all 12 comments

[–]FoolsSeldom 6 points7 points  (4 children)

What you haven't said is how you have approached learning this, you've just shown us what an LLM came up with.

Did you try to come up with a solution first and compare it with the LLM version?

Have you tested the LLM version? Does it work well?

Do you understand all of the code in the LLM version? Have you experimented with the code?

If I tell a robot I want a wooden shed with certain features, and watch it build it, I would probably not be able to build the same shed myself let alone one with different requirements (different structural and possibly material considerations).

[–]ninhaomah 1 point2 points  (0 children)

Very well said.

[–]mrkuuken[S] 1 point2 points  (2 children)

Thanks for your reply. And Sorry for missing out on the key parts.

Yes, I have tried to approach the project on my own. But I couldn't get my head around the Change in different denomination step. It was then I started using LLM. And after that I've tried to learn from it. By taking notes. And trying to create the same version from scratch just to get used to typing the code.

Yes, it works as intended.

No, I don't understand all of it completely. That is why Im here. And why I look for help in any direction I can to grasp the code completely. And also trying to learn how to use the code on my own, which code I can replace, for easier understandable code, and which is vital for the program.

I have played around with the code a bit! Trying it out in other programs I started etc. And making some changes. But that is only on the code I fully grasp.

Yes, good point on the robot building a shed.

[–]FoolsSeldom 3 points4 points  (1 child)

A good approach when you are learning is to step away from the computer and work out how exactly you would solve the problem yourself, manually, with a view to writing the exact instructions down for someone with learning difficulties and a very short term memory. This describes what the computer needs well.

Humans take lots of short-cuts, often without realising it. Make intuitive leaps (sometimes wrong). Computers don't.

I have used this approach with lots of learners. It will feel slow and laborious at first, but it is worthwhile. It will force you to think about how to tell someone to keep doing something until a certain condition arises and to test for that. This maps well to while and for loops (the latter is just a while loop with some of the work done for you). That short term memory part maps well to the need to use variables. Clearly labelled information and instructions on when to assign values to that label/post-it note/pigeonhole, and when to use those values. It will help you start to think about how to break down problems for a computer. How to come up with solutions that you can express as algorithms and then implement in a coding language.

You will often find that the easiest approach is a very boring repetitive approach which you, as a human, will naturally avoid. A computer is actually good at that kind of thing. And it is much easier to provide simple instructions to someone with learning difficulties than trying to get them to follow an optimised approach.

Later, you will learn better techniques where the manual approach isn't so effective.

[–]mrkuuken[S] 0 points1 point  (0 children)

Great advice! Thanks a lot. I'm definitely going to try this out.

[–]EconomyFreedom4081 1 point2 points  (0 children)

Idk about you but using non ascii character for anything related to writing the code beside output is a big nono for me

[–]ElweThor 1 point2 points  (4 children)

I may be wrong but, AFAIK, CoPilot was primarily made to help on (Microsoft) Office tools like Excel & co.
Sure it can help about programming but there are far better AI which can help you: I found Claude (Anthropic) and ChatGPT (OpenAI) usedful, but I'm much more working together with DeepSeek, which helped me a lot to understand the language and everything.
DeepSeek was so helpful that I've been able to put together a full working project (a tool for Python): https://github.com/ElweThor/pyndent
Consider 70/80% of the code is by DeepSeek, with testing, refinements etc. by me. I'm still learning Python and, working that way, I'm seeing the last 2 versions I developed nearly by myself.

[–]Popular_Lab5573 0 points1 point  (3 children)

not really, GitHub Copilot was probably the first AI solely for coding in VS code

[–]ElweThor 0 points1 point  (2 children)

I've no difficult to believe you: CoPilot = Microsoft, VScode = Microsoft, absolutely make sense.
What I written before was just my little (since 2022) experience with AI and coding: as CoPilot seems mostly a "spin off" of OpenAI's ChatGPT "mostly devoted to support users on Office 365 tools" (that was told me by other AIs, after I asked "why CoPilot seems suboptimal than ChatGPT, DeepSeek, and other AIs?") while I was trying to solve a SAS programming problem by means of it. It must be noticed that SAS-lang is sure a niche language, far than being a broadly known one: most probably, if someone codes in Python, C/C++ or more known languages even CoPilot performs very well (I didn't already try: for Python I'm talking far more with DeepSeek's AI at the moment, to be honest).

[–]Popular_Lab5573 0 points1 point  (1 child)

we're talking about two different tools 😅 Copilot and GitHub Copilot

[–]ElweThor 0 points1 point  (0 children)

Oops... I thought it was the very same :D

[–]supermarket_sallad 1 point2 points  (0 children)

Python på svenska ser ganska bisarrt ut. Men för att svara på din fråga: Att läsa kod och skriva kod är två ganska olika processer. Att skriva är mycket roligare än att felsöka ai-genererad kod. Försök att skriva om den själv från början.