How can large language models be incorporated into recommendation systems? Outline use cases such as item/user metadata enrichment, query and intent understanding, cold-start handling, generative retrieval, semantic reranking, explanations, and multi-modal recommendations. Propose architectures (LLM as feature generator, reranker, or agent/orchestrator), describe online/offline placement and caching strategies, address latency/cost constraints and safety/content filtering, and define offline and online evaluation plans (A/B tests, guardrails, feedback loops).