|
|
|
|
|
by bob1029
198 days ago
|
|
I have my best successes by keeping things constrained to method-level generation. Most of the things I dump into ChatGPT look like this: public static double ScoreItem(Span<byte> candidate, Span<byte> target)
{
//TODO: Return the normalized Levenshtein distance between the 2 byte sequences.
//... any additional edge cases here ...
}
I think generating more than one method at a time is playing with fire. Individual methods can be generated by the LLM and tested in isolation. You can incrementally build up and trust your understanding of the problem space by going a little bit slower. If the LLM is operating over a whole set of methods at once, it is like starting over each time you have to iterate. |
|
Using an agentic system that can at least read the other bits of code is more efficient than copypasting snippets to a web page.