Question

You are designing a customer-support generative AI application for an e-commerce company. Business requirements state that the assistant must: (1) answer general product policy questions, (2) look up a specific customer's live order status by order ID, and (3) initiate refund requests that require writing to an internal transactional system. The company wants a single conversational entry point that decides which capability to use per turn. Which application design best satisfies these requirements?

Accepted Answer

An agent that uses an LLM to reason about intent and select among tools: a RAG retriever over policy documents, a read-only order-lookup function, and a refund-submission function that writes to the transactional system.

Answer

A single large prompt that concatenates the policy documents, the order database schema, and refund instructions, relying on the LLM to generate answers, order statuses, and refund confirmations directly from context.

Answer

A fixed sequential chain that always retrieves policy documents, then queries order status, then submits a refund on every user turn regardless of the question asked.

Answer

A fine-tuned model trained on historical support transcripts, deployed without external tools, that memorizes policies, order data, and refund outcomes.