An answer no longer tells you who did the thinking behind it.

Struggle isn't wasted effort; it's what turns information into understanding, and AI lets you skip it.

We used to test understanding by pushing back, but now the pushing back can be outsourced too.

In 1913, a mathematician in Cambridge opened a letter from a stranger in Madras. It was full of results, pages of them, with almost no explanation attached.

Some looked like the work of a crank. Some looked impossible. G.H. Hardy, a very serious mathematician of his generation, later said the letter contained results that "must be true, because if they were not true, no one would have had the imagination to invent them."

The stranger was Srinivasa Ramanujan. He was an obscure clerk with almost no formal training. He would go on to become one of the most naturally gifted mathematicians who ever lived. He even inspired a book and movie called The Man Who Knew Infinity.

But the strangest thing about him wasn't that he was brilliant. It's that he so often seemed to arrive at the answer before he could explain how he got there. The proof came second, if it came at all.

What really strikes me is that this sequence, answer first and explanation later, is exactly what happens every time we use a large language model.

A Book That Wouldn't Explain Itself

Here's the part of Ramanujan's story that complicates things.

At 16, he got hold of an old book, a cram........

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