I found that "not interested" didn't work for me, that I had to explicitly state what I was interested in and only then did my suggestions become relevant. It will at times revert to slop and then I have to go through the process all over again.
| AI is orders of magnitude more useful and transformative than Facebook was in 2005
It better be, it's taken over 40000x the funding.
The question is not whether AI is useful, the question is whether it's useful enough relative to the capital expectations surrounding it. And those expectations are higher than anything the world has ever seen.
With regard to Etsy, hand-made crafts don't scale so a VC-backed startup around them was never going to be able to resist this. Only hope would be a highly moderated and curated Craigslist-style website that was happy to pay the bills, pay some salaries and keep the lights on while maintaining integrity.
Craft fairs, though, no excuse or reason. There should not be profit maximizing at local craft fairs. They're a bellwether for the degradation of culture.
I use AI as a rubber duck to research my options, sanity-check my code before a PR, and give me a heads up on potential pain points going forward.
But I still write my own code. If I'm going to be responsible for it, I'm going to be the one who writes it.
It's my belief that velocity up front always comes at a cost down the line. That's been true for abstractions, for frameworks, for all kinds of time-saving tools. Sometimes that cost is felt quickly, as we've seen with vibe coding.
So I'm more interested in using AI in the research phase and to increase the breadth of what I can work on than to save time.
Over the course of a project, all approaches, even total hand-coding with no LLMs whatever, likely regress to the mean when it comes to hours worked. So I'd rather go with an approach that keeps me fully in control.
My question is why use AI to output javascript or python?
Why not output everything in C and ASM for 500x performance? Why use high level languages meant to be easier for humans? Why not go right to the metal?
If anyone's ever tried this, it's clear why: AI is terrible at C and ASM. But that cuts into what AI is at its core: It's not actual programming, it's mechanical reproduction.
Which means its incapabilities in C and ASM don't disappear when using it for higher-level languages. They're still there, just temporarily smoothed over due to larger datasets.
I got the right answer but it was so easy I went in with doubt I had done it right.
Which I understand is my issue to work on, but if I were interviewing, I'd ask candidates to verbalize or write out their thought process to get a sense of who is overthinking or doubting themselves.
Easily worth the extra money alone.