I use LLMs for various purposes in day to day development. I don't use any of the tools mentioned in the article because I'm using intellij and don't want to replace a tool that has lots of stuff that I use all the time. But aside from that, it's good advice and matches my experience.
I've dabbled with plugins for intellij but wasn't really happy with those. But ever since chat gpt for desktop started interfacing directly with jetbrains products (and vs code as well), that's my goto tool. I realized that I like being able to pull that up with a simple keybinding and it auto connects to the IDE when I do. I don't need to replace my tools and I get to have AI support ready to go. Most of the existing plugins seem to insist on some crappy auto complete, which in a tool that offers a lot of auto complete features already is a bit of an anti feature. I don't need clippy style autocomplete.
What matters here is the tool integration, not the model quality. Better tool integration means better prompts with less work and getting better answers that way.
Example: I run a test, it fails with some output. I had this yesterday. So I asked, "why is this failing" and had a short discussion about what could be wrong. No need for me to specify any detail; all extracted from the IDE. We ticked off a few possible causes, I excluded them. And then it noticed a subtle change in the log messages that I had not noticed (a co-routine context switch) that turned out to be the root cause.
That kind of open ended debugging is a bit of a mixed bag. Sometimes it finds stuff. Mostly it just starts proposing solutions based on a poor analysis of the problem.
What works pretty reliably is:
- address the TODOs / FIXMEs, especially if you give it some examples of what you expect
- write documentation (very good for this)
- evaluate if I covered all the edge cases (often finds stuff I want to fix)
- simple code transformations (rewrite this using framework X instead of Y)
I don't trust it blindly. But it's generally giving me good code and feedback. And I get to outsource a lot of the boring crap.
Yes I find chatGPT/Jetbrains (RubyMine) in my case is the most usable setup I've encountered.
It's like Rubymine is "home" for me - and chatGPT's macOS client has become another "home" for me so it's quite convenient that they talk to each other now.
I have a little FOMO about Cursor though. ChatGPT will automatically apply its suggested changes to my open editor - but I have the sense Cursor will do a bit more? Apply changes to multiple files? And have knowledge of your whole project, not just open files? Can someone fill me in
I've dabbled with plugins for intellij but wasn't really happy with those. But ever since chat gpt for desktop started interfacing directly with jetbrains products (and vs code as well), that's my goto tool. I realized that I like being able to pull that up with a simple keybinding and it auto connects to the IDE when I do. I don't need to replace my tools and I get to have AI support ready to go. Most of the existing plugins seem to insist on some crappy auto complete, which in a tool that offers a lot of auto complete features already is a bit of an anti feature. I don't need clippy style autocomplete.
What matters here is the tool integration, not the model quality. Better tool integration means better prompts with less work and getting better answers that way.
Example: I run a test, it fails with some output. I had this yesterday. So I asked, "why is this failing" and had a short discussion about what could be wrong. No need for me to specify any detail; all extracted from the IDE. We ticked off a few possible causes, I excluded them. And then it noticed a subtle change in the log messages that I had not noticed (a co-routine context switch) that turned out to be the root cause.
That kind of open ended debugging is a bit of a mixed bag. Sometimes it finds stuff. Mostly it just starts proposing solutions based on a poor analysis of the problem.
What works pretty reliably is:
- address the TODOs / FIXMEs, especially if you give it some examples of what you expect
- write documentation (very good for this)
- evaluate if I covered all the edge cases (often finds stuff I want to fix)
- simple code transformations (rewrite this using framework X instead of Y)
I don't trust it blindly. But it's generally giving me good code and feedback. And I get to outsource a lot of the boring crap.