I strongly agree on the refactor, but for debugging I have another perspective: I think debugging is changing for the better, so it looks different.

Sure, you don't know the code by heart, but people debugging code translated to assembly already do that.

The big difference is being able to unleash scripts that invalidate enormous amount of hypothesis very fast and that can analyze the data.

Used to do that by hand it took hours, so it would be a last resort approach. Now that's very cheap, so validating many hypothesis is way cheaper!

I feel like my "debugging ability" in terms of value delivered has gone way up. For skill, it's changing. I cannot tell, but the value i am delivering for debugging sessions has gone way up

As someone who's switched from mobile to web dev professionally for the last 6 months now. If you care about code quality, you'll develop that neural connection after some time.

But if you don't and there's no PR process (side projects), the motivation to form that connection is quite low.

That is not the entire selling point - so you are very wrong.

You very much decide how you employ LLMs.

Nobody are keeping a gun to your head to use them. In a certain way.

Sonif you use them in a way that increase you inherent risk, then you are incredibly wrong.

I see it completely the opposite way, you use an LLM and correct all its mistakes and it allows you to deliver a rough solution very quickly and then refine it in combination with the AI but it still gets completely lost and stuck on basic things. It’s a very useful companion that you can’t trust, but it’s made me 4-5x more productive and certainly less frustrated by the legacy codebase I work on.

Yeah I whole hardheartedly disagree with this. Because I understand the basics of coding I can understand where the model gets stuck and prompt it in other directions.

If you don't know whats going on through the whole process, good luck with the end product.

They purportedly solve the problem of needing skill to get things done. IME, this is usually repeated by VC backed LLM companies or people who haven’t knowingly had to deal with other people’s bad results.

This all bumps up against the fact that most people default to “you use the tool wrong” and/or “you should only use it to do things where you already have firm grasp or at least foundational knowledge.”

It also bumps against the fact that the average person is using LLM’s as a replacement for standard google search.

This is such a weird statement in so many levels.

The latent assumption here is that learning is zero sum.

That you can take a 30 year old from 1856 bring them into present day and they will learn whatever subject as fast as a present day 20 year old.

That teachers doesn't matter.

That engagement doesn't matter.

Learning is not zero sum. Some cultural background makes learning easier, some mentoring makes is easier, and some techniques increases engagement in ways that increase learning speed.

So, you havent really learned anything from any teacher if you could not do it again without them?

I could definitely maintain the infrastructure without an llm. Albeit much slower.

And yes. If LLMs disappear, then we need to hire a lot of people to maintain the infrastructure.

Which naturally is a part of the risk modeling.

I think this is a bit dismissive.

It’s quite possible to be deep into solving a problem with an LLM guiding you where you’re reading and learning from what it says. This is not really that different from googling random blogs and learning from Stack Overflow.

Assuming everyone just sits there dribbling whilst Claude is in YOLO mode isn’t always correct.

>> I am learning a new skill with instructor at an incredible rate

> Could you do it again on your own?

Can you you see how nonsensical your stance is? You're straight up accusing GP of lying they are learning something at the increased rate OR suggesting if they couldn't learn that, presumably at the same rate, on they own, they're not learning anything.

That's not very wise to project your own experiences on others.

The challenge is not if you could do all of it without AI but any of it that you couldn't before.

Not everyone learns at the same pace and not everyone has the same fault tolerance threshold. In my experiencd some people are what I call "Japanese learners" perfecting by watching. They will learn with AI but would never do it themselves out of fear of getting something wrong while they understand most of it, others that I call "western learners" will start right away and "get their hands dirty" without much knowledge and also get it wrong right away. Both are valid learning strategies fitting different personalities.

I believe some professor warned us about being over reliant on Google/reddit etc: “how would you be productive if internet went down” dilemma.

Well, if internet is down, so is our revenue buddy. Engineering throughput would be the last of our concerns.

If you've seen further it's only because you've stood on the shoulders of giants.

Having other people do work for you is how people get to focus on things they actually care about.

Do you use a compiler you didn't write yourself? If so can you really say you've ever learned anything about computers?

It is easy to not believe if you only apply an incredibly narrow world view.

Open your eyes, and you might become a believer.

It's partly that, but also reading and surface level understanding something vs generating yourself are different skills with different depths. If you're learning a language, you can get good at listening without getting good at speaking for example.