this post was submitted on 24 May 2025
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I've been think about this for a while. Consider how quick LLM's are.
If the amount of energy spent powering your device (without an LLM), is more than using an LLM, then it's probably saving energy.
In all honesty, I've probably saved over 50 hours or more since I starred using it about 2 months ago.
Coding has become incredibly efficient, and I'm not suffering through search-engine hell any more.
Edit:
Lemmy users when someone uses AI: noooo, you can't generate helpful answers to your questions which cost a tenth of a cent worth of electricity.
Also Lemmy users when they see someone consuming the electric power of an entire nuclear power plant just to play Doom The Dark Ages on their $20,000 PC: neat!
Just writing code uses almost no energy. Your PC should be clocking down when you're not doing anything. 1GHz is plenty for text editing.
Does ChatGPT (or whatever LLM you use) reduce the number of times you hit build? Because that's where all the electricity goes.
What kind of code are you writing that your CPU goes to sleep? If you follow any good practices like TDD, atomic commits, etc, and your code base is larger than hello world, your PC will be running at its peak quite a lot.
Example: linting on every commit + TDD. You'll be making loads of commits every day, linting a decent code base will definitely push your CPU to 100% for a few seconds. Running tests, even with caches, will push CPU to 100% for a few minutes. Plus compilation for running the app, some apps take hours to compile.
In general, text editing is a small part of the developer workflow. Only junior devs spend a lot of time typing stuff.
Anything that's per-commit is part of the "build" in my opinion.
But if you're running a language server and have stuff like format-on-save enabled, it's going to use a lot more power as you're coding.
But like you said, text editing is a small part of the workflow, and looking up docs and browsing code should barely require any CPU, a phone can do it with fractions of a Watt, and a PC should be underclocking when the CPU is underused.
Except that half the time I dont know what the fuck I'm doing. It's normal for me to spend hours trying to figure out why a small config file isnt working.
That's not just text editing, that's browsing the internet, referring to YouTube videos, or wallowing in self-pity.
That was before I started using gpt.
It sounds like it does save you a lot of time then. I haven't had the same experience, but I did all my learning to program before LLMs.
Personally I think the amount of power saved here is negligible, but it would actually be an interesting study to see just how much it is. It may or may not offset the power usage of the LLM, depending on how many questions you end up asking and such.
It doesn't always get the answers right, and I have to re-feed its broken instructions back into itself to get the right scripts, but for someone with no official coding training, this saves me so much damn time.
Consider I'm juggling learning Linux starting from 4 years ago, along with python, rust, nixos, bash scripts, yaml scripts, etc.
It's a LOT.
For what it's worth, I dont just take the scripts and paste them in, I'm always trying to understand what the code does, so I can be less reliant as time goes on.
Are you using your PC less hours per day?
Yep, more time for doing home renovations.