[GiorgioG]

My experience is that it will simply make up methods, properties and fields that do NOT exist in well-documented APIs. If something isn't possible, that's fine, just tell me it's not possible. I spent an hour trying to get ChatGPT (4/4o and 3.5) to write some code to do one specific thing (dump/log detailed memory allocation data from the current .NET application process) for diagnosing an intermittent out of memory exception in a production application. The answer as far as I can tell is that it's not possible in-process. Maybe it's possible out of process using the profiling API, but that doesn't help me in a locked-down k8s pod/container in AWS.

[empath75]

I think once you understand that they're prone to do that, it's less of a problem in practice. You just don't ask it questions that requires detailed knowledge of an API unless it's _extremely_ popular. Like in kubernetes terms, it's safe to ask it about a pod spec, less safe to ask it details about istio configuration and even less safe to ask it about some random operator with 50 stars on github.

Mostly it's good at structure and syntax, so I'll often find the library/spec I want, paste in the relevant documentation and ask it to write my function for me.

This may seem like a waste of time because once you've got the documentation you can just write the code yourself, but A: that takes 5 times as long and B: I think people underestimate how much general domain knowledge is buried in chatgpt so it's pretty good at inferring the details of what you're looking for or what you should have asked about.

In general, I think the more your interaction with chatgpt is framed as a dialogue and less as a 'fill in the blanks' exercise, the more you'll get out of it.

[neonsunset]

From within the process it might be difficult*, but please do give this a read https://learn.microsoft.com/en-us/dotnet/core/diagnostics/du... and dotnet-dump + dotnet-trace a try.

If you are still seeing the issue with memory and GC, you can submit it to https://github.com/dotnet/runtime/issues especially if you are doing something that is expected to just work(tm).

* difficult as in retrieving data detailed enough to trace individual allocations, otherwise `GC.GetGCMemoryInfo()` and adjacent methods can give you high-level overview. There are more advanced tools but I always had the option to either use remote debugging in Windows Server days and dotnet-dump and dotnet-trace for containerized applications to diagnose the issues, so haven't really explored what is needed for the more locked down environments.