[Bukhmanizer]

I think the issue is that a lot of orgs are systematically using the tool poorly.

I’m responsible for a couple legacy projects with medium sized codebases, and my experience with any kind of maintenance activities has been terrible. New code is great, but asking for fixes, refactoring, or understanding the code base has had an essentially 2% success rate for me.

Then you have to wonder, how the hell orgs expect to maintain/scale and more code from fewer devs, who don’t even understand how the original code worked?

LLMs are just a tool but overreliance on them is just as much of a code smell as - say - deciding your entire backend is going to be in Matlab; or all your variables are going to be global variables - you can do it, but I guarantee that it’s going to cause issues 2-3 years down the line.

[simonw]

"understanding the code base has had an essentially 2% success rate for me"

How have you been using LLMs to help understand existing code?

I have been finding that to work extremely well, but mainly with the longer context models like Google Gemini.