It's getting harder to find IDEs that properly boycott LLMs.
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Why wouldn't it?
I have used agentic coding tools to solve problems that have literally never been solved before, and it was the AI, not me, that came up with the answer.
If you look under the hood, the multi-layered percqptratrons in the attention heads of the LLM are able to encode quite complex world models, derived from compressing its training set in a which which is formally as powerful as reasoning. These compressed model representations are accessible when prompted correctly, which express as genuinely new and innovative thoughts NOT in the training set.
Would you show us? Genuinely asking
It’s happened now that a couple of times it pops out novel results. In computational chemistry, machine learned potentials trained with transformer models have already resulted in publishable new chemistry. Those papers are t out yet, but expect them within a year.