tee() splits a stream into two branches. It seems straightforward, but the implementation requires buffering: if one branch is read faster than the other, the data must be held somewhere until the slower branch catches up.
One of the criticisms about AI generated code is that it “just regurgitates everything on GitHub” but by construction, if the code is faster than what currently exists, then it can’t have been stolen and must be an original approach. Even if the explicit agentic nature of rustlearn makes it risky to adopt downstream, the learnings from how it accomplishes its extreme speed are still valuable.
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