Of course but presumably on occasion you do work in other languages? I work in all kinds of languages and so jumping between them it’s pretty handy to bridge the gap.

If I were jumping languages a lot, I definitely think it would be helpful. But pretty much 100% of what I’ve done for the last 3-4 years is Go (mostly) or JavaScript (occasionally). I have used chatgpt the few times I needed to work in some other language, but that has been pretty rare.

I think you could definitely still get value out of generating simple stuff though, at least for me it really helps get projects done quickly without burning myself out

If simple stuff == for loops and basic boilerplate, the kind of stuff that copilot can autocomplete, I write that on autopilot and it doesn’t really register. So it doesn’t contribute to my burnout. If simple stuff == boring, boilerplate tests, I’ll admit that I don’t do nearly enough of that. But doing the ‘prompt engineering’ to get copilot to write that wasn’t any less painful that writing it myself.

For small one off scripts it makes them actually save more time than they take to write

The other day I wrote a duplicate image detector for my sister (files recovered from a dying drive). In hindsight I could have asked chatgpt to do it. But it was something I’ve never done before and an interesting problem so it was more fun to do it myself. And most of the one off stuff I’m asked to do by coworkers is tied to our code and our system and not the kind of thing chatgpt would know how to do.

func randomRGB(uid int) color.RGBA {
	b := binary.BigEndian.AppendUint64(nil, uint64(uid))
	h := sha256.Sum256(b)
	return color.RGBA{h[0], h[1], h[2], 255}
}

That took me under three minutes and half of that was remembering that RGBA is in the color package, not the image package, and uint-to-bits is in the binary package, not the math package. I have found chatgpt useful when I was working in a different language. But trying to get chatgpt or copilot to write tests or documentation for me (the kind of work that bores me to death), doing the prompt engineering to get it to spit out something useful was more work than just writing the tests/documentation myself. Except for the time when I needed to write about 100 tests that were all nearly the same. In that case, using chatgpt was worth it.

If I’ve been working in the same language for at least a year or two, I don’t have to look up any of that. Copilot might be actually helpful if I’m working in a language I’m not used to, but it’s been a long time since I’ve had to look up syntax or functions (excluding 3rd party packages) for the language I work in.

I won’t say copilot is completely useless for code. I will say that it’s near useless for me. The kind of code that it’s good at writing is the kind of code that I can write in my sleep. When I write a for-loop to iterate over an array and print it out (for example), it takes near zero brain power. I’m on autopilot, like driving to work. On the other hand, when I was trialing copilot I’d have to check each suggestion it made to verify that it wasn’t giving me garbage. Verifying copilot’s suggestions takes a lot more brain power than just writing it myself. And the difference in time is minimal. It doesn’t take me much longer to write it myself than it does to validate copilot’s work.

My comment game has gotten far better since I started doing live code reviews. Essentially I ask myself, “Would I feel the need to explain this to someone during a code review?” and if the answer is yes I add a comment.

That’s a hot take. If you want your code to be maintainable at all, it needs comments. If you’re part of a team, write comments for them. If someone else may take over your project after you move on, leave comments for them. And have you ever tried to read uncommented code you wrote a year ago? Leave comments for yourself.

I’d create my own macro or function for that. I have enough ADD that I cannot stand boring shit like that and I will almost immediately write a pile of code to avoid having to do boring crap like that, even with copilot.

I have not and will not ever use AI generated code that I don’t thoroughly understand. If you properly understand the code you’re committing there shouldn’t be any damage. And beyond AI you should never commit code that you don’t properly understand unless it’s a throw away project.

I’ve run into that exact issue with copilot (deleting my tests). It is infuriating.

I don’t think I’d trust it to refactor code for me, not for anything important. I’d need to completely understand both the initial state and the result on a statement-by-statement level to be confident the result wasn’t secretly garbage and at that point I might as well write everything myself.

If I designed the schema it is most certainly going to be structured. Unstructured databases are awful.

So you’re arguing that “Object oriented” shouldn’t apply to languages that are oriented around objects?

Of course, but OOP is typically about putting methods on classes, inheritance of behaviour etc.

You’re referring to one subtype of OOP. That may be what most people mean when they say OOP, but that doesn’t make it correct. Object-oriented programming is programming with objects, which does not require inheritance or classes.

I’ve done a little bit of Python in the past, the biggest thing being an automation task that borderline became an app. I certainly can imagine using it for scripts, though I default to bash because that’s almost always available but TBH mostly because inertia. Beyond that my default is Go because inertia (and I love Go). I watched a video by the Primeagen (on YT) - in his view, Rust is better for text/data pipelines and CLI tools. Being very familiar with Go and not at all familiar with Rust, that’s an interesting take because honestly writing a CLI in Go is kind of meh.

so you have to catch all exceptions then do extra work to tell what the specific situation is

That’s horrifying. That’s a solid reason to avoid Python like the plague.

For references within a scope, you’re probably right. For references that cross scope boundaries (i.e. function parameters), they necessarily must consume memory (or a register). Passing a parameter to a function call consumes memory or a register by definition. If a function call is inlined, that means its instructions are copy-pasted to the call location so there’s no actual call in the compiled code.

Making good UX is fucking hard. I say UX because making it good is really about the user’s experience, not graphic design. An ugly front end can be good if it’s intuitive and easy to use. But a visually gorgeous front end will still be garbage if it’s clunky and confusing.

It’s really something you have to experience to fully understand. Ultimately it comes down to this: front ends have to deal with people, backends only have to deal with computers. So backends can be cleanly organized and well structured. Applying backend design principles to a front end will get you a CRUD interface - something that’s usable but no one really wants to use.

I’m a cishet white dude so I experience effectively zero discrimination directed at me, but I am on the spectrum.

I guess basically everyone I regularly interact with either is also on the spectrum or has intense interests regardless, or is used to people like that. Though TBF I have learned to not get intense if I’m in public talking to random strangers. But if someone asks me a question like, “how do computers work”, I will answer at great length.

If my IQ was higher than my body weight I’d be the smartest person on the planet…

Edit: I was thinking lbs, that makes a lot more sense in kg.

I’d stop being awkward if I could but I wouldn’t give up my intense interests. You?

I think the word you want is minutiae?