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Where RAG actually earns its keep

An honest sketch of when retrieval-augmented generation pulls weight, and when it's a workaround for a missing data model.

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RAG is one of the most over-prescribed AI patterns of the last two years. This piece pins down the conditions under which it pays off, the conditions under which it's a workaround, and how I evaluate the difference on real engagements.

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