Most comments here surprise me: I am using Githubs Copilot / ChatGPT 4.0 at work with a code base which is mostly implements a basic CRUD service... and outside of small/trivial example (where the generated code is mostly okay), prompting is more often than not a total waste of time. Now, I wonder if I am just totally unable to write/refine good prompts for the LLM (as it works for smaller samples, I hope I am not too far off) or what could explain the huge discrepancy of experience.
(Just for the record: I would totally not mind if the LLM writes the code for the stuff I have to do at work.)
To clarify my questions:
- Who here uses LLMs to generate code for bigger projects at work? (>= 20k lines of code)
- If you use LLMs for bigger projects: Do you need to change your prompting strategy to get good results?
- What programming languages are you using in your code bases?
- Are there other people here who experience that LLMs are no help for non trivial problems?
To clarify my questions: - Who here uses LLMs to generate code for bigger projects at work? (>= 20k lines of code) - If you use LLMs for bigger projects: Do you need to change your prompting strategy to get good results? - What programming languages are you using in your code bases? - Are there other people here who experience that LLMs are no help for non trivial problems?