ai: AI-Assisted Development powered by Local Models

The post highlights how running AI locally on developers’ devices addresses long-standing concerns about data privacy, dependency on cloud services, and limited control over tooling. By using local models, teams — especially those working on sensitive or regulated projects — can keep data on-device, customize workflows, reduce latency, and retain full control over model behavior. The article positions local models as a practical approach for AI-assisted development and is published on the Azure AI Foundry Blog.

• Source: Microsoft AI Foundry Blog