:shrug: I'm one person on the Internet, so if using the LLM makes it work better for more of your users, go with that.
I do think data filtering and visualization is an important value add, Pytrace looks cool, but it doesn't look much different from what I get if I debug Javascript in a web browser, so I think there's a ton of room to improve. Visual representations of data transformations and code paths are a relatively unexplored area across the entire software industry imo.
If an LLM could flat-out reduce my need to reason and fix the bug for me, great -- but I've worked with coders that I respect a lot, and remote debugging with them has always been a pain and made narrowing down issues harder. I've never enjoyed debugging something remotely where I was working through a middleperson and couldn't look at what was going on; it's helpful to have multiple eyes on the code, but not if I have to use someone else's eyes to look at what's happening.
So for me, in order to successfully reduce the amount of reasoning I need to do and overcome the downside of me not being able to visualize the timeline/data, the LLM would need to be better at fixing these bugs than professional developers in industry: developers who are already intimately familiar with the codebases I'm debugging because they wrote a significant portion of the code. It would need to be better at coding than professional humans. And I just don't think there's anyone who would say that GPT-4 is close to that level yet.
What I could see is, maybe -- if I have access to that data, and the LLM is just kind of on-the-side, maybe at that point it can offer helpful advice and there wouldn't be a downside because I would still be able to debug as fast as I can using all of the available data, and if the LLM can occasionally find something I missed, then great. Peer-debugging sessions with multiple coders are great, so at least in theory I could see some value from an LLM on that stuff, even if I'm a little skeptical about potential performance. And if the LLM wasn't in front of the entire data, if it didn't work then no worries, the data is still there.
But again, if people like it, then it doesn't matter what I think. Why I wouldn't use the tool is less important than why someone would use the tool, and if integration with the LLM makes people want to use the tool, then... I mean, not everyone has identical work styles. Different things might work for different people.
I do think data filtering and visualization is an important value add, Pytrace looks cool, but it doesn't look much different from what I get if I debug Javascript in a web browser, so I think there's a ton of room to improve. Visual representations of data transformations and code paths are a relatively unexplored area across the entire software industry imo.
If an LLM could flat-out reduce my need to reason and fix the bug for me, great -- but I've worked with coders that I respect a lot, and remote debugging with them has always been a pain and made narrowing down issues harder. I've never enjoyed debugging something remotely where I was working through a middleperson and couldn't look at what was going on; it's helpful to have multiple eyes on the code, but not if I have to use someone else's eyes to look at what's happening.
So for me, in order to successfully reduce the amount of reasoning I need to do and overcome the downside of me not being able to visualize the timeline/data, the LLM would need to be better at fixing these bugs than professional developers in industry: developers who are already intimately familiar with the codebases I'm debugging because they wrote a significant portion of the code. It would need to be better at coding than professional humans. And I just don't think there's anyone who would say that GPT-4 is close to that level yet.
What I could see is, maybe -- if I have access to that data, and the LLM is just kind of on-the-side, maybe at that point it can offer helpful advice and there wouldn't be a downside because I would still be able to debug as fast as I can using all of the available data, and if the LLM can occasionally find something I missed, then great. Peer-debugging sessions with multiple coders are great, so at least in theory I could see some value from an LLM on that stuff, even if I'm a little skeptical about potential performance. And if the LLM wasn't in front of the entire data, if it didn't work then no worries, the data is still there.
But again, if people like it, then it doesn't matter what I think. Why I wouldn't use the tool is less important than why someone would use the tool, and if integration with the LLM makes people want to use the tool, then... I mean, not everyone has identical work styles. Different things might work for different people.