this post was submitted on 17 Dec 2024
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I'm saying ChatGPT is not useless.
I'm a senior software engineer and I make use of it several times a week either directly or via things built on top of it. Yes you can't trust it will be perfect, but I can't trust a junior engineer to be perfect either—code review is something I've done long before AI and will continue to do long into the future.
I empirically work quicker with it than without and the engineers I know who are still avoiding it work noticeably slower. If it was useless this would not be the case.
Nice, me too, and whenever some tech-brained C-suite bozo tries to mansplain to me why LLMs will make me more efficient, I smile, nod politely, and move on, because at this point I don't think I can make the case that pasting AI slop into prod is objectively a worse idea than pasting Stack Overflow answers into prod.
At the end of the day, if I want to insert a snippet (which I don't have to double-check, mind you), auto-format my code, or organize my imports, which are all things I might use ChatGPT for if I didn't mind all the other baggage that comes along with it, Emacs (or Vim, if you swing that way) does this just fine and has done so for over 20 years.
If LOC/min or a similar metric is used to measure efficiency at your company, I am genuinely sorry.
I agree with you on the examples listed, there are much better tools than an LLM for that. And I agree no one should be copy and pasting without consideration, that's a misuse of these tools.
I'd say my main uses are kicking off a new test suite (obviously you need to go and check the assertions are what you expect, but it's usually about 95% there) which has gone from a decent percentage of the work for a feature down to an almost negligible amount of time. This one also results in me enjoying my job a bit more now too as I've always found writing tests a bit of a drudgery.
The other big use for me is that my organisation is pretty big and has a hefty amount of code (a good couple of thousand repos at least), we have a tool that's based on GPT which has processed all the code, so you can now ask queries about internal stuff that may not be well documented or particularly obvious. This one saves a load of time because I now don't always have to do the Slack merry go round to try and find an engineer that knows about what I'm looking for—sometimes it's still unavoidable, but they're less frequent moments now.
It's tied to OKR completion, which is generally based around delivery. If you deliver more feature work, it generally means your team's scores will be higher and assuming your manager is aware of your contributions, that translates to a bigger bonus. It's more of a carrot than a stick situation IMO, I could work less hard if I didn't want the extra money.
I worked at one of the biggest AI companies and their internal AI question/answer was dogshit for anything that could be answered by someone with a single fold in their brain. Maybe your co has a much better one, but like most others, I'm gonna go with the smooth brain hypothesis here.