded tasks to them instead of AI.

Like 19% weaker, according to the only study to date that measured their productivity.

That’s the whole issue in a nutshell.

Can the output of a generative system be verified as accurate by a human (or ultimately verified by a human)

Experts who can look at an output and verify if it is valid are the people who can use this.

For anyone else it’s simply an act of faith, not skill.