working in a large codebase I use Claude for code understanding and the code reviews from Macroscope have caught bugs for me a bunch of times. Usually if I use claude it’s for refactoring a and source to source transformations that would be too confusing for me to figure out how to do with e.g. ast-grep, but that I can prompt in a minute or two and then have claude work through it. It’s stuff I could do without LLMs but it’s less effort to use them. I don’t let it write new code, because it decays the process of programming as theory building.
not the person you're replying to, but someone who agrees with the gist of their message - I personally use Claude Code as a better Google search for debugging and syntax.
It used to be "oh, why am I getting an error on line 352, let me google the error message and wade through Stack Overflow answers" now it's "Claude, why am I getting an error on line 352? Ah, it's because $REASON, let's see if that fixes it, yes, thank you."
Obviously reading the official documentation is very useful, but sometimes you can't find anything that relevant to your exact use case, and forums are also very useful, but it can take hours or even days to get a reply to question when the LLM can do it in like a minute.
I've used both ChatGPT and Claude, they seem interchangeable for my needs. I only use the web prompt interface except for the rare occasion that it is helpful for it to have the context of my entire project. I think less is more when it comes to LLM interaction, but sometimes they are exactly the right tool for the job.
I didn't realize you wanted that information too, I could probably bore someone to death talking about it.
Planning: I often ask it to help me plan an approach if we are dealing with something I don't have a lot of experience with, most recently working with the DOM. If there is a library or an API that is new to me, I ask for an overview and run my plan by it for comments. Feed it the documentation and it is like talking to author.
Coding: I have a pretty reliable sense for when a section of code that I want to write is obvious enough for the LLM to one-shot based on the other code in the file, and on those occasions I call in completion. I do this with code that I can verify at a glance.
Analysis: If I have any uncertainty at all about the code I've written, I run it by the LLM to find issues. Out of all the other uses, I think this is the most productive and time saving. If I run into a bug and I'm stumped, I show it the section of code. I'm amazed at how good it is at finding mistakes.
I'm working solo as a full stack developer coming from a different background, so I sometimes find myself out of my depth. Having access to the breadth of knowledge that an LLM brings and its attention to detail has been game changing. I've tried a couple agents and configuring them to work competently seems like a rabbit hole, and I like the tight control over the context that chatting with the web prompt interface brings. It seems like half the value is putting into words my intent, it forces me to have a cohesive understanding myself. It is like rubber duck debugging where the duck can actually talk back and sometimes provide the critical part that I'm missing. I have it speak like a pirate which is just for fun but sometimes the sailing metaphors that it uses are really intuitive.
working in a large codebase I use Claude for code understanding and the code reviews from Macroscope have caught bugs for me a bunch of times. Usually if I use claude it’s for refactoring a and source to source transformations that would be too confusing for me to figure out how to do with e.g. ast-grep, but that I can prompt in a minute or two and then have claude work through it. It’s stuff I could do without LLMs but it’s less effort to use them. I don’t let it write new code, because it decays the process of programming as theory building.
not the person you're replying to, but someone who agrees with the gist of their message - I personally use Claude Code as a better Google search for debugging and syntax.
It used to be "oh, why am I getting an error on line 352, let me google the error message and wade through Stack Overflow answers" now it's "Claude, why am I getting an error on line 352? Ah, it's because $REASON, let's see if that fixes it, yes, thank you."
Obviously reading the official documentation is very useful, but sometimes you can't find anything that relevant to your exact use case, and forums are also very useful, but it can take hours or even days to get a reply to question when the LLM can do it in like a minute.
I've used both ChatGPT and Claude, they seem interchangeable for my needs. I only use the web prompt interface except for the rare occasion that it is helpful for it to have the context of my entire project. I think less is more when it comes to LLM interaction, but sometimes they are exactly the right tool for the job.
What do you use it for then?
“right tool for the job” - what job exactly, why so mysterious?
I didn't realize you wanted that information too, I could probably bore someone to death talking about it.
Planning: I often ask it to help me plan an approach if we are dealing with something I don't have a lot of experience with, most recently working with the DOM. If there is a library or an API that is new to me, I ask for an overview and run my plan by it for comments. Feed it the documentation and it is like talking to author.
Coding: I have a pretty reliable sense for when a section of code that I want to write is obvious enough for the LLM to one-shot based on the other code in the file, and on those occasions I call in completion. I do this with code that I can verify at a glance.
Analysis: If I have any uncertainty at all about the code I've written, I run it by the LLM to find issues. Out of all the other uses, I think this is the most productive and time saving. If I run into a bug and I'm stumped, I show it the section of code. I'm amazed at how good it is at finding mistakes.
I'm working solo as a full stack developer coming from a different background, so I sometimes find myself out of my depth. Having access to the breadth of knowledge that an LLM brings and its attention to detail has been game changing. I've tried a couple agents and configuring them to work competently seems like a rabbit hole, and I like the tight control over the context that chatting with the web prompt interface brings. It seems like half the value is putting into words my intent, it forces me to have a cohesive understanding myself. It is like rubber duck debugging where the duck can actually talk back and sometimes provide the critical part that I'm missing. I have it speak like a pirate which is just for fun but sometimes the sailing metaphors that it uses are really intuitive.
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