AWS Certified AI Practitioner AIF-C01 Practice Question

Retrieval-Augmented Generation first looks up the most relevant passages from an external knowledge source-such as an indexed collection of company documents-at inference time. It then injects those retrieved snippets into the prompt so the foundation model can generate an informed answer using that fresh context. Because the knowledge is supplied dynamically, no additional model training, pruning, or model chaining is required. The other options describe full fine-tuning, parameter pruning for cost reduction, or dividing work across several models; none of those approaches capture the defining characteristic of RAG, which is real-time retrieval of external information to augment the model's response.