Shame. There was a time that people dug out of their own messes, I think you learn more, faster

Yes, that’s how we became senior guys. But when you have deadlines that you’re both on the hook for and they’re just floundering, you can only give them so much opportunity. I’ve had too many arguments with management about letting them merge and I’m not letting that ruin my code base

Speaking of meaningless metrics, how many people ask you for Lines Of Code counts, even today?

We have a new VP collecting metrics on everyone, including lines of code, number of merge requests, times per day using ai, days per week in the office vs at home

Experienced software developer, here. "AI" is useful to me in some contexts. Specifically when I want to scaffold out a completely new application (so I'm not worried about clobbering existing code) and I don't want to do it by hand, it saves me time.

And... that's about it. It sucks at code review, and will break shit in your repo if you let it.

I’ve had too many arguments with management about letting them merge and I’m not letting that ruin my code base

I guess I'm lucky, before here I always had 100% control of the code I was responsible for. Here (last 12 years) we have a big team, but nobody merges to master/main without a review and screwups in the section of the repository I am primarily responsible for have been rare.

We have a new VP collecting metrics on everyone, including lines of code, number of merge requests, times per day using ai, days per week in the office vs at home

I have been getting actively recruited - six figures+ - for multiple openings right here in town (not a huge market here, either...) this may be the time...

"Using something that you're not experienced with and haven't yet worked out how to best integrate into your workflow slows some people down"

Wow, what an insight! More at 8!

As I said on this article when it was posted to another instance:

AI is a tool to use. Like with all tools, there are right ways and wrong ways and inefficient ways and all other ways to use them. You can’t say that they slow people down as a whole just because some people get slowed down.

Fun how the article concludes that AI tools are still good anyway, actually.

This AI hype is a sickness

As a developer

• I can jot down a bunch of notes and have ai turn it into a reasonable presentation or documentation or proposal
• zoom has an ai agent which is pretty good about summarizing a meeting. It usually just needs minor corrections and you can send it out much faster than taking notes
• for coding I mostly use ai like autocomplete. Sometimes it’s able to autocomplete entire code blocks
• for something new I might have ai generate a class or something, and use it as a first draft where I then make it work

That's happening right now. I have a few friends who are looking for entry-level jobs and they find none.

It really sucks.

That said, the future lack of developers is a corporate problem, not a problem for developers. For us it just means that we'll earn a lot more in a few years.

They wanted someone with experience, who can hit the ground running, but didn't want to pay for it, either with cash or time.

• cheap
• quick
• experience

You can only pick two.

Not really.

Linter in the build pipeline is generally not useful because most people won’t give results time or priority. You usually can’t fail the build for lint issues so all it does is fill logs. I usually configure a linter and prettifier in a precommit hook, to shift that left. People are more willing to fix their code in small pieces as they try to commit.

But this is also why SonarQube is a key tool. The scanners are lint-like, and you can even import some lint output. But the important part is it tries to prioritize them, score them, and enforce a quality gate based on them. I usually can’t fail a build for lint errors but SonarQube can if there are too many or too priority, or if they are security related.

But this is not the same as a code review. If an ai can use the code base as context, it should be able to add checks for consistency and maintainability similar to the rest of the code. For example I had a junior developer blindly follow the AI to use a different mocking framework than the rest of the code, for no reason other than it may have been more common in the training data. A code review ai should be able to notice that. Maybe this is too advanced for current ai, but the same guy blindly followed ai to add classes that already existed. They were just different enough that SonarQube didn’t flag is as duplicate code but ai ought to be able to summarize functionality and realize they were the same. Or I wonder if ai could do code organization? Junior guys spew classes and methods everywhere without any effort in organizing like with like, so someone can maintain it all. Or how about style? I hope yo never revisit style wars but when you’re modifying code you really need to follow style and naming of what’s already there. Maybe ai code review can pick up on that

Who says I made my webapp with ChatGPT in an afternoon?

I built it iteratively using ChatGPT, much like any other application. I started with the scaffolding and then slowly added more and more features over time, just like I would have done had I not used any AI at all.

Like everybody knows, Rome wasn't built in a day.

It may also be self fulfilling. Our new ceo said all upcoming projects must save 15% using ai, and while we’re still hiring it’s only in India.

So 6 months from now we will have status reports talking about how we saved 15% in every project

Explain this too me AI. Reads back exactly what's on the screen including comments somehow with more words but less information
Ok....

Ok, this is tricky. AI, can you do this refactoring so I don't have to keep track of everything. No... Thats all wrong... Yeah I know it's complicated, that's why I wanted it refactored. No you can't do that... fuck now I can either toss all your changes and do it myself or spend the next 3 hours rewriting it.

Yeah I struggle to find how anyone finds this garbage useful.

If you give it the right task, it’s super helpful. But you can’t ask it to write anything with any real complexity.

Where it thrives is being given pseudo code for something simple and asking for the specific language code for it. Or translate between two languages.

That’s… about it. And even that it fucks up.

So you treated it like a junior developer and did a thorough review of its output.

I think the only disagreement here is on the semantics.

Explain this too me AI. Reads back exactly what's on the screen including comments somehow with more words but less information
Ok....

Ok, this is tricky. AI, can you do this refactoring so I don't have to keep track of everything. No... Thats all wrong... Yeah I know it's complicated, that's why I wanted it refactored. No you can't do that... fuck now I can either toss all your changes and do it myself or spend the next 3 hours rewriting it.

Yeah I struggle to find how anyone finds this garbage useful.

Same. I also like it for basic research and helping with syntax for obscure SQL queries, but coding hasn't worked very well. One of my less technical coworkers tried to vibe code something and it didn't work well. Maybe it would do okay on something routine, but generally speaking it would probably be better to use a library for that anyway.

I like the saying that LLMs are “good” at stuff you don’t know. That’s about it.

When you know the subject it stops being much useful because you’ll already know the very obvious stuff that LLM could help you.

Fun how the article concludes that AI tools are still good anyway, actually.

This AI hype is a sickness

That's still not actually knowing anything. It's just temporarily adding more context to its model.

And it's always very temporary. I have a yarn project I'm working on right now, and I used Copilot in VS Code in agent mode to scaffold it as an experiment. One of the refinements I included in the prompt file to build it is reminders throughout for things it wouldn't need reminding of if it actually "knew" the repo.

• I had to constantly remind it that it's a yarn project, otherwise it would inevitably start trying to use NPM as it progressed through the prompt.
• For some reason, when it's in agent mode and it makes a mistake, it wants to delete files it has fucked up, which always requires human intervention, so I peppered the prompt with reminders not to do that, but to blank the file out and start over in it.
• The frontend of the project uses TailwindCSS. It could not remember not to keep trying to downgrade its configuration to an earlier version instead of using the current one, so I wrote the entire configuration for it by hand and inserted it into the prompt file. If I let it try to build the configuration itself, it would inevitably fuck it up and then say something completely false, like, "The version of TailwindCSS we're using is still in beta, let me try downgrading to the previous version."

I'm not saying it wasn't helpful. It probably cut 20% off the time it would have taken me to scaffold out the app myself, which is significant. But it certainly couldn't keep track of the context provided by the repo, even though it was creating that context itself.

Working with Copilot is like working with a very talented and fast junior developer whose methamphetamine addiction has been getting the better of it lately, and who has early onset dementia or a brain injury that destroyed their short-term memory.