How do you take an AI agent from a working demo to a production-ready system? Marko Hotti and Madeline Egan walk through a practical framework to observe, evaluate, and optimize AI agents with Azure Cosmos DB. Explore the full repo: https://aka.ms/cosmos-travel-planner Watch the full series: https://aka.ms/CodeWithCosmosPlaylist
Learn how traces, evaluation suites, regression testing, and before-and-after metrics can help improve retrieval, latency, token usage, memory efficiency, and Azure Cosmos DB request unit consumption across the data, retrieval, memory, and LLM layers.
💻 GitHub repo: https://aka.ms/cosmos-travel-planner
▶️ Watch the full series: https://aka.ms/CodeWithCosmosPlaylist
Try Azure Cosmos DB for free: https://aka.ms/trycosmosfree
Learn how traces, evaluation suites, regression testing, and before-and-after metrics can help improve retrieval, latency, token usage, memory efficiency, and Azure Cosmos DB request unit consumption across the data, retrieval, memory, and LLM layers.
💻 GitHub repo: https://aka.ms/cosmos-travel-planner
▶️ Watch the full series: https://aka.ms/CodeWithCosmosPlaylist
Try Azure Cosmos DB for free: https://aka.ms/trycosmosfree