[theplumber]

I call it BS. When you are hitting real scalability issues that the AI can no longer help you are already a successful business. The non technical founder will not know about async message passing but will ask the AI why the site is loading so slowly and sure enough the AI is able to implement caching and various mechanism to improve the performance and observability. You are hitting a wall when you do novel stuff (I.e a special search engine) but something like Facebook which is more or less a CRUD app is not a problem at all. And this is the case with Today’s AI systems(GPT Sol, Kimi K3 etc).

I can’t imagine what models will be able to do next year, especially the open weights ones that are not nerfed for economic or other reasons(I.e Fable saga)

[RugnirViking]

Have you ever tried to get an LLM agent to improve performance in a complex system? It's not good at it at all, it doesn't have a very scientific mindset about it, loves to do premature optimisation and "fancy tricks" while ignoring/missing glaring issues/gains - I'm sure it could be taught to be more methodical (verify what is actually slow before attempting a fix) but it's anything but right now.

Even if you walk it through the process, it also has terrible intuition about what time certain things "should" take - dismissing the possibility of massive speedups because it thinks some number is normal etc

[lanstin]

I thought the model was the one person company with enough usage to be worth 1 billion USD. Badly designed systems can hit bottle necks at like a few thousand DB calls per second which a well designed system can handle on one container. Getting those new features adding to table width or SQL length (or document nesting if you are going that route) with each new feature, I feel the company with a few experts will be at an advantage. Like the old beating the averages essay on using lisp. More smart flexibility wins in the marketplace.