Comment by bicx

I think it depends on the kind of work you're doing, but I use it on mature codebases where I am the expert, and I heavily delegate to Claude Code. By being knowledgeable of the codebase, I know exactly how to specify a task I need performed. I set it to work on one task, then I monitor it while personally starting on other work.

I think LLMs shine when you need to write a higher volume of code that extends a proven pattern, quickly explore experiments that require a lot of boilerplate, or have multiple smaller tasks that you can set multiple agents upon to parallelize. I've also had success in using LLMs to do a lot of external documentation research in order to integrate findings into code.

If you are fine-tuning an algorithm or doing domain-expert-level tweaks that require a lot of contextual input-output expert analysis, then you're probably better off just coding on your own.

Context engineering has been mentioned a lot lately, but it's not a meme. It's the real trick to successful LLM agent usage. Good context documentation, guides, and well-defined processes (just like with a human intern) will mean the difference between success and failure.