all true for a single grep invocation, however a capable LLM can drive grep using similar terms (`grep (red|maroon|scarlet|crimson)`, moving the measure of similarity from embedding/indexing time to inference time. There's benefits to that.

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jdthedisciple 2 days ago | parent [-]

> red|maroon|scarlet|crimson

still doesn't include typo'ed variants for any of these

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ozkatz 2 days ago | parent [-]

but a good combination of prompt, harness and model will easily close that gap. a more advanced (but equivalent) form of grep could also offer fuzzy matching/levenshtein distance function to augment that.

	▲	everforward 2 days ago \| parent \| next [-]
		It will, but it does so by burning tokens. I'm sure you've also seen the output of an overly eager grep by an LLM. I think we're verging on the point where people will care more about the most token-efficient ways to do a task than the lowest human effort version. Humans are expensive, humans using half as many tokens are cheaper.
	▲	c-hendricks 2 days ago \| parent \| prev [-]
		This sounds like AOT vs JIT weights.