When code was written by an LLM, do you note that in the code? How specific is the citation -- do you note the date the code was generated". LLM capabilities can vary over time. Do you list the prompt? (I don't but typically ask the LLM to provide a docstring.)
Because there will be development platforms and tools built around AI-generated code. The LLMs will have integrated code execution and libraries/APIs that they are familiar with. If a programmer or user stays within this platform, which will be fairly general purpose, the AI can handle 98% of requests with no help writing code.
These types of platforms will completely normalize AI-written code. People won't think twice about using it or feel they need to make a note of it.
What you might see say five years out is kind of the opposite. For some code bases, if a human writes the code and it hasn't been checked by an AI, then they have to make a note in a comment with their name and why they are not using AI verification. But they will probably choose to have an AI verify the code just to avoid extra procedure.
I don’t document things as “I learned this from stackoverflow” either, LLMs are very similar.
For LLM-generated code, I don't see much value in documenting where it came from, especially since it will be very exhaustively tested (and likely rewritten entirely) before it gets checked in, to an even greater extent than excerpts snagged from Stack Overflow. Also, a given prompt will rarely return exactly the same code twice, certainly not years later when I need to look back at it. It will make more sense to create a new query if/when that happens.
Put another way, till IP-implications have been figured out, I assume all LLM-generated code is radioactive for FLOSS projects.
[edit to clarify]: so documenting that a commit you're pushing includes code generated with an LLM will make maintainers' lives dramatically simpler. Please, and thank you!
All the best,
-HG
When I read your code I want to do know what the function does and why it does it. LLM generation details would just distract from that.
Before LLMs, you would cobble a bunch of disjoint information via a search engine like Google. Now, LLMs do this for you, and it certainly helps me to get a lot quicker with using libraries or APIs I am not familiar with (e.g., PyGame, Flask, Django). However, you might find that code from the LLM might need some fixing (subtle bugs or redundancies) or a better use of resources.
The other issue is the LLM's dataset bias towards the most used technologies or concepts. So you might have a hard time with an LLM trying to make Clojure/Racket code or telling the LLM to specifically do the point-in-triangle test with the wedge product only.
Hence, there is still some leeway or reason to use your thing between the ears.
You might as well ask: Are you referencing Stack Overflow or the Microsoft Developer Reference (e.g., in your developer notes/comments)?
My answer: usually, yes.