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
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…
Yeah. I’ve found new logic by asking GPT for improvements on my code or suggestions.
I cut the size of a function in half once using a suggested recursive loop and it blew my mind.
Feels like having a peer to do a code review on hand at all times.
I’m a penetration tester and it increases my productivity a lot
so it’s a vector of attack?
I mainly use AI for learning new things. It’s amazing at trivial tasks.
as a dental assistant I can also confirm that AI has increased my productivity, checks notes, by a lot.
Claude is my coding mentor. Wouldn’t want to work without it.
I run code snippets by three or four LLMs and the consensus is never there. Claude has been the worst for me.
Which one has been best? I’m only a hobbyist, but I’ve found Claude to be my favorite, and the best UI by a mile.
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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.
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.
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.
For me, it is a glorified auto-complete function. Could definitely live without it.
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.
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
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.
Feel the same way!
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.
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
And yet, higher ups continue to lay off more devs because AI “is the future”.
In my experience, most of the tech layoffs have been non-devs. PMs and Designers have been the hardest hit and often their roles are being eliminated.
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.
I honestly stopped using it after a week