[inSenCite]

On one hand I agree with this conceptually, but on the other hand I've also been able to use AI to rapidly clean up and better structure a bunch of my existing code.

The blind copy-paste has generally been a bad idea though. Still need to read the code spit out, ask for explanations, do some iterating.

[whazor]

Imagine a single file full of complicated logic, where messing with one if statement might cause serious bugs. Here an AI will likely struggle, whereas a human could spend a couple of hours trying to work out the connections.

But if you have a code base with predictable software architectural patterns, the AI will likely recognise and help with all the boilerplate.

Of course there is a lot of middle ground between bad and good.

[physicles]

Do you mind getting into specifics about how you've been using AI to restructure your code? What tools are you using, and how large is the code base you're working with?

[inSenCite]

Using a combination of both chatgpt and claude/sonnet. Codebase is not very complex or cutting edge (e.g., data pipeline to maintain a local db, and an analytics system). These are not enterprise or even public facing applications.

For additional context I have not been a software engineer professionally for over a decade but still am in the engineering field.

Usually I will feed in a few functions (or just 1), sometimes a whole module if it small enough, and prompt it for general performance, and maintainability improvements. I just kinda iterate from there. I also restart chats often

[ImaCake]

Yeah LLMs are pretty good at doing things like moving a lambda function to the right spot or refactoring two overlapping classes to a base class. Often it only saves five minutes but that adds up over time.