This article explains how to set up OpenCode with Docker Model Runner for a private AI coding assistant. It covers configuration, model selection, and the benefits of maintaining control over data and costs. The guide also highlights coding-specific models that enhance development workflows.

This article investigates the data sent by seven popular AI coding agents during standard programming tasks. By intercepting their network traffic, the research highlights privacy and security concerns, revealing how these tools interact with user data and potential telemetry leaks.

Cline explains its decision not to index users' codebases, emphasizing the importance of privacy and security for developers. By not indexing code, Cline seeks to foster a more secure environment where users can work without the fear of exposing sensitive information. This approach ultimately benefits developers by allowing them to focus on their coding without concerns over data breaches.

AgenticSeek is a fully local AI assistant that autonomously browses the web, writes code, and plans tasks while ensuring complete privacy by operating solely on the user's hardware. It features voice capabilities, smart agent selection, and the ability to execute complex tasks without cloud dependency. The project is in active development and welcomes contributions from the open-source community.