[yahoozoo]

Yes, LLMs often generate coherent, structured, multi-paragraph responses. But this coherence emerges as a side effect of learning statistical patterns in data, not because the model possesses a global plan or explicit internal narrative. There is no deliberative process analogous to human thinking or goal formation. There is no mechanism by which it consciously “decides” to think 50 tokens ahead; instead, it learns to mimic sequences that have those properties in the training data.

Planning and long-range coherence emerge from training on text written by humans who think ahead, not from intrinsic model capabilities. This distinction matters when evaluating whether an LLM is actually reasoning or simply simulating the surface structure of reasoning.

[famouswaffles]

>But this coherence emerges as a side effect of learning statistical patterns in data, not because the model possesses a global plan or explicit internal narrative.

That's not true.

https://www.anthropic.com/research/tracing-thoughts-language...