RAG Interview Questions, issue 21, Jul 25, 2026

The GraphRAG Scaling Trap

Senior ML Engineer interview at Google, and the interviewer asks:

Your GraphRAG pipeline uses an LLM to extract entity-relationship triplets. It’s flawless in the demo. Now you’re ingesting 50K docs a week and your indexing bill is on fire. What did you trade away when you picked LLM extraction?

Don’t say: LLMs are more accurate than rule-based parsers, so it’s worth the cost.

The hidden trap where appending documents to a knowledge graph destroys your deduplication, and why senior engineers trade pure LLMs for a hybrid, tiered pipeline.

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