Code analysis firm sees no major benefits from AI dev tool when measuring key programming metrics, though others report incremental gains from coding copilots with emphasis on code review.
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.
Haha, yeah. It really loves to refactor my code to “fix” bracket list initialization (e.g. ListstringList= [];) because it keeps not remembering that the syntax has been valid for a while.
It’s newest favorite hangup is to incessantly suggest null checks without asking if it’s a nullable property that it’s checking first. I think I’m almost at the point where it’s becoming less useful to me.
You do realize that a very thorough manual is but a man bash away? Perhaps it’s not the most accessible source available, but it makes up for that in completeness.
I believe accessibility is the part that makes LLMs helpful, when they are given an easy enough task to verify. Being able to ask a thing that resembles a human what you need instead of reading through possibly a textbook worth of documentation to figure out what is available and making it fit what you need is fairly powerful.
If it were actually capable of reasoning, I’d compare it to asking a linguist the origin of a word vs looking it up in a dictionary. I don’t think anyone disagrees that the dictionary would be more likely to be fully accurate, and also I personally would just prefer to ask the person who seemingly knows and, if I have reason to doubt, then go back and double-check.
Here’s the manpage for bash’s statistics from wordcounter.net:
Perhaps LLMs can be used to gain some working vocabulary in a subject you aren’t familiar with. I’d say anything more than that is a gamble, since there’s no guarantee that hallucinations have not taken place. Remember, that to spot incorrect info, you need to already be well acquainted with the matter at hand, which is at the polar opposite of just starting to learn the basics.
I do try to keep the “unknown unknowns” problem in mind when I use it, and I’ve been using it far less as I latched on to how OOP actually works and built up the lexicon and my own preferences. I try to only ask it for high-level stuff that I can then use to search the wider (hopefully more human) internet more traditionally with. I fully appreciate that it’s nothing more than a very incredibly fancy auto-completion engine and the basic task of auto-complete just so happens to appear intelligent as it gets better and more complex but continues to lack any form of real logical thoughts.
Even with amazing documentation, it can be hard to find the thing you’re looking for if you don’t know the right phrasing or terminology yet. It’s easily the most usable thing I’ve seen come out of “AI”, which makes sense. Using a Language Model to parse language is a very literal application.
The person I replied to was talking about learning the basics of a language… This isn’t about searching for something specific, this is about reading the very basic introduction to a language before trying to Google your way through it. Avoiding the basic documentation is always a bad idea. Replacing it with the LLMed version of the original documentation probably even more so.
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.
Haha, yeah. It really loves to refactor my code to “fix” bracket list initialization (e.g.
List stringList = [];) because it keeps not remembering that the syntax has been valid for a while.It’s newest favorite hangup is to incessantly suggest null checks without asking if it’s a nullable property that it’s checking first. I think I’m almost at the point where it’s becoming less useful to me.
I learned bash thanks to AI!
For years, all I did was copy and paste bash commands. And I didn’t understand arguments, how to chain things, or how it connects.
You do realize that a very thorough manual is but a
man bashaway? Perhaps it’s not the most accessible source available, but it makes up for that in completeness.I believe accessibility is the part that makes LLMs helpful, when they are given an easy enough task to verify. Being able to ask a thing that resembles a human what you need instead of reading through possibly a textbook worth of documentation to figure out what is available and making it fit what you need is fairly powerful.
If it were actually capable of reasoning, I’d compare it to asking a linguist the origin of a word vs looking it up in a dictionary. I don’t think anyone disagrees that the dictionary would be more likely to be fully accurate, and also I personally would just prefer to ask the person who seemingly knows and, if I have reason to doubt, then go back and double-check.
Here’s the manpage for bash’s statistics from wordcounter.net:
Perhaps LLMs can be used to gain some working vocabulary in a subject you aren’t familiar with. I’d say anything more than that is a gamble, since there’s no guarantee that hallucinations have not taken place. Remember, that to spot incorrect info, you need to already be well acquainted with the matter at hand, which is at the polar opposite of just starting to learn the basics.
I do try to keep the “unknown unknowns” problem in mind when I use it, and I’ve been using it far less as I latched on to how OOP actually works and built up the lexicon and my own preferences. I try to only ask it for high-level stuff that I can then use to search the wider (hopefully more human) internet more traditionally with. I fully appreciate that it’s nothing more than a very incredibly fancy auto-completion engine and the basic task of auto-complete just so happens to appear intelligent as it gets better and more complex but continues to lack any form of real logical thoughts.
What about just reading the documentation?
Even with amazing documentation, it can be hard to find the thing you’re looking for if you don’t know the right phrasing or terminology yet. It’s easily the most usable thing I’ve seen come out of “AI”, which makes sense. Using a Language Model to parse language is a very literal application.
The person I replied to was talking about learning the basics of a language… This isn’t about searching for something specific, this is about reading the very basic introduction to a language before trying to Google your way through it. Avoiding the basic documentation is always a bad idea. Replacing it with the LLMed version of the original documentation probably even more so.