Building an AI Travel Planner Locally with Azure Cosmos DB and AI-Assisted Development

This episode starts a series on building a production-style AI travel planning application with Azure Cosmos DB, beginning from a blank local folder and ending with a working app without an Azure subscription. It focuses on setting up a local Cosmos DB environment and using AI-assisted development tools in VS Code to design a data model, generate application code, create queries, and test locally.

■ Local development setup
- Starting the Azure Cosmos DB emulator with a container command
- Running a local Cosmos DB environment without provisioning cloud resources

■ AI-assisted workflow
- Using a short PRD and a Barcelona long-weekend scenario as the application example
- Applying GitHub Copilot, the Azure Cosmos DB Agent Kit, and the MCP Toolkit for data modeling and code generation
- Generating and refining NoSQL and vector queries from natural language
- Seeding the local emulator with travelers, trips, destinations, hotels, restaurants, and flights

■ Scope and next steps
- The episode covers local setup, data model design, code generation, query creation, and local testing
- It does not cover cloud deployment or vector, full-text, and hybrid search, which are introduced as the next episode

Developers who are new to Azure Cosmos DB or want to understand AI-assisted application development can use this episode to follow a local setup and workflow. Viewers can apply the described steps to move from a specification to a testable local application and prepare for the next episode on intelligent search over operational data.