Can AI-Generated Code Scale? Cosmos DB Demo Tests Agent Performance Under Load
adnan_hashmi · x · 2026-08-15
This GitHub repository accompanies an Azure Cosmos DB video titled "Let the Agent Write It—But Can It Scale?". It addresses a critical practical question: while AI agents can quickly generate working applications, will their data models, queries, and SDK usage still perform under realistic workloads?
Experiment Workflow:
- Prompt-Driven Build: Prompts describe what to build, not how. The agent creates a ticketing API without specialized Cosmos DB guidance.
- Baseline Capture: Deterministic data is seeded, and LoadGen captures a performance baseline.
- Optimization: The Azure Cosmos DB Agent Kit is installed to identify and repair scaling issues in the existing API, followed by a re-run of the tests.
The repo includes full Bicep configurations, a .NET 10 API, and the LoadGen testing harness, providing a concrete case study on the feasibility of AI-generated code in production environments.
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