A travel-booking assistant built as a Foundry agent needs to tell customers today's lowest fare for a specific flight route. Fares change by the minute and the airline exposes a live pricing API. Embedding a snapshot of prices into the system prompt would go stale within hours. What is the best way to keep the assistant's fare quotes current?
Select an answer to reveal the explanation.
Short Explanation
Picture the assistant as a travel agent who could either memorize yesterday's price sheet or pick up the phone and check with the airline right now. Fares move by the minute, so anything baked in ahead of time, whether it is retrained overnight, refreshed once each morning, or just crammed into a bigger prompt, is already out of date the moment a customer asks. None of those approaches change the fundamental problem: the number was captured earlier and the world has moved on since then. What actually works is giving the assistant a live connection it can use mid-conversation, a tool it calls to reach the airline's own pricing system and read back whatever the price is at that exact second. That is the only option here where the answer is guaranteed to be current no matter when the customer asks, because it is not relying on anything written down in advance.
Full Explanation
The correct answer is C. Registering the airline's pricing API as a tool the agent can call lets the assistant fetch the actual current fare at the moment a customer asks, so the answer reflects live pricing rather than a snapshot that grows stale within minutes. Option A is incorrect because retraining a model nightly still leaves the assistant working from the previous day's numbers for the entire following day, which does not solve a problem that changes minute to minute. Option B is incorrect because a morning manual update still goes stale as soon as prices shift later that day, and it depends on someone remembering to do it. Option D is incorrect because a larger context window only lets the model hold more text at once; it does not make old fare data current, it just means more stale numbers fit in the prompt. Tool calling is the mechanism built for exactly this situation: instead of baking facts into the model or the prompt, the agent reaches out to a live system during the conversation and reads back a fresh result, which is the only one of these four options that actually guarantees the quoted fare is current.