Your question is Fine-Tuning vs RAG Trade-offs. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
Explain the trade-offs between fine-tuning a model versus using a retrieval-augmented approach for domain-specific knowledge at Anduril.
Compare both approaches for factual domain knowledge, changing documentation, proprietary data, and operational safety. Address quality, freshness, training and inference cost, latency, data governance, hallucination, prompt injection, and evaluation. Recommend a choice or hybrid design and explain how you would validate it offline and online.