[lewdev]

The way I see AI programming assistants is that it would help juniors be a bit more productive, but senior developers can do with out the assistant.

I've used Cody and Copilot and it just gets in the way because I know exactly what I need to write and neither really helped me.

[kshitij_libra]

Precisely. I think it helps with smaller/mundane tasks (that it has seen in its training), but the tasks that actually require a higher level reasoning and understanding of the bigger picture - are not something we can expect the current LLM's to do.

However as I was researching, there are a few interesting ideas in this space that might help these LLM's solve more complex problems in the future. Post here if interested: https://kshitij-banerjee.github.io/2024/04/30/can-llms-produ...

[theshrike79]

These are the cases where even senior developers should use AIs.

When I'm creating a CRUD API I know exactly what I want, I know exactly how it should look like.

Do I want to spend 15-30 minutes typing furiously adding the endpoints? No.

I can just tell Copilot to do it and check its work. I'll be done in 5 minutes doing something more engaging like adding the actual business logic.

[widgeyboy]

I agree with this mostly - but recently a bug was introduced into our app because of a copilot suggestion that wasn't checked thoroughly enough by the engineer (it suggested a property that was similarly named to another property but not the same).

Like you say, it makes the most sense repetitive or easy tasks.

[pdimitar]

> I can just tell Copilot to do it and check its work

Checking other entities' code is not trivial and very error-prone.

I get what you're saying but I have my doubts if me doing the whole work manually would be slower than asking an assistant + doing an extensive code review.

[TaylorAlexander]

Lately I have been using it to write print and logger statements. I type what I want as a sentence in a comment and then it handles all the special syntax characters. Given the error rate I’m not certain it saves time, but it is fun to play with.

[DoingIsLearning]

For seniors I think it depends on how much breadth you need. I find them very useful to explore/poke around new areas where I don't have domain knowledge. I agree that areas/problems that I worked in the past it just slows you down but as you move into more unknown territories they are kind of nice to have as a sparing partner.

[piva00]

Similar to my usage as well, it's a good start for unfamiliar territory to quickly get up to speed but you can hit its limits quite fast.

I've been toying around with embedded development for some art projects, it was invaluable to have a kickstart using LLMs to get a glimpse of the knowledge I need to explore, get some useful quick results but when I got into more complex tasks it just breaks down: non-compiling code, missing steps, hallucinations (even to variables that weren't declared previously), reformatting non-functioning code instead of rewriting it.

As complexity grows the tool simply cannot handle it, as you said it's a good sparing partner for new territory but after that you will rely on your own skills to move into intermediate/advanced stuff.

[eterevsky]

I find the ML completion used in Google codebase very useful. It knows the APIs that I'm going to use better than I do, and it also can infer how exactly I'm going to use them. So in my experience, it does make me more productive.