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by torben-friis 148 days ago
I’m not particularly proAI but I struggle with the mentality some engineers seem to apply to trying.

If you read someone say “I don’t know what’s the big deal with vim, I ran it and pressed some keys and it didn’t write text at all” they’d be mocked for it.

But with these tools there seems to be an attitude of “if I don’t get results straight away it’s bad”. Why the difference?

5 comments

There isn't a bunch of managers metaphorically asking people if they're using vim enough, and not so many blog posts proclaiming vim as the only future for building software
I’d argue that, if we accept that AI is relevant enough to at least be worth checking, then dismissing it with minimal effort is just as bad as mindlessly hyping the tech.
You must be new here. "I use vim between", "you don't use vim, you use Visual Studio, your opinion doesn't count" is a thing in programming circles.
Internet commenters, sure.

It never broke into the workplace like measuring AI use among your employees. Nobody's asked me about how I've used vim keybinds to improve the company's growth in a performance review.

I don't understand how to get even bad results. Or any results at all. I'm at a level where I'm going "This can't just be me not having read the manual".

I get the same change applied multiple times, the agent having some absurd method of applying changes that conflict with what I say it like some git merge from hell and so on. I can't get it to understand even the simplest of contexts etc.

It's not really that the code it writes might not work. I just can't get past the actual tool use. In fact, I don't think I'm even at the stage where the AI output is even the problem yet.

>I don't understand how to get even bad results. Or any results at all. I'm at a level where I'm going "This can't just be me not having read the manual".

>I get the same change applied multiple times, the agent having some absurd method of applying changes that conflict with what I say it like some git merge from hell and so on. I can't get it to understand even the simplest of contexts etc.

That is weird. results have a ton of variation, but not that much.

Say you get a claude subscription, point it to a relatively self contained file in your project, hand it the command to run relevant tests, and tell it to find quick win refactoring opportunities, making sure that the business outcome of the tests is maintained even if mocks need to change.

You should get relevant suggestions for refactoring, you should be able to have the changes applied reasonably, you should have the tests passing after some iterations of running and fixing by itself. At most you might need to check that it doesn't cheat by getting a false positive in a test or something similar.

Is such an exercise not working for you? I'm genuinely curious.

> I'm at a level where I'm going "This can't just be me not having read the manual".

Sure it can, because nobody is reading manuals anymore :).

It's an interesting exercise to try: take your favorite tool you use often (that isn't some recent webshit, devoid of any documentation), find a manual (not a man page), and read it cover to cover. Say, GDB or Emacs or even coreutils. It's surprising just how much powerful features good software tools have, and how much you'll learn in short time, that most software people don't know is possible (or worse, decry as "too much complexity") just because they couldn't be arsed to read some documentation.

> I just can't get past the actual tool use. In fact, I don't think I'm even at the stage where the AI output is even the problem yet.

The tools are a problem because they're new and a moving target. They're both dead simple and somehow complex around the edges. AI, too, is tricky to work, particularly when people aren't used to communicating clearly. There's a lot of surprising problems (such as "absurd method of applying changes") that come from the fact that AI is solving a very broad class of problems, everywhere at the same time, by virtue of being a general tool. Still needs a bit of and-holding if your project/conventions stray away from what's obvious or popular in particular domain. But it's getting easier and easier as months go by.

FWIW, I too haven't developed a proper agentic workflow with CLI tools for myself just yet; depending on the project, I either get stellar results or garbage. But I recognize this is only a matter of time investment: I didn't have much time to set aside and do it properly.

I agree to a degree, but I am in that camp. I subscribe to alphasignal, and every morning there are 3 new agent tools, and two new features, and a new agentic approach, and I am left wondering, where is the production stuff?
So just like in the JavaScript world?
Well one could say that since it's AI, AI should be able to tell us what we're doing wrong. No?

AI is supposed to make our work easier.

Certainly, every tool is supposed to make our work easier or more productive, but that doesn't mean that every tool is intuitive or easy to learn to use effectively or even to use it at all.
Certainly, but aren't AI tools supposed to be intuitive and easy to use because we can communicate with them in natural language?

With VIM or Emacs I am supposed to know what Ctrl-X does. But with AI tools (ideally) I should be able to ask AI (in English) to edit the document for me?

Maybe the reason we can't do it that way is that, "We're not there yet"?

What you are doing wrong in respect to what? If you ask for A, how would any system know that you actually wanted to ask for B?
Honestly IMO it's more that I ask for A, but don't strongly enough discourage B then I get both A, B and maybe C, generally implemented poorly. The base systems need to have more focus and doubt built in before they'll be truely useful for things aside from a greenfield apps or generating maintainable code.
Some people shouldn't just be engineers in the first place, I guess.