[fnordpiglet]

That’s not needle in a haystack.

I would note that LLMs handle this task better if you slice the two documents into smaller sections and iterate section by section. They aren’t able to reason and have no memory so can’t structurally analyze two blobs of text beyond relatively small pieces. But incrementally walking through in much smaller pieces that are themselves semantically contained and related works very well.

The assumption that they are magic machines is a flawed one. They have limits and capabilities and like any tool you need to understand what works and doesn’t work and it helps to understand why. I’m not sure why the bar for what is still a generally new advance for 99.9% of developers is effectively infinitely high while every other technology before LLMs seemed to have a pretty reasonable “ok let’s figure out how to use this properly.” Maybe because they talk to us in a way that appears like it could have capabilities it doesn’t? Maybe it’s close enough sounding to a human that we fault it for not being one? The hype is both overstated and understated simultaneously but there have been similar hype cycles in my life (even things like XML were going to end world hunger at one point).