I thought that software engineers were supposed to do, you know, engineering - solving hard problems, dealing with uncertainty.
But you might be right, engineering around the difficult LLM primitive might be a task which is just too hard for your typical software engineer, as you said, they want predictability, hand holding, determinism, most are unable to deal with the real world which is not a spherical cow in a vacuum. So I guess they can stick to simple very well understood primitives like EC2 or Postgres and leave dealing with LLMs for others.
The most well paid people in the industry brought us here. And "here" is very much as fuzzy as last year with better harnessing towards the local optima. And I say local optima because even the perceived capabilities have slowed down, nevermind the benchmark numbers which are in aggrement.
The best paid engineers in the world, with almost no practical budget limit, still deliver shoddy quality software with AI. Is that not fact? And if it is what does that say for the rest of us.
You are allowed to believe. I'm still waiting for the beneficial results, not only those that benefit griefters, hackers and scammers. AI has been a huge boon there.
Reality will materialize and markets will redress hopefully once they go public. Which they very much seem to be hesitant to do right now.
> I would expect better results than what we have today.
Not sure what your baseline was, if you said 10 years ago "in 2026 you'll be able to describe an app into the microphone, and the computer will write by itself in one day 50k lines of code to implement it, in a language and tech stack of your choosing, costing $200, and it will sort-of-work, and it will be at least as good as a junior-level programmer writing it from the same requirements in 3 months", most people would have said "implausible, that's at least 50 years away"
Yes, it is very impressive what they can do by recycling copyrighted material. They are more impressive for me when they are not used in agentic contexts. Though that doesn't sell hype anymore to inflate valuation.
For more than a year now I was renting a limited GPU server for ~300$/month to learn, experiment, research and build internal tooling around open weight models. Thinking they are tools with potential and buying the exaggerated marketing are different things.
My history of comments on HN lands often on both providing what I believe to be my insights working with LLMs and calling out exaggerations, stupid terms of service, and the other mishaps in the field. You are free to browse them if you'd like to see my broader opinion.
But you might be right, engineering around the difficult LLM primitive might be a task which is just too hard for your typical software engineer, as you said, they want predictability, hand holding, determinism, most are unable to deal with the real world which is not a spherical cow in a vacuum. So I guess they can stick to simple very well understood primitives like EC2 or Postgres and leave dealing with LLMs for others.