Question

You are building a customer support agent in Azure AI Foundry Agent Service. Users interact with the agent across multiple sessions over several days, and the business requires that the agent recall prior conversation context (previous questions, order numbers, and stated preferences) within an ongoing support case without you having to manually re-send the entire history in each request. Which approach should you use to persist and manage conversational context across turns?

Accepted Answer

Create a persistent thread per support case and add messages to that thread so the Agent Service maintains conversation state across turns and sessions.

Answer

Increase the model's max token context window and resend the full transcript with every request to guarantee the model sees all prior turns.

Answer

Store each user message in an Azure AI Search vector index and rely on retrieval grounding to reconstruct the full conversation on every call.

Answer

Deploy a separate agent instance for each user so that each agent statelessly remembers only that user's data in the deployment configuration.