> LLMs don’t copy-paste (or cut and paste) code. For instance, when you ask them to refactor a big file into smaller ones, they’ll "remember" a block or slice of code, use a delete tool on the old file, and then a write tool to spit out the extracted code from memory. There are no real cut or paste tools. Every tweak is just them emitting write commands from memory. This feels weird because, as humans, we lean on copy-paste all the time.
There is not that much copy/paste that happens as part of refactoring so it leans to just using context recall. It's not entirely clear if providing an actual copy/paste command is particularly useful, at least from my testing it does not do much. More interesting are repetitive changes that clog up the context. Those you can improve on if you have `fastmod` or some similar tool available: with it you can instruct codex or claude to perform edits with it.
> And it’s not just how they handle code movement -- their whole approach to problem-solving feels alien too.
It is, but if you go back and forth to work out a plan for how to solve the problem, then the approach greatly changes.
To use another example, with my IDE I can change a signature or rename something across multiple files basically instantly. But an LLM agent will take multiple minutes to do the same thing and doesn't get it right.
> How is it not clear that it would be beneficial?
There is reinforcement learning on the Anthropic side for a text edit tool, which is built in a way that does not lend itself to copy/paste. If you use a model like the GPT series then there might not be reinforcement learning for text editing (I believe, I don't really know), but it operates on line-based replacements for the most part and for it to understand what to manipulate it needs to know the content in the context. When you try to give it a copy/paste buffer it does not fully comprehend what the change in the file looks like after the operation.
So it might be possible to do something with copy/paste, but I did not find it to be very obvious how you make that work with an agent, given that it needs to read the file into context anyways and its recall capabilities are surprisingly good.
> To use another example, with my IDE I can change a signature or rename something across multiple files basically instantly.
So yeah, that's the more interesting case and there things like codemod/fastmod are very effective if you tell an agent to use it. They just don't reach there.
I think copy/paste can alleviate context explosion. Basically the model can remember what's the code block contain, can access it at any time, without needing to "remember" it.
There is not that much copy/paste that happens as part of refactoring so it leans to just using context recall. It's not entirely clear if providing an actual copy/paste command is particularly useful, at least from my testing it does not do much. More interesting are repetitive changes that clog up the context. Those you can improve on if you have `fastmod` or some similar tool available: with it you can instruct codex or claude to perform edits with it.
> And it’s not just how they handle code movement -- their whole approach to problem-solving feels alien too.
It is, but if you go back and forth to work out a plan for how to solve the problem, then the approach greatly changes.