How can someone have a skill issue with AI? Isn’t the whole point that it does everything for me? Never understood this.
People are like “you’re gonna get left behind!” and I’m like. How could I be left behind by the magic machine that does everything for me? I’ll just start using it one day and be just as good as everyone else because that’s explicitly how they are designing the software to be used, right?
I think you do have a point. I think the overarching problem with discussions about “AI” is that people rarely refer to the same things when they talk about it and they end up talking past each other. There is a difference between using a custom harness with (a) carefully optimized local LLM(s) and other models you glue on top yourself for other-than-text tasks and using server-side models with a ready-made CLI and UI served to you on a golden platter with all processing being done elsewhere. “You’re gonna get left behind” is not the argument here. If the problem is “the code is too complicated”, that is a style issue that can be mitigated. It’s not set in stone. Sure, there are many problems with LLMs and ML models in terms of where they source their training data from and the environmental impact of data centers. I’ve also had my fair share of literal slop pop out. Some problems are just there and won’t go away (yet), but some problems are a choice, whether you know it or not.
I also think that some people like the idea of being on the designing end rather than just being on the using end. Why stop at skill.md? Why not post-train your model on your own code, style and preferences? I’ve trained a tiny model on a small subset of data I may legally use because it’s… fun. It’s my hobby. I just tinker around with it. The model itself is absolute poop, because it’s super small. But it works. I also locally rebuilt llama.cpp with a TheRock ROCm build for better support for my graphics card and got a very significant performance improvement. It doesn’t even need to be useful in any meaningful way (it often is anyway), as long as I got fun understanding how it works.
“I’ll just start using it one day and be just as good as everyone else because that’s explicitly how they are designing the software to be used, right?”. Yes. You’re still going to need to be capable enough to express what you want with precision, but if you can do that, you’re absolutely right, especially considering future models. But maybe you don’t want to be absolutely dependent on big companies serving you those models.
It’s with anything. It’s a tool. Like if you buy a synthesizer but you don’t press any buttons and complain you don’t get the sound you want.
Like go on a image generation site and say “dog” sure you’ll probably get a picture of a dog but it’s probably not the breed, color or setting or pose you want. If you are more spesific in your prompt you’ll get a more spesific thing.
Skills etc are just prompts. And with better prompts you’ll get better results. It’s very simple
How can someone have a skill issue with AI? Isn’t the whole point that it does everything for me? Never understood this.
People are like “you’re gonna get left behind!” and I’m like. How could I be left behind by the magic machine that does everything for me? I’ll just start using it one day and be just as good as everyone else because that’s explicitly how they are designing the software to be used, right?
I think you do have a point. I think the overarching problem with discussions about “AI” is that people rarely refer to the same things when they talk about it and they end up talking past each other. There is a difference between using a custom harness with (a) carefully optimized local LLM(s) and other models you glue on top yourself for other-than-text tasks and using server-side models with a ready-made CLI and UI served to you on a golden platter with all processing being done elsewhere. “You’re gonna get left behind” is not the argument here. If the problem is “the code is too complicated”, that is a style issue that can be mitigated. It’s not set in stone. Sure, there are many problems with LLMs and ML models in terms of where they source their training data from and the environmental impact of data centers. I’ve also had my fair share of literal slop pop out. Some problems are just there and won’t go away (yet), but some problems are a choice, whether you know it or not.
I also think that some people like the idea of being on the designing end rather than just being on the using end. Why stop at skill.md? Why not post-train your model on your own code, style and preferences? I’ve trained a tiny model on a small subset of data I may legally use because it’s… fun. It’s my hobby. I just tinker around with it. The model itself is absolute poop, because it’s super small. But it works. I also locally rebuilt llama.cpp with a TheRock ROCm build for better support for my graphics card and got a very significant performance improvement. It doesn’t even need to be useful in any meaningful way (it often is anyway), as long as I got fun understanding how it works.
“I’ll just start using it one day and be just as good as everyone else because that’s explicitly how they are designing the software to be used, right?”. Yes. You’re still going to need to be capable enough to express what you want with precision, but if you can do that, you’re absolutely right, especially considering future models. But maybe you don’t want to be absolutely dependent on big companies serving you those models.
It’s with anything. It’s a tool. Like if you buy a synthesizer but you don’t press any buttons and complain you don’t get the sound you want.
Like go on a image generation site and say “dog” sure you’ll probably get a picture of a dog but it’s probably not the breed, color or setting or pose you want. If you are more spesific in your prompt you’ll get a more spesific thing.
Skills etc are just prompts. And with better prompts you’ll get better results. It’s very simple