[h33t-l4x0r]

I think this is right on, and the things that LLM excels at (react components was your example) are really the things that there's just such a ridiculous amount of training data for. This is why LLMs are not likely to get much better at code. They're still useful, don't get me wrong, but they 5x expectations needs to get reined in.

[danielbln]

A breadth and depth of training data is important, but modern models are excellent at in-context learning. Throw them documentation and outline the context for what they're supposed to do and they will be able to handle some out-of-distribution things just fine.

I would love to see some detailed failure cases of people who used agentic LLMs and didn't make it work. Everyone is asking for positive examples, but I want to see the other side.