this post was submitted on 01 Oct 2023
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Maybe it is

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[–] [email protected] 70 points 1 year ago* (last edited 1 year ago) (1 children)

Isn't that basically how it works?

Just add an additional group of monkeys that aggressively hires and fires the others based on performance

Tada, machine learning

[–] kubijoe 10 points 1 year ago

It was the best of times, it was the blurst of times!

[–] [email protected] 50 points 1 year ago* (last edited 1 year ago) (3 children)

asks for password hashing

gets code that looks like password hashing, named like password hashing, but, without any of the hashing

[–] [email protected] 22 points 1 year ago

But it has better performance

[–] [email protected] 14 points 1 year ago
[–] [email protected] 3 points 1 year ago

but, without any of the hashing

Or it's something like unsalted MD4.

[–] [email protected] 20 points 1 year ago (1 children)

It generates the blurst of code!

[–] [email protected] 13 points 1 year ago (1 children)

I've been using copilot and find it's suggestions are perfectly cromulent.

[–] [email protected] 6 points 1 year ago

I turn to copilot whenever I need to embiggen my code

[–] [email protected] 13 points 1 year ago (3 children)

Tbh, copilot was probably the worst AI coding experience I've had. It actually made me less productive and made me question my competency as a programmer at the same time. Straight up did not have a good time. Use Cody or GPT-4 instead.

[–] starman 26 points 1 year ago (4 children)

It is designed for other purposes than GPT models. Next time try to use copilot as autocompletion, not to generate new code. It's excellent in that.

[–] [email protected] 10 points 1 year ago (1 children)

That's how I thought it was supposed to be used. It's "copilot" not "autopilot". I don't need nor want it to write whole functions for me.

[–] [email protected] 2 points 1 year ago (1 children)

Company ran a trial for it, and it worked really well for generating boilerplate code following our existing system design. Sometimes it makes mistakes, but during the trial it was a rare occurence

The company is giving it to us all for free next year, hope it doesn't negatively affect hiring though...

[–] [email protected] 3 points 1 year ago

The company is giving it to us all for free next year, hope it doesn't negatively affect hiring though...

Should be fine. No way they'll assume that the new technology is magic and over promise, under budget, and then start a company death spiral, before cashing out their stock options and doing the same somewhere else. I'm sure glad we don't see that all the time in tech. /s

[–] [email protected] 4 points 1 year ago (2 children)

That's how I was using it; I ended up spending as much time as I was saving going around and cleaning up after it and/or second guessing myself. Basically, because it only operates in the context of the file you're working in, it will suggest garbage half the time if you have to work with resources from other files.

[–] starman 7 points 1 year ago* (last edited 1 year ago)

From the docs:

GitHub Copilot analyzes the context in the file you are editing, as well as related files

Tho, I don't know if it allways been that way, maybe they added bigger context later

[–] Kwartel 3 points 1 year ago

If you have those other files open, it also picks those up. And lately it seems to follow imports too, I feel like

[–] [email protected] 12 points 1 year ago (2 children)

But the propaganda from GitHub said it was making devs 80%+/- more productive!

How could this have happened? /s

[–] [email protected] 7 points 1 year ago

it works well for me, mostly accurately guesses what I am trying to do, helps a ton with boilerplate code

[–] [email protected] 3 points 1 year ago

It was 55% for me. Higher baseline I suppose. <\s>

[–] [email protected] 12 points 1 year ago

Because we are the apes that wrote the code that copilot read.

[–] [email protected] 2 points 1 year ago

I’m not understanding the CoPilot hate. It’s an amazing tool if you are competent. Even when it gets it wrong it still saves me 90%+ of the typing then I just correct what it did differently than how I want it.

Boilerplate becomes a breeze and I work way better when I have something to iterate on rather than coming up with it from scratch. It lets me play with and test ideas way faster and sometimes even does it differently than I’d do it which leads to learning new things and/or looking at the problem in a different way. I don’t blindly follow its output, sometimes I reject it wholesale, sometimes I edit it, sometimes it’s literally exactly what I would have typed myself.