why leave comments intended for your human colleague when they will only forward them to the bot?
why not speak directly to the bot yourself instead? then you can drop pretenses and get to the point
I find this to be a new variant of the old behavior where a colleague comments on a typo in a PR, and the team later moans about laborious back and forth for small nitpicks, instead of simply editing the typo right there (and perhaps leaving a note that they did so)
yeah I have this happen to me. I occasionally get screenshots of claude sent to me!
I had this happen to me twice. The first time I ignored it, second time I responddd with “I could have asked ChatGPT myself but I asked you”. Never happened again.
"why are you such a drag on team morale?", "why are you invalidating your colleagues learning experiences?" "Next time you do this, HR will have to step in" etc etc.
There's no justice in this world.
I’d you’re not willing to stand your ground and have a direct conversation with your co worker then there’s no solution to it.
Because it doesn't matter what you say to the bot. You might as well have a conversation with yourself about the PR.
The bot isn't making decisions. It's not choosing to submit extensive PRs with bad code. The colleague is the one who needs to actually learn something here, and the problem is that confronting him about it directly is widely considered to be bad form. This is, of course, a deeply unhealthy aspect of our corporate culture. We need to be more open to honest communication, even when it's either uncomplimentary of one of the people involved, or counter to the prevailing opinions within the company.
let's take the two stories to management:
"I'm writing tons of code, and the process is stumbling where the guy whose job it is to review code isn't reviewing it."
"I'm not reviewing code."
Sometimes I wonder: how does someone go and think so much about their coworkers, and never once think about how they themselves look?
Even if I sympathize with the people complaining about their poorly chosen GitHub-based workflow - whose purpose is to let pull requests languish, for the most part - and how they stumble when overwhelmed with solutions. It's obvious to me, that the people who complain the loudest about the anti-sociality of LLM authored code in their precious harmonious low-effort workplace status quo: they are projecting.
Imagine you are a restaurant reviewer. Your job is unquestionably to go to restaurants, order and eat food, and write a review. The restaurant's job is to provide you food to eat and review.
You go to a new restaurant, and order some dishes, and one of the plates your server brings out is a big ol pile of dog shit.
Who's being anti-social in this situation? The restaurant is doing its job and all they're asking is that you do yours. On the other hand, you have certain expectations about what you order from the restaurant and they're not being met. Who's anti-social?
He's not bringing you a pile of dog shit. He's bringing you some food he went to the restaurant next doors to get. How do you review it?
I cannot think of a single actual food critic that would consider it acceptable for a restaurant to serve a dish for review that they went to the restaurant next door to get. If the critic wanted to eat at/review that restaurant they would simply have gone there instead.
His point, exactly.
what is the point? this whole restaurant analogy is completely fictitious and happens nowhere, and the scenario i'm describing is happening all the time... why not just talk about the not imaginary scenario?
So he’s redundant. You call Uber Eats and you don’t pay a salary for that.
The person who "writes" code is also supposed to review their own work, and answer for that. If they won't do that - well - they should be fired. But if you have weak or uninvolved leadership, then the team's only rational recourse is to shun them.
It’s much more effort to verify that code is correct than it is to produce it. This is the case even for human-written code, and now that we face a torrent of ok-looking probably-usable AI generated code, the problem is compounded infinitely.
If someone’s using AI to generate a large quantity of actually-tested, actually-good code then that’s one thing. If they’re generating a fire hose of slop and demanding that others do the actual human time-consuming work of validating that code then that person is the problem. It’s hard to tell which is the case here.