What turns an AI agent into a real product? (memory, MCP, GitHub Copilot, Cosmos DB)

Patty Chow explains what it takes to move an AI agent beyond a demo, focusing on “memory” as an architecture decision that affects cost, recall quality, and user experience, and demonstrating an MCP server running inside GitHub Copilot backed by Azure Cosmos DB.

Overview

• The short argues that agent memory isn’t a checkbox feature; it’s an architecture decision that impacts:
  • Cost
  • Recall quality
  • User experience
• Demonstration highlights a live MCP server running inside GitHub Copilot, with persistent memory backed by Azure Cosmos DB.
• The approach is positioned as a way to build production-ready AI agents on Azure using:
  • Persistent memory
  • Retrieval
  • Tool use
  • Model Context Protocol (MCP)
  • Azure Cosmos DB NoSQL API and vector search

Related link

• Cosmos DB Conf 2026 on-demand sessions playlist: https://aka.ms/CosmosConf26Playlist