Yeah also noticing similar bullshit. People send me exact steps on what to do written by ChatGPT that understands exactly nothing about the context and is therefore often wrong or a half truth at best.
Another client has pushed a single commit to a messy project that added 70k lines and a load of new features. The project is now unmaintainable.
Our dev tried to send me a generated summary and code. My reply was “Yes, i’ve read your llm summary. You’re still missing the fact that the script has hardcoded the same ip into every single client and consequently doesn’t work”
I am not even a developer but I’ve noticed tickets having a response written clearly by AI that miss several things I already talked to the person over teams about. Like dude read your own fucking comment before you post. The conclusion is wrong and you know that because we talked about it before you had the AI “figure out the problem” in the first place. Fuck. I know reading logs is really time consuming and annoying but the AI isn’t always very good or won’t just say “hey that log isn’t showing that I’m looking for” and instead just hallucinates something.
I don’t even hate AI, but could we at least use our fucking brains while using the AI? When it spits out code to me for my home projects, I, someone who is not a developer, still look at the code to make sure it’s not say running a loop that will hammer disk looking for 1200 files one at a time instead of pulling a directory listing and searching it or something very similar in the database I’m using. People have gotten so lazy. Maybe they’re tired of their bosses trying to force them and are providing garbage? I don’t know but can we just not? Lol.
I’ve had multiple people try and use LLMs to troubleshoot. It gives me a great feeling of job security. Those fuckers cannot think and in fact drove a boss to screen punching strokeout running him in a two hour circle over something i fixed with two clicks and cognitive function
Sometimes it can help troubleshoot but you have to already know what you’re doing so you can filter out really stupid suggestions and get to the “oh yeah I didn’t think about that” kind of stuff. If you’re relying on it completely, you’re gonna have a bad time lol.
Instructions are sloppy, code can be sloppy, but what I find is: when they review code changes they find real stuff. Not all the real stuff, but more real stuff than human reviewers typically find. A code review doesn’t need to be perfect, not even 100% correct, it just needs to show you stuff that you look at and think “damn, good to catch this now instead of in a field problem report a year from now…”
We only do about 3-10 reviews a week, depending… it’s not there to replace you, it’s there to help.
Before AI assistance we would do fewer reviews, because the AI is finding things - real things worth fixing - now some reviews (the reviews of our colleagues who haven’t figured out how to use AI to review their pull requests before submitting them effectively) get recycled 2-3 times before they’re adequately cleaned up.
Documentation and requirements are better aligned with code, unit test coverage is better, and the developers who use AI to review their code before putting in a pull request generally are getting through on the first pass. You still have to read the documentation and requirements, review the code, but now it’s actually approaching accurate and complete much more closely than it used to.
Our team is small and diverse, some do embedded C, some do GUI oriented .NET, some do backend processing in Rust / Linux - we all know our domains and there is lots of value in the collective wisdom, but it doesn’t translate super easily or efficiently - AI is helping with that.
If you’ve got 100 pull requests to review every day - quit. Maybe stick around for the paycheck until you find something better, but that’s not a job, that’s a clusterbomb waiting to go off.
For this, we need to start using (much more) secure ID tech, so you really know who is submitting, and prioritize those who have made good quality submissions in the past. Sadly, this may negelect “unknown” authors, but such is life.
Also, we may need to recruit more code authors / wanna be code authors to act as code reviewers more of the time, perhaps following the model we use in our commercial operation where all authors also act as reviewers.
Yeah also noticing similar bullshit. People send me exact steps on what to do written by ChatGPT that understands exactly nothing about the context and is therefore often wrong or a half truth at best.
Another client has pushed a single commit to a messy project that added 70k lines and a load of new features. The project is now unmaintainable.
Our dev tried to send me a generated summary and code. My reply was “Yes, i’ve read your llm summary. You’re still missing the fact that the script has hardcoded the same ip into every single client and consequently doesn’t work”
I am not even a developer but I’ve noticed tickets having a response written clearly by AI that miss several things I already talked to the person over teams about. Like dude read your own fucking comment before you post. The conclusion is wrong and you know that because we talked about it before you had the AI “figure out the problem” in the first place. Fuck. I know reading logs is really time consuming and annoying but the AI isn’t always very good or won’t just say “hey that log isn’t showing that I’m looking for” and instead just hallucinates something.
I don’t even hate AI, but could we at least use our fucking brains while using the AI? When it spits out code to me for my home projects, I, someone who is not a developer, still look at the code to make sure it’s not say running a loop that will hammer disk looking for 1200 files one at a time instead of pulling a directory listing and searching it or something very similar in the database I’m using. People have gotten so lazy. Maybe they’re tired of their bosses trying to force them and are providing garbage? I don’t know but can we just not? Lol.
I’ve had multiple people try and use LLMs to troubleshoot. It gives me a great feeling of job security. Those fuckers cannot think and in fact drove a boss to screen punching strokeout running him in a two hour circle over something i fixed with two clicks and cognitive function
Sometimes it can help troubleshoot but you have to already know what you’re doing so you can filter out really stupid suggestions and get to the “oh yeah I didn’t think about that” kind of stuff. If you’re relying on it completely, you’re gonna have a bad time lol.
I’m just glad people will write off my terrible code as AI.
Instructions are sloppy, code can be sloppy, but what I find is: when they review code changes they find real stuff. Not all the real stuff, but more real stuff than human reviewers typically find. A code review doesn’t need to be perfect, not even 100% correct, it just needs to show you stuff that you look at and think “damn, good to catch this now instead of in a field problem report a year from now…”
That’s fine when you’re looking at 1 or 2 reviews. Now try sifting through hundreds a day.
We only do about 3-10 reviews a week, depending… it’s not there to replace you, it’s there to help.
Before AI assistance we would do fewer reviews, because the AI is finding things - real things worth fixing - now some reviews (the reviews of our colleagues who haven’t figured out how to use AI to review their pull requests before submitting them effectively) get recycled 2-3 times before they’re adequately cleaned up.
Documentation and requirements are better aligned with code, unit test coverage is better, and the developers who use AI to review their code before putting in a pull request generally are getting through on the first pass. You still have to read the documentation and requirements, review the code, but now it’s actually approaching accurate and complete much more closely than it used to.
Our team is small and diverse, some do embedded C, some do GUI oriented .NET, some do backend processing in Rust / Linux - we all know our domains and there is lots of value in the collective wisdom, but it doesn’t translate super easily or efficiently - AI is helping with that.
If you’ve got 100 pull requests to review every day - quit. Maybe stick around for the paycheck until you find something better, but that’s not a job, that’s a clusterbomb waiting to go off.
I was referring to the people running open source projects that are receiving 100s of reviews per day from people just blasting outs PRs.
For this, we need to start using (much more) secure ID tech, so you really know who is submitting, and prioritize those who have made good quality submissions in the past. Sadly, this may negelect “unknown” authors, but such is life.
Also, we may need to recruit more code authors / wanna be code authors to act as code reviewers more of the time, perhaps following the model we use in our commercial operation where all authors also act as reviewers.