Conductor version 0.34.0 introduces a robust platform for orchestrating a team of artificial intelligence-powered coding agents specifically on Apple's macOS ecosystem. The core methodology centers on enabling parallel execution of heterogeneous large language models (LLMs), specifically integrating agents based on OpenAI's Codex and Anthropic's Claude Code models. Each agent operates within an isolated workspace, a sandboxed environment designed to prevent dependency conflicts and ensure operational independence, thereby enhancing stability and reproducibility of agent outputs. This isolation likely employs containerization or virtual environment techniques to manage distinct runtime contexts for each LLM instance. The system provides immediate visibility into the agents' ongoing tasks, allowing users to monitor their progress and current work status through an intuitive interface. A critical component of its workflow integration is the capability to facilitate human oversight and control: users can review the changes proposed or implemented by the agents and subsequently merge these modifications into a codebase, mirroring standard software development practices involving version control systems. This structured review-and-merge process ensures human-in-the-loop validation of AI-generated code, maintaining quality and control over the development pipeline.