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ML Academy

RAG and agents

Interview question

  • stafflevel
  • 25 minsuggested time
  • 3Applied AI, ML engineer, Data scientist

A legal-operations team asks for an assistant that answers questions over a set of about 300-page contract bundles. A vendor demo simply pastes the whole bundle into a long-context model. Engineering wants retrieval. How do you decide between long context, RAG, or a combination, and what would you put in the decision record?

Tests: Architecture choice between long-context prompting and retrieval: cost per query, latency, accuracy on position and multi-document reasoning, caching, update patterns, and evaluation-driven decision making.

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