For me, it is a glorified auto-complete function. Could definitely live without it.
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Same for me, but that glorified auto complete helps a lot.
Hell yea. Our unit test coverage went way up because you can blow through test creation in second. I had a large complicated migration from one data set to another with specific mutations based on weird rules and GPT got me 80% of the way there and with a little nudging basically got it perfect. Code that would've taken a few hours took about 6 prompts. If I'm curious about a new library I can get a working example right away to see how everything fits together. When these articles say there's no benefit I feel people aren't using these tools or don't know how to use them effectively.
Yeah, it's useful, you just gotta keep it on a short leash, which is difficult when you don't know what you're doing
Basically, it's a useful tool for experienced developers that know what to look out for
We always have to ask what language is it auto-completing for? If it is a strictly typed language, then existing tooling is already doing everything possible and I see no need for additional improvement. If it is non-strictly typed language, then I can see how it can get a little more helpful, but without knowledge of actual context I am not sure if it can get a lot more accurate.
Good devs gain little.
I gain a lot.
Its basically a template generator, which is really helpful when you're generating boilerplate. It doesn't save me much if any time to refactor/fill in that template, but it does save some mental fatigue that I can then spend on much more interesting problems.
It's a niche tool, but occasionally quite handy. Without leaps forward technically though, it's never going to become more than that.
Just beware, sometimes the AI suggestions are scary good, some times they’re batshit crazy.
Just because AI suggests it, doesn’t mean it’s something you should use or learn from.
Generative AI is great for loads of programming tasks like helping create regular expressions or syntax conversions between languages. The main issue I've seen in codebases that rely heavily on generative AI is that the "solutions" often fix today's bug while making future debugging more difficult. Generative AI makes it easy to go fast in the wrong direction. Used right it's a useful tool.
While I am not fond of AI, we do have access to it at work and I must admit that it saves some time in some cases. I'm not a developer with decades of experience in a single language, so something I am using AI to is asking "Is it possible to do a one-liner in language X where it does Y?" It works very well and the code is rarely unusable, but it is still up to my judgement whether the AI came up with a clever use of functions that I didn't know about or whether it crammed stuff into a single unreadable line.
It introduced me to the basics of C# in a way that traditional googling at my previous level of knowledge would've made difficult.
I knew what I wanted to do and I didn't know what was possible or how to ask without my question being closed as a duplicate with a link to an unhelpful post.
In that regard, it's very helpful. If I had already known the language well enough, I can see it being less helpful.
Great for Coding 101 in a language I'm rusty with or otherwise unfamiliar.
Absolutely useless when it comes time to optimize a complex series of functions or upgrade to a new version of the .NET library. All the "AI" you need is typically baked into Intellisense or some equivalent anyway. We've had code-assist/advice features for over a decade and its always been mid. All that's changed is the branding.
This is what I've used it for and it's helped me learn, especially because it makes mistakes and I have to get them to work. In my case it was with Terraform and Ansible.
Everyone keeps talking about autocomplete but I've used it successfully for comments and documentation.
You can use vs code extensions to generate and update readme and changelog files.
Then if you follow documentation as code you can update your Confluence/whatever by copy pasting.
I also use it a lot for unit tests. It helps a lot when you have to write multiple edge cases, and even find new one at times. Like putting a random int in an enum field (enumField = (myEnum)1000), I didn't knew you could do that...
I'm a penetration tester and it increases my productivity a lot
Penetration tester, huh? Sounds like a fun and reproductive job.
But it can be very HARD sometimes
I mainly use AI for learning new things. It’s amazing at trivial tasks.
so it's a vector of attack?
My main use is skipping the blank page problem when writing a new suite of tests—which after about 10 mins of refactoring are often a good starting point
No shit. Senior devs have been saying this the whole time. AI, in its current form, for developers, is like handing a spatula to a gourmet chef. Yes it is useful to an extremely small degree, but that’s it…for now.
A convoluted spatula that sometimes accidentally cuts what your cooking im half instead of flipping it and consumes as much power as the entirety of Japan.
And yet, higher ups continue to lay off more devs because AI "is the future".
The writer has a clear bias and a lack of a technical background (writing for Techies.com doesn't count) .
You don't have to look hard to find devs saving time and learning something with AI coding assistants. There are plenty of them in this thread. This is just an opinion piece by someone who read a single study.
if you are already competent and you are aware that it doesn't necessarily give you correct information, the it is really helpful. I know enough to sense when it is making shit up. Also it is, for some scenarios, faster and easier then looking at a documentation. I like it personally. But it will not replace competent developers anytime soon.
Places GPT-based "AI" next to flying cars
Flying cars exist, they’re just not cost effective. AFAICT there’s no GPT that is proficient at coding yet.
It's a lot easier to access ChatGPT than it is to access a flying car
The more people using chatgpt to generate low quality code they don't understand, the more job safety and greater salary I get.
Every now and then, GitHub Copilot saves me a few seconds suggesting some very basic solution that I am usually in the midst of creating. Is it worth the investment? No, at least not yet. It hasn't once "beaten" me or offered an improved solution. It (more frequently than not) requires the developer to understand and modify what it proposes for its suggestions to be useful. Is is a useful tool? Sure, just not worth the price yet, and obviously not perfect. But, where I'm working is testing it out, so I'll keep utilizing it.
lol Uplevel's """full report""" saying devs using Copilot create 41% more bugs has 2 pages and reads like a promotional material.
you can download it with a 10 minute email if you really want to see for yourself.
just some meaningless numbers.
It's just fancier spell check and boilerplate generator
It's great as essentially a StackOverflow that I can talk to in real time. But as with SO, I've still got to figure out what pieces are legit and where they go.
I honestly stopped using it after a week
Who are those guys they keep asking this question over and over ? And how are they not able to use such a simple tool to increase their productivity ?
Yep, by definition generative AI gets worse the more specific you get. If you need common templates though, it’s almost as good as today’s google.
… which is not a high bar.
I get more benefit from a good IDE that helps me track libraries, cars, functions, grammar checks my code, offers a pop-up with params and options....
I don't needcode I would grade as a D- from an AI. Most of what I write comes from my code closet anyway. I have skeleton code for so much, and I trust my old code more than AIs new code
I partly disagree, complex algorithms are indeed a no, but for learning a new language it is awesome.
Currently learning Rust and although it cannot solve everything, it does guide you with suggestions and usable code fragments.
Highly recommended.
Garbage in garbage out is how they all work if you give it a well defined prompt you can get exactly what you want out of it most of the time but if you just say fix this problem it’ll just fix the problem ignoring everything else
I’m shocked. There must be an error in this analysis. /s
Maybe engage an AI coding assistant to massage the data analysis lol