3 ms·

Maybe didn't have the environment set up locally and did initial investigative work?

rsynnott 3y ago
So, if I wanted to investigate ORM output and didn't have an appropriate environment set up, I would simply set one up. If you just want to see SQL output this should be trivial; clone the repo, install any dependencies, modify an integration test. What I would not do is ask a machine noted for its confident incorrectness to imagine what the ORM's output might be. Like, this is not doing investigative work. That’s not what ‘investigative’ means.
- mewpmewp2 3y ago
  So imagine there is an urgent performance issue in production and you have a hunch that this SQL code may be the culprit. However before doing all of what you mentioned you want to verify it before following down a bad path. Maybe the environment setup could take few hours, maybe it is not a repo or codebase you are even familiar with. Typical in a large org. But if you know the SQL you will be able to run it raw to see if this causes it. Then maybe you can page the correct team to wake them up etc and fix it themselves.
  - rsynnott 3y ago
    But _you do not_ know the SQL. To be clear, ChatGPT will not be able to tell you what the ORM will generate. At best, it may tell you something that an ORM might plausibly generate. (If it's a _production_ issue, then you should talk to whoever runs your databases and ask them to look at their diagnostics; most DBMs will have a slow query log, for a start. You could also enable logging for a sample of traffic. There are all sorts of approaches likely to be more productive than _guessing_.)
    - mewpmewp2 3y ago
      So I don't know what use-case exactly OP had, but all of your suggestions can potentially take hour or more and might depend on other people or systems you might not have access to. While with GPT you can get an answer in 10 seconds, and then potentially try out the query in the database yourself to see if it works or not. If it worked for him so far, it must've worked accurately enough. I would see this some sort of niche solution although OP seemed to indicate it's a recurrent thing they do. I have used ChatGPT for thousands of things, which are on the scale of like this, although I would mostly use if it's potentially an ORM I don't know anything about in a language I don't have experience with, e.g. to see if does some sort of JOIN underneath or does an IN query. If there was a performance issue to debug, then best case is that the query was problematic, and then when I run the GPTs generated query I will see that it was slow, so that's a signal to investigate it further.
      - NoGravitas 3y ago
        The answer you get in 10 seconds is worthless, though, because you need to know what SQL the ORM is actually generating, not what it might reasonably generate.
        mewpmewp2 3y ago
        You are thinking in a too binary way. It's about getting insights/signals. Life is full of uncertainties in everything. Nothing is for sure. You must incorporate probabilities in your decisions to be able to be as successful as you can be, instead of thinking either 100% or 0%. Nothing is 100%.
        NoGravitas 3y ago
        But it is a meaningless signal! It does not tell you anything new about your problem, it is not evidence! I mean, I could consult my Tarot cards for insight on how to proceed with debugging the problem, that would not be useless. Same for Oblique Strategies. But in this case, I already know how to debug the problem, which is to change the logging settings on the ORM.
oxfordmale 3y ago
I am a Data Engineer. I can spin up the service locally, but it would probably take me half a day to install the right versions etc and change the log level. The code is there, ChatGPT does a good enough job at it, or at least did. It is super easy to verify it did a decent job at it.

So, if I wanted to investigate ORM output and didn't have an appropriate environment set up, I would simply set one up. If you just want to see SQL output this should be trivial; clone the repo, install any dependencies, modify an integration test. What I would not do is ask a machine noted for its confident incorrectness to imagine what the ORM's output might be. Like, this is not doing investigative work. That’s not what ‘investigative’ means.

mewpmewp2 3y ago
So imagine there is an urgent performance issue in production and you have a hunch that this SQL code may be the culprit. However before doing all of what you mentioned you want to verify it before following down a bad path. Maybe the environment setup could take few hours, maybe it is not a repo or codebase you are even familiar with. Typical in a large org. But if you know the SQL you will be able to run it raw to see if this causes it. Then maybe you can page the correct team to wake them up etc and fix it themselves.
- rsynnott 3y ago
  But _you do not_ know the SQL. To be clear, ChatGPT will not be able to tell you what the ORM will generate. At best, it may tell you something that an ORM might plausibly generate. (If it's a _production_ issue, then you should talk to whoever runs your databases and ask them to look at their diagnostics; most DBMs will have a slow query log, for a start. You could also enable logging for a sample of traffic. There are all sorts of approaches likely to be more productive than _guessing_.)
  - mewpmewp2 3y ago
    So I don't know what use-case exactly OP had, but all of your suggestions can potentially take hour or more and might depend on other people or systems you might not have access to. While with GPT you can get an answer in 10 seconds, and then potentially try out the query in the database yourself to see if it works or not. If it worked for him so far, it must've worked accurately enough. I would see this some sort of niche solution although OP seemed to indicate it's a recurrent thing they do. I have used ChatGPT for thousands of things, which are on the scale of like this, although I would mostly use if it's potentially an ORM I don't know anything about in a language I don't have experience with, e.g. to see if does some sort of JOIN underneath or does an IN query. If there was a performance issue to debug, then best case is that the query was problematic, and then when I run the GPTs generated query I will see that it was slow, so that's a signal to investigate it further.
    - NoGravitas 3y ago
      The answer you get in 10 seconds is worthless, though, because you need to know what SQL the ORM is actually generating, not what it might reasonably generate.
      - mewpmewp2 3y ago
        You are thinking in a too binary way. It's about getting insights/signals. Life is full of uncertainties in everything. Nothing is for sure. You must incorporate probabilities in your decisions to be able to be as successful as you can be, instead of thinking either 100% or 0%. Nothing is 100%.
        NoGravitas 3y ago
        But it is a meaningless signal! It does not tell you anything new about your problem, it is not evidence! I mean, I could consult my Tarot cards for insight on how to proceed with debugging the problem, that would not be useless. Same for Oblique Strategies. But in this case, I already know how to debug the problem, which is to change the logging settings on the ORM.

oxfordmale 3y ago

I am a Data Engineer. I can spin up the service locally, but it would probably take me half a day to install the right versions etc and change the log level. The code is there, ChatGPT does a good enough job at it, or at least did. It is super easy to verify it did a decent job at it.