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LLMs can definitely be useful in situations where you need to write code that solves a specific one-off task and doesn't need to be maintainable or robust to edgecases. Some prompts where LLMs saved me 15 minutes or so of work:

• "Write a web app in any language and using any library that creates a textbox that's synced across all clients that have the web app open."
• "Write a python PIL program that iterates over the pixels in an image... Now make it a command line tool with argparse that takes the image path as input"

That would be correct for me. If i know what question to ask i also know how to solve it. And its not good at solving beacuse it requires precision which is something that generative ai inherently dont poses. But its also why i think gen ai will reduce the number of artist very significantly beacuse art just need to be good enough. Or to be precise democrtize art. No longer will you need to have a band of 5 pepole and a smidge talent to make a metal song for yourself. Likewise if you want a sick reasonably specific wallpaper for your screen. Now idea will be good enough for a good enough result.

I got fed up with my boss coming around and saying “would this work go any faster with AI?”, but now I’ve become AI-Positive and I take her bits of technical debt we’d like to clean up saying “we could use AI on this!”.

It helps me as autocomplete, but that’s about it. The increase in productivity is negligible. The problem I have is suddenly feeling dependent on it. It’s like with navigation software. We rely on it so much, suddenly we can’t navigate our way out of a paper bag when it’s not around. There’s something unsettling about having the floor pulled out from under you like that.

If I was simply someone trying to get a job done and drone through the day, sure, it’s probably fine. But I’m someone that needs to know and understand everything I put into my commits, and I actually enjoy coding.

One of the common uses I've heard is for generating boiler plate code. I have two thoughts on this. First, you actually have to understand what the boiler plate code is doing for it to be of any value. Second, there are already solutions for this that work just as well or better. Most of the major IDE's either support code templates or have extensions for that. You just have to be willing to take the time to create templates. I use Resharper with Visual Studio for this all the time.

I tried copilot free for a month and was not that impressed.

It doesn't do anything for me. It's good for simple code that I could've written myself in the time it takes me to make sure that what it generates is what I needed.

Absolutely has been my experience. It's actually slowed me down because of the slop it tends to throw in there as part of the hallucinations.

The article mentioned in the screenshot.

I used replit for education. At some point they added ai assistance. It was like pair programming with someone who is over eager and doesn't know why you're dying things.

When I'm teaching code, I don't need ai to finish my circle calculation program before I've explained the first line to students.

I don't know, I use GH copilot every day. Not to generate whole blocks of code but as autocomplete. It more often than not can finish my sentence for me. It's makes wrong assumptions some times but it most definitely saves me time. I was just using an IDE today not set up for copilot and it made me realize how much I miss it when its gone.

Honestly, it’s GREAT for replying to bull shit business emails.

People should be using it to get their test suite correct > 90% first before attempting to put any ML generated code into production

Been using copilot and another smaller AI model for hobby projects. Both of them slowed me down as much as they helped me with my code.

Now I've switched to supermaven free tier, and it's actually net positive for me.

It's not like it's writing whole functions for me, but it's actually quite context sensitive when it comes to defining functions and using them with the same parameters and things like that. I won't say I am 50% faster, but I could easily attribute a 30% development boost to it. Now mind you, for bug fixes and bug prevention that's back down to a 5% boost in speed, but that's still a net positive, so I'll take that.

As a hobbyist with no production-environment or critical coding projects, Google Gemini has been great for generating a starting point for Arduino projects if I otherwise don't know how to get going.