Respectfully but that's a bit like saying you don't need to learn how to ride a bicycle because you can use a pair of safety wheels. It's an excuse to not learn something, to keep yourself less knowledgeable and skillful than you could really be. Why stunt yourself? Knowledge is power.
See it this way: anyone can use ChatGPT but not everyone knows Python well, so you 'll never be able to use ChatGPT to compete with someone who knows Python well. You + limited knowledge of Python + ChatGPT << someone + good knowledge of Python + ChatGPT.
Experiences like the one you relay in your comment makes me think using LLMs for coding in particular is betting on short-term gains for a disproportionately large long-term cost. You can move faster now, but there's a limit to what you can do that way and you'll never be able to escape it.
Slow down, cowboy. Getting a LLM to generate code for you that is immediately useful and doesn't require you to think too hard about it can stunt learning, sure, but even just reading it and slowly getting familiar with how the code works and how it relates to your original task is helpful.
I learned programming by looking at examples of code that did similar things to what I wanted, re-typing it, and modifying it a bit to suit my needs. From that point of view it's not that different.
I've seen a couple of cases first hand of people with no prior experience with programming learn a bit by asking ChatGPT to automate some web scraping tasks or spreadsheet manipulation.
> You + limited knowledge of Python + ChatGPT << someone + good knowledge of Python + ChatGPT.
Substract ChatGPT from both sides and you have a rather obvious statement.
> Respectfully but that's a bit like saying you don't need to learn how to ride a bicycle because you can use a pair of safety wheels.
How did you learn to ride a bicycle?
You are making a lot of assumptions about someone's ability to learn with AND without assistance, while also making rather sci-fi leaps about our brain somehow being able to differentiate between learning that has somehow been tainted by the tendrils of ML overlords.
The models and the user interface around them absolutely will continue to improve far faster than any one person's ability to obtain subject mastery in a field.
If you want to have a debate, I'm all for it, but if you're going to go around imagining things that I may have said in another timeline then I don't see what's the point of that.
You could be right, but I strongly suspect that you are actually wrong.
The OP said:
>>> For example my Python knowledge is limited and I don't really use it often, so I don't want to spend time to better learn it.
And I replied:
>> Respectfully but that's a bit like saying you don't need to learn how to ride a bicycle because you can use a pair of safety wheels. It's an excuse to not learn something, to keep yourself less knowledgeable and skillful than you could really be. Why stunt yourself? Knowledge is power.
"It's an excuse to not learn something (...) Why stunt yourself?".
Do you care how a car engine works to drive a car?
The AI is pretty good at answering "I know this is possible, remind me what it's called or what the syntax is."
For a lot of these the reason I want to look it up is I don't use it enough to build muscle memory. If I did, I'd already have the muscle memory. And in practice, it's just a faster version of looking for examples on stackoverflow.
So learning syntax nuances of yet another programming language which I'll forget soon is wasted time. There's some "fundamental" knowledge, like understanding what functional value is, but the specific syntax that Python invented for lambda - that's not something valuable when I use Python few times a year.
Rereading your comment I think I got the wrong impression from it. You said:
>> I don't really use it often, so I don't want to spend time to better learn it
And I focused more on "I don't want to spend time to better learn it" than on "I don't really use it often". I also don't use Python often and I have to look up its syntax, same with e.g. R. I guess in that case it makes sense to not spend too much time learning the ins and outs of a language. On the other hand, Python is a staple, like Java was back in the day, and Perl and so on. It's useful, like speaking English. I don't think I would ever feel comfortable saying "I don't want to learn" it; or anything else.
2. To break procrastination loops. For example I often can't name a particular variable, because I can see few alternatives and I don't like all of them. Nowadays I just ask ChatGPT and often proceed with his opinion.
3. Navigating less known technologies. For example my Python knowledge is limited and I don't really use it often, so I don't want to spend time to better learn it. ChatGPT is just perfect for that kind of tasks, because I know what I want to get, I just miss some syntax nuances and I can quickly check the result. Another example is jq, it's very useful tool, but its syntax is arcane and I can't remember it even after years of occasional tinkering with it. ChatGPT builds jq programs like a super-human, I just show example JSON and what I want to get.
4. Not ChatGPT, but I think Copilot is based on GPT4, and I use Copilot very often as a smart autocomplete. I didn't really adopt it as a code writing tool, I'm very strict at code I produce, but it still helps a lot with repetitive fragments. Things I had to spend 10-20 minutes before, construction regexps or using editor macroses, I can now do with Copilot in 10-20 seconds. For languages like Golang where I must write `if err != nil` after every line, it also helps not to become crazy.
May be I didn't formulate my thoughts properly. It's not anything irreplaceable and I didn't become 10x programmer. But those tools are very nice and absolutely worth every penny I paid for it. It's like Intellij Idea. I can write Java in notepad.exe, but I'm happy to pay $100/year to Jetbrains and write Java in Idea.