alt Hacker NewsI've gone back and forth on this.
A couple of years ago LLM prompts really were incredibly cheap and falling in price. OpenAI's own models had fallen in cost by a factor of about 1000x since GPT-3.
They were also cheap because many of the things you might want to do with an LLM took in the order of a few thousands tokens, at most.
Then coding agents happened, and suddenly we had a reason to burn 100,000s or even millions of tokens on a single task. Stuff got expensive!
(Classic Jevon's paradox right there.)
It feels to me like that's trending back down again though. DeepSeek and Kimi are massively less expensive than OpenAI and Anthropic, and almost as useful.
OpenAI dropped the price of Luna by 80% the other day, and it's proving very capable of exploring codebases and generating quite competent code.
So I don't think advanced AI that can help debug and maintain software will stay out of the reach of most people for very long.
> So I don't think advanced AI that can help debug and maintain software will stay out of the reach of most people for very long.
But then what stops the upstream tools from doing exactly the same thing and getting the same speedups? I've certainly seen AI become a huge boon in my debugging experience for random user reports for example.
FWIW if we are talking about hyper personalized software like the OP, it's going to quickly go beyond "debug and maintain" and towards bigger issues like UX, ergonomics, features etc. And at that point, if the upstream is also being developed you will have differences between your personal visions and upstream
Is the answer at that point "accept whatever AI does"? That to me seems to clash with the entire premise of hyper-personalization which is where your vision is what matters not the AI's. Do you really want to get into the game of having opinions on design of every tool you use forever?